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Title: DEVELOPMENT OF AN ARTIFICIAL NEURAL NETWORKS MODEL TO ESTIMATE DELAY USING TOLL PLAZA TRANSACTION DATA.
Creator: Muppidi, Aparna, Al-Deek, Haitham, University of Central Florida
Abstract / Description: In spite of the most up-to-date investigation of the relevant techniques to analyze the traffic characteristics and traffic operations at a toll plaza, there has not been any note worthy explorations evaluating delay from toll transaction data and using Artificial Neural Networks (ANN) at a toll plaza. This thesis lays an emphasis on the application of ANN techniques to estimate the total vehicular delay according to the lane type at a toll plaza. This is done to avoid the laborious task of...
Show moreIn spite of the most up-to-date investigation of the relevant techniques to analyze the traffic characteristics and traffic operations at a toll plaza, there has not been any note worthy explorations evaluating delay from toll transaction data and using Artificial Neural Networks (ANN) at a toll plaza. This thesis lays an emphasis on the application of ANN techniques to estimate the total vehicular delay according to the lane type at a toll plaza. This is done to avoid the laborious task of extracting data from the video recordings at a toll plaza. Based on the lane type a general methodology was developed to estimate the total vehicular delay at a toll plaza using ANN. Since there is zero delay in an Electronic Toll Collection (ETC) lane, ANN models were developed for estimating the total vehicular delay in a manual lane and automatic coin machine lane. Therefore, there are two ANN models developed in this thesis. These two ANN models were trained with three hours of data and validated with one hour of data from AM and PM peak data. The two ANN models were built with the dependent and independent variables. The dependent variables in the two models were the total vehicular delay for both the manual and automatic coin machine lane. The independent variables are those, which influence delay. A correlation analysis was performed to see if there exists any strong relationship between the dependent (outputs) and independent variables (inputs). These inputs and outputs are fed into the ANN models. The MATLABTB code was written to run the two ANN models. ANN predictions were good at estimating delay in manual lane, and delay in automatic coin machine lane.
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Date Issued: 2005
Identifier: CFE0000334, ucf:46298
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000334

Title: EVALUATING THE IMPACT OF OOCEA'S DYNAMIC MESSAGE SIGNS (DMS) ON TRAVELERS' EXPERIENCE USING THE PRE-DEPLOYMENT SURVEY.
Creator: Rogers, John, Al-Deek, Haitham, University of Central Florida
Abstract / Description: The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Pre-Deployment DMS Survey (henceforth referred to as "pre-deployment survey"). DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large...
Show moreThe purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Pre-Deployment DMS Survey (henceforth referred to as "pre-deployment survey"). DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA is currently in the process of adding several fixed DMS on their toll road network. Between January 2007 and February 2008, approximately 30 DMS are planned on their network. It is important to note that there was one DMS sign on the OOCEA network before this study started. Since most of the travelers on OOCEA toll roads are from Orange, Osceola and Seminole counties, this study is limited to these counties. This thesis documents the results of pre-deployment analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most used toll road, and county of residence) were asked to the respondents. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network. The respondents commonly agreed that the DMS are helpful for providing information about hazardous conditions, and that the DMS are easy to read. The majority of the travelers preferred DMS formats as a steady message for normal traffic conditions, and use of commonly recognized abbreviations such as I-Drive for International Drive. The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" display the significant variables that explain the likelihood of the traveler being satisfied. The results from the coefficients show that infrequent travelers are more likely to be satisfied with traveler information on OOCEA toll roads. In addition, the provision of hazard warnings, special event information, and accuracy of information on DMS are associated with higher levels of satisfaction with traveler information. The binary logit model for "Revealed Preference (RP)" diversion behavior showed that Seminole County travelers were likely to stay on the toll road, and SR 408 travelers were likely to divert off the toll road. The travelers who acknowledged DMS on the OOCEA network were also likely to divert off the toll road, but those who learned of the congestion by DMS were likely to stay on the toll road. Learning of congestion by DMS could encourage travelers to stay, since when they are on the toll roads, diversion at times could be difficult with no access to exits or little knowledge of alternate routes. But it is also possible that travelers stayed because their perception was that the toll roads are faster, especially when messages on DMS show travel times that confirm the travelers' belief. Travelers who were not satisfied with travel information on the network were more likely to divert off the toll road. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a steady message for normal traffic conditions. Commonly recognized abbreviations, such as I-Drive for International Drive, must be used for roadway identification when possible. DMS messages should be pertained to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. Accuracy of information provided on DMS was important for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. DMS information that led to the travelers canceling their intended stops led to a higher likelihood of them being dissatisfied with traveler information. It is important to meet the travelers' preferences and concerns for DMS.
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Date Issued: 2007
Identifier: CFE0001852, ucf:47374
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001852

Title: A GASOLINE DEMAND MODEL FOR THE UNITED STATES LIGHT VEHICLE FLEET.
Creator: Rey, Diana, Al-Deek, Haitham, University of Central Florida
Abstract / Description: ABSTRACT The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock...
Show moreABSTRACT The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close "gas guzzlers" plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States.
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Date Issued: 2009
Identifier: CFE0002539, ucf:47659
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002539

Title: UTILIZING A REAL LIFE DATA WAREHOUSE TO DEVELOP FREEWAY TRAVEL TIME ELIABILITY STOCHASTIC MODELS.
Creator: Emam, Emam, Al-Deek, Haitham, University of Central Florida
Abstract / Description: During the 20th century, transportation programs were focused on the development of the basic infrastructure for the transportation networks. In the 21st century, the focus has shifted to management and operations of these networks. Transportation network reliability measure plays an important role in judging the performance of the transportation system and in evaluating the impact of new Intelligent Transportation Systems (ITS) deployment. The measurement of transportation network travel...
Show moreDuring the 20th century, transportation programs were focused on the development of the basic infrastructure for the transportation networks. In the 21st century, the focus has shifted to management and operations of these networks. Transportation network reliability measure plays an important role in judging the performance of the transportation system and in evaluating the impact of new Intelligent Transportation Systems (ITS) deployment. The measurement of transportation network travel time reliability is imperative for providing travelers with accurate route guidance information. It can be applied to generate the shortest path (or alternative paths) connecting the origins and destinations especially under conditions of varying demands and limited capacities. The measurement of transportation network reliability is a complex issue because it involves both the infrastructure and the behavioral responses of the users. Also, this subject is challenging because there is no single agreed-upon reliability measure. This dissertation developed a new method for estimating the effect of travel demand variation and link capacity degradation on the reliability of a roadway network. The method is applied to a hypothetical roadway network and the results show that both travel time reliability and capacity reliability are consistent measures for reliability of the road network, but each may have a different use. The capacity reliability measure is of special interest to transportation network planners and engineers because it addresses the issue of whether the available network capacity relative to the present or forecast demand is sufficient, whereas travel time reliability is especially interesting for network users. The new travel time reliability method is sensitive to the users' perspective since it reflects that an increase in segment travel time should always result in less travel time reliability. And, it is an indicator of the operational consistency of a facility over an extended period of time. This initial theoretical effort and basic research was followed by applying the new method to the I-4 corridor in Orlando, Florida. This dissertation utilized a real life transportation data warehouse to estimate travel time reliability of the I-4 corridor. Four different travel time stochastic models: Weibull, Exponential, Lognormal, and Normal were tested. Lognormal was the best-fit model. Unlike the mechanical equipments, it is unrealistic that any freeway segment can be traversed in zero seconds no matter how fast the vehicles are. So, an adjustment of the developed best-fit statistical model (Lognormal) location parameter was needed to accurately estimate the travel time reliability. The adjusted model can be used to compute and predict travel time reliability of freeway corridors and report this information in real time to the public through traffic management centers. Compared to existing Florida Method and California Buffer Time Method, the new reliability method showed higher sensitivity to geographical locations, which reflects the level of congestion and bottlenecks. The major advantages/benefits of this new method to practitioners and researchers over the existing methods are its ability to estimate travel time reliability as a function of departure time, and that it treats travel time as a continuous variable that captures the variability experienced by individual travelers over an extended period of time. As such, the new method developed in this dissertation could be utilized in transportation planning and freeway operations for estimating the important travel time reliability measure of performance. Then, the segment length impacts on travel time reliability calculations were investigated utilizing the wealth of data available in the I-4 data warehouse. The developed travel time reliability models showed significant evidence of the relationship between the segment length and the results accuracy. The longer the segment, the less accurate were the travel time reliability estimates. Accordingly, long segments (e.g., 25 miles) are more appropriate for planning purposes as a macroscopic performance measure of the freeway corridor. Short segments (e.g., 5 miles) are more appropriate for the evaluation of freeway operations as a microscopic performance measure. Further, this dissertation has explored the impact of relaxing an important assumption in reliability analysis: Link independency. In real life, assuming that link failures on a road network are statistically independent is dubious. The failure of a link in one particular area does not necessarily result in the complete failure of the neighboring link, but may lead to deterioration of its performance. The "Cause-Based Multimode Model" (CBMM) has been used to address link dependency in communication networks. However, the transferability of this model to transportation networks has not been tested and this approach has not been considered before in the calculation of transportation networks' reliability. This dissertation presented the CBMM and applied it to predict transportation networks' travel time reliability that an origin demand can reach a specified destination under multimodal dependency link failure conditions. The new model studied the multi-state system reliability analysis of transportation networks for which one cannot formulate an "all or nothing" type of failure criterion and in which dependent link failures are considered. The results demonstrated that the newly developed method has true potential and can be easily extended to large-scale networks as long as the data is available. More specifically, the analysis of a hypothetical network showed that the dependency assumption is very important to obtain more reasonable travel time reliability estimates of links, paths, and the entire network. The results showed large discrepancy between the dependency and independency analysis scenarios. Realistic scenarios that considered the dependency assumption were on the safe side, this is important for transportation network decision makers. Also, this could aid travelers in making better choices. In contrast, deceptive information caused by the independency assumption could add to the travelers' anxiety associated with the unknown length of delay. This normally reflects negatively on highway agencies and management of taxpayers' resources.
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Date Issued: 2006
Identifier: CFE0000965, ucf:46709
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000965

Title: DEVELOPING MICROSCOPIC TOLL PLAZA MODEL USING PARAMICS.
Creator: Nezamuddin, Nezamuddin, Al-Deek, Haitham, University of Central Florida
Abstract / Description: Simulation modeling is the most cost-effective way of studying real life transportation problems, either existing or anticipated, without disturbing the balance of the transportation system. There is a vast suite of simulation models available in market, ready to choose from macroscopic, mesoscopic, or microscopic in nature, to study different transportation system elements like freeways, highways, signalized and un-signalized intersections. However, most of these network simulation models,...
Show moreSimulation modeling is the most cost-effective way of studying real life transportation problems, either existing or anticipated, without disturbing the balance of the transportation system. There is a vast suite of simulation models available in market, ready to choose from macroscopic, mesoscopic, or microscopic in nature, to study different transportation system elements like freeways, highways, signalized and un-signalized intersections. However, most of these network simulation models, like PARAMICS, VISSIM, CORSIM … etc, do not come readily available with built in toll plaza models. On the other hand, many researchers have independently developed toll plaza models, which can only model an isolated toll plaza without the road network. These toll plaza models, which are based on queuing theory (and some are macroscopic in nature), do not take into account headway, gap acceptance, or inter-vehicle interaction to follow a lead car or to perform lane changing maneuvers. Vehicles just upstream of the toll plaza are assigned to one of the toll lanes, solely based on the payment method (manual, automatic coin machine, or electronic toll collection) and queue lengths at the toll lanes. For instance, if a vehicle is traveling in the leftmost lane and the rightmost toll lane has the shortest queue length, then the queuing model will assign this vehicle to the rightmost lane, and the vehicle will do unrealistic maneuvering to reach to the assigned toll lane instantly. Microscopic network simulation models simulate the vehicular movements based on lane-changing and car-following rules. If such a model could be customized to serve the purpose of the toll plaza simulation, it will simulate the vehicular movements just upstream and downstream of the toll plaza more realistically. Being a network simulation model, it can also model the road network integrated with the plaza, which can be used to study the entire toll road corridor, unlike the isolated toll plaza models. In addition to being a microscopic network simulation model, PARAMICS has many simulation tools, which can be customized to develop a network model with enhanced toll plaza simulation capabilities. PARAMICS also provides the flexibility of using an aerial picture of the toll plaza and upstream/downstream sections of the road as overlay, to ensure that the toll plaza model operates under similar geometric conditions as the real plaza. Using an overlay, exact details of the transition area can be fed into the model. In real life, there is a smooth transition (in terms of the number of lanes and the width of the roadway) from the uniform free-flowing section of the roadway to the toll plaza. Detailed representation of the transition area, in terms of geometry and curb of the roadway along with the number of lanes, is essential for a realistic toll plaza simulation. This kind of detail is not available in a queuing model. As the roadway approaches the toll plaza, it contains more lanes compared to its upstream segments. However, in a simulation model vehicles have a tendency to maintain the same old lanes, and the newly added lanes remain unoccupied by the vehicles. Next-lane Allocation feature in PARAMICS can be used to map upstream lanes onto downstream lanes, preventing this unrealistic behavior from occurring in the simulation model. It tells the vehicles in a particular upstream lane to choose from one or more of the downstream lanes as per the settings. Next-lane allocation can be used in such a manner that all the downstream lanes are utilized. PARAMICS has several other tools such as Restrictions Manager, Vehicle Type Manager, Lane-choices Rules, HOV Lanes, and Vehicle Actuated (VA) Signals which can be used in combination to build a toll plaza model. A microscopic 'Holland East Plaza - SR408' network model has been developed using PARAMICS V5.1. This model contains the plaza and the downstream section of SR 408 Westbound till I-4 interchange in downtown Orlando. This model has been successfully calibrated and validated for the mainline toll plaza and ramp volumes for year 2004. Several hypothetical incident scenarios were simulated to study an entire corridor from the toll plaza to Interstate 4. It was found that the volumes on I-4 off-ramp and SR 408 mainline were affected the most under incident conditions. Volumes for other ramps were not affected in the same proportions. An incident on mainline toll road affected the throughput of the plaza significantly, but the same is not true for an incident on an off-ramp. Travel times to I-4 off-ramps and SR 408 thru lanes were the most sensitive in each of the incident scenarios. In case of the elimination of tolls during the hurricane evacuation, the throughput of the plaza increased significantly. Travel times for the vehicles coming through the plaza and going to different destinations decreased significantly, while it increased for vehicles using on-ramps, because of their inability to merge in the mainline traffic due to the increased toll road volume. The developed model in this thesis has the potential of transportation network wide applications with multiple toll plazas.
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Date Issued: 2006
Identifier: CFE0001183, ucf:46851
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001183

Title: EVALUATING THE IMPACT OF OOCEA'S DYMANIC MESSAGE SIGNS (DMS) ON TRAVELERS' EXPERIENCE USING A PRE AND POST-DEPLOYMENT SURVEY.
Creator: Flick, Jason, Al-Deek, Haitham, University of Central Florida
Abstract / Description: The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using a Pre and Post-Deployment DMS Survey (henceforth referred to as "pre and post-deployment survey") analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this...
Show moreThe purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using a Pre and Post-Deployment DMS Survey (henceforth referred to as "pre and post-deployment survey") analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA have been working over the past two years to add several fixed DMS on their toll road network. At the time of the pre-deployment survey, only one DMS was installed on the OOCEA toll road network. At the time of the post-deployment survey, a total of 30 DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads are from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results and comparisons between the pre and post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006, and the post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. The results of both the pre and post-deployment surveys are discussed in this thesis, but it should be noted that the more telling results are those of the post-deployment survey. The results of the post-deployment survey show the complete picture of the impact of DMS on travelers' experience on the OOCEA toll road network. The pre-deployment results are included to show an increase or decrease in certain aspects of travel experience with relation to DMS. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network, while a total of 63.93% of the OOCEA travelers recalled seeing DMS during the post-deployment analysis. This showed an increase of almost 10% between the two surveys demonstrating the people are becoming more aware of DMS on the OOCEA toll road network. The respondents commonly agreed that the DMS were helpful for providing information about hazardous conditions, and that the DMS are easy to read. Also, upon further research it was found that between the pre and post-deployment surveys the travelers' satisfaction with special event information provided on DMS and travel time accuracy on DMS increased significantly. With respect to formatting of the DMS, the following methods were preferred by the majority of respondents in both the pre and post-deployment surveys: • Steady Message as a default DMS message format • Flashing Message for abnormal traffic information (94% of respondents would like to be notified of abnormal traffic information) • State road number to show which roadway (for Colonial – SR 50, Semoran – SR 436 and Alafaya – SR 434) • "I-Drive" is a good abbreviation for International Drive • If the distance to the international airport is shown on a DMS it thought to be the distance to the airport exit The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" displayed the significant variables that explained the likelihood of the traveler being satisfied. This satisfaction model was based on respondents who showed a prior knowledge of DMS on OOCEA toll roads. With the use of a pooled model (satisfaction model with a total of 1775 responses – 816 from pre-deployment and 959 from post-deployment), it was shown that there was no statistical change between the pre and post-deployment satisfaction based on variables thought to be theoretically relevant. The results from the comparison between the pre and post-deployment satisfaction models showed that many of the coefficients of the variables showed a significant change. Although some of the variables were statistically insignificant in one of the two survey model results: Either the pre or post-deployment model, it was still shown that every variable was significant in at least one of the two models. The coefficient for the variable corresponding to DMS accuracy showed a significantly lower value in the post-deployment model. The coefficient for the variable "DMS was helpful for providing special event information" showed a significantly higher value in the post-deployment model. The final post-deployment diversion model was based on a total of 732 responses who answered that they had experienced congestion in the past 6 months. Based on this final post-deployment diversion model, travelers who had stated that their most frequently traveled toll road was either SR 408 or SR 417 were more likely to divert. Also, travelers who stated that they would divert in the case of abnormal travel times displayed on DMS or stated that a DMS influenced their response to congestion showed a higher likelihood of diversion. These two variables were added between the pre and post-deployment surveys. It is also beneficial to note that travelers who stated they would divert in a fictitious congestion situation of at least 30 minutes of delay were more likely to divert. This shows that they do not contradict themselves in their responses to Revealed Preference and Stated Preference diversion situations. Based on a comparison between pre and post-deployment models containing similar variables, commuters were more likely to stay on the toll road everything else being equal to the base case. Also, it was shown that in the post-deployment model the respondents traveling on SR 408 and SR 417 were more likely to divert, but in the pre-deployment model only the respondents traveling on SR 408 were more likely to divert. This is an expected result since during the pre-deployment survey only one DMS was located on SR 408, and during the post-deployment survey there were DMS located on all toll roads. Also, an interesting result to be noted is that in the post-deployment survey, commuters who paid tolls with E-pass were more likely to stay on the toll road than commuters who paid tolls with cash. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a flashing message for abnormal traffic situations and the state road number should be used to identify a roadway. DMS messages should pertain to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. The travel time accuracy on DMS was shown to be significant for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. Finally, it is important to meet the travelers' preferences and concerns for DMS.
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Date Issued: 2008
Identifier: CFE0002295, ucf:47862
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002295

Title: IMPACT OF CONSTRUCTION ON FREEWAY TRAFFIC OPERATIONS.
Creator: Jagtap, Seema, Al-Deek, Haitham, University of Central Florida
Abstract / Description: This study provides an insight into the impact of construction activities on traffic operations. Specifically, the topic of interest for this thesis is to study the impact of construction on traffic operations for construction projects on Interstate 4 from SR 434 to John Young Parkway, from SR 528 to SR 535, and from SR 482 to SR 528. These three projects were chosen because they were the only projects on Interstate 4 where both construction data and loop detector data were available for...
Show moreThis study provides an insight into the impact of construction activities on traffic operations. Specifically, the topic of interest for this thesis is to study the impact of construction on traffic operations for construction projects on Interstate 4 from SR 434 to John Young Parkway, from SR 528 to SR 535, and from SR 482 to SR 528. These three projects were chosen because they were the only projects on Interstate 4 where both construction data and loop detector data were available for analysis. The data was collected by examining the Florida Department of Transportation daily inspection reports which had detailed documentation of construction operations that took place. The following information was collected: date, type of construction work being performed, time, location, and direction of impact to the traveling public. These data points were cross-referenced to the loop detector stations and mile posts to collect the loop detector data and roadway geometric characteristics such as location of ramps, type of median, etc. The loop detector data (speed, volume, and occupancy) were collected and aggregated for the data analysis. The loop detector data were collected during construction, one year prior to construction, and one year after construction for comparison purposes. Logistic regression analysis under the within-stratum matched sampling framework was conducted as an exploratory analysis to see if there was a difference on the traffic impacts with and without construction. This was done by matching the variables to ensure that there were no other differences impacting the traffic operations. Logistic regression proved there was a difference in the traffic operations with and without the presence of construction. The simple model results demonstrated that speed was reduced, occupancy was increased, and volume decreased during construction. After construction, the speed and volume increased and the occupancy decreased. Linear regression and analysis of covariance were used to quantify the impact of the various construction activities on the speed, occupancy and volume. Linear regression and analysis of covariance were used to understand the impacts from the presence of roadway geometrics on freeway traffic operations during construction. Logistic regression controls the geometrics, linear regression and analysis of covariance demonstrated how the geometrics impacted the construction effects. The geometric characteristics of each area were included in this analysis. This thesis investigates construction activities and roadway geometric parameters that impact traffic freeway operations (speed, volume, and occupancy) before, during, and after construction. This research showed the impact of different types of construction operations in a highway construction widening project. This research demonstrated that construction activities have a significant impact on speed, volume, and occupancy. Different types of construction activities have more of an impact than other activities. Paving had the highest adverse impact. Agencies writing construction contracts should prohibit paving during the most highly congested times. For example, in Orlando, Florida on Interstate 4, agencies should prohibit night paving during the peak holiday seasons (such as Thanksgiving, spring breaks, Christmas, etc.) around the tourist attractions during closing times, during the peak morning hours, and during the closing times of high attendance activities, such as Halloween Horror Nights at Universal Studios when high attendance is anticipated at the theme parks. Roadway geometrics also impact the traffic operations differently, before, during, and after construction and differently during various times of the day. The information of improved roadway geometrics and faster traffic flow can be used at open houses for upcoming projects where there are many people opposed to construction projects to show how the roadway construction projects actually increase traffic flow, helping everyone to get to their destinations much faster. The impact of the traffic delays in the congested areas, such as the tourist areas on Interstate 4 during the peak traffic times could be quantified to calculate delay costs to the roadway users.
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Date Issued: 2008
Identifier: CFE0002201, ucf:47887
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002201

Title: EVALUATING THE IMPACT OF OOCEA'S DYMANIC MESSAGE SIGNS (DMS) ON TRAVELERS' EXPERIENCE USING MULTINOMIAL AND ORDERED LOGIT FOR THE POST-DEPLOYMENT SURVEY.
Creator: Lochrane, Taylor, Al-Deek, Haitham, University of Central Florida
Abstract / Description: The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Post-Deployment DMS Survey analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes...
Show moreThe purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Post-Deployment DMS Survey analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA has added twenty-nine fixed DMS to their toll road network from 2006-2008. At the time of the post-deployment survey, a total of twenty-nine DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads were from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results for the post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interview. The post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. This thesis is using results of the multinomial logit model for diversion of traffic. This model takes into account the different diversion decisions from the post development survey (stay vs. divert all the way vs. divert and come back vs. abandon trip) and explains the differences in the diversion behavior. Drivers that use SunPass or Epass tend to stay on the toll road during unexpected congestion. Frequent SR 408 users are more likely to divert and stay off the toll road and frequent SR 417 users are more likely to divert and get back on the toll road. Drivers whose stated preference was to divert off the toll road were more likely to do the same in the real world. However, not too many of the respondents were likely to abandon their trips in the real world even if they said they would in a hypothetical congestion scenario. Users of 511 were more likely to divert and get back on the toll road or abandon their trips due to unexpected congestion. OOCEA can use this study to concentrate on keeping their toll roads more attractive during unexpected congestion to keep drivers from diverting all the way or abandoning their trips. For example, better incident management in clearing accidents more efficiently (thereby decreasing delay) and encouraging the use of SunPass or EPass could help drivers stay than divert or abandon their trip. This thesis also used ordered logit model for satisfaction. This model explains the levels of magnitude of satisfaction with traveler information on OOCEA toll roads. Drivers who acquired traveler information from DMS were less likely to be dissatisfied with traveler information provided on toll roads than other respondents. Drivers who were satisfied with accuracy and information on hazard warnings on DMS were more likely to be satisfied with information provided on toll roads than other respondents. This thesis provides a microscopic insight on the driver behavior on toll roads. This thesis expands the diversion and satisfaction models from previous studies in a way that OOCEA can identify specific groups of drivers related to a given response behavior (i.e., diverts off toll roads or dissatisfied with traveler information). Such analysis can be conducted in the future in the same study area or replicated in other areas to quantify the effects of individual and choice related attributes on choice behavior.
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Date Issued: 2009
Identifier: CFE0002711, ucf:48169
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002711

Title: EVALUATION OF THE POTENTIAL BENEFITS TO TRAFFIC OPERATIONS AT A TOLL PLAZAWITH EXPRESS ETC LANES.
Creator: Gordin, Eric Anthony, Al-Deek, Haitham M., University of Central Florida
Abstract / Description: The effectiveness of modifying a conventional toll plaza for implementation of an open road tolling concept with express ETC lanes was evaluated in this thesis. Speed controlled dedicated ETC lanes were replaced with express ETC lanes at the Orlando-Orange County Expressway Authority (OOCEA) University Mainline Toll Plaza. This evaluation was accomplished by utilizing collected field data and simulated scenarios using Toll Plaza SIMulation (TPSIM) software developed by the University of...
Show moreThe effectiveness of modifying a conventional toll plaza for implementation of an open road tolling concept with express ETC lanes was evaluated in this thesis. Speed controlled dedicated ETC lanes were replaced with express ETC lanes at the Orlando-Orange County Expressway Authority (OOCEA) University Mainline Toll Plaza. This evaluation was accomplished by utilizing collected field data and simulated scenarios using Toll Plaza SIMulation (TPSIM) software developed by the University of Central Florida. The speed controlled dedicated ETC lanes were located within toll lanes (contained within a toll plaza canopy) with widths ranging between 10 to 14 ft. These types of lanes required all vehicles to reduce their speed from the highway speed to 35 mph. Express ETC lanes (sometimes referenced as open road tolling or non-stop tolling) allow vehicles to pass through the plaza at high speeds. Open road tolling is a concept that employs high speed toll lanes.A before and after study of the University toll plaza was conducted. Benefits in the form of reduced delays and increased capacities were observed when making the comparison between the before and after studies. Since we expect the capacity of an express ETC lane to be greater than the dedicated ETC lanes (due to an increase in free-flow speed), further analysis using equations and car-following theory proved that if the ETC speed was increased, then the capacity would increase as well. Using equations derived from the Highway Capacity Manual (HCM) and car-following theory, the capacity was increased from 2016 to 2314 vph when the ETC speed increased from 31 mph to 65 mph. This indicated an increase in capacity of 14.8 percent (based on the conversion from dedicated to express ETC lanes). The field data was also used as input for TPSIM (a computer simulation model) in order to perform a sensitivity analysis of the express ETC lanes by varying the type of ETC lane, number of approach lanes, and plaza configurations (the addition of an ACM lane) between scenarios. Results that were observed during the after study were verified using the TPSIM scenarios. Reductions in delays for the entire plaza were observed using the TPSIM model when making similar improvements to the plaza as in the after study.The changes made to the University Mainline Toll Plaza after construction was completed resulted in benefits by reducing delays and increasing the capacity of the toll plaza (by converting dedicated ETC lanes to express ETC lanes and adding an additional A/ETC lane per direction). These benefits were measured using field data and confirmed when performing the TPSIM scenarios. A customer's travel time along the toll facility will be reduced by using the express ETC lanes (since they are not required to decelerate at the toll plaza). In addition, weaving maneuvers downstream of the plaza are no longer required by customers using the express ETC lanes due to the location of the downstream travel lanes in relation to the express ETC lanes. These benefits may have led to changes in the number and percentage of ETC users in each of the toll lanes. Changes in ETC usage in the conventional mixed-use lanes directly impacted the throughput and delays for each of these lanes, since ETC equipped vehicles have a service time of zero seconds. In addition to the operational benefits, other possible benefits for express ETC lanes were identified and recommended for further evaluation and research. The re-distribution of customers at the plaza due to the implementation of open road tolling, in the form of express ETC lanes, was a great benefit to the overall traffic operations for the University Mainline Toll Plaza in Orlando, Florida.
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Date Issued: 2004
Identifier: CFE0000057, ucf:46072
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000057

Title: EVALUATION OF THE IMPACTS OF ITS INFORMATION STRATEGIES ON I-4 CORRIDOR.
Creator: Zuo, Yueliang, Al-Deek, Haitham M., University of Central Florida
Abstract / Description: This study evaluated the impacts of ITS information strategies under incident conditions in Interstate 4 (I-4) corridor of Orlando. The analysis was performed using DYNASMART-P software package. The ITS information strategies range from pre-trip information, en-route information, and variable message signs. Simulation covered one hour during the morning peak period. The impacts of ITS information strategies on mobility were evaluated by simulating the performance of various ITS information...
Show moreThis study evaluated the impacts of ITS information strategies under incident conditions in Interstate 4 (I-4) corridor of Orlando. The analysis was performed using DYNASMART-P software package. The ITS information strategies range from pre-trip information, en-route information, and variable message signs. Simulation covered one hour during the morning peak period. The impacts of ITS information strategies on mobility were evaluated by simulating the performance of various ITS information components (pre-trip information, en-route information, and variable message signs) under incident conditions for the I-4 corridor and comparing the results with the corresponding scenarios in the absence of these components. The traffic flow relations were calibrated against the flow measurements along freeway to determine model parameters. An effort was made to validate estimated traffic volumes against measured link counts. The archived I-4 data at the Center for Advanced Transportation Systems Simulation (CATSS) at the University of Central Florida was used for both calibration and validation. The analysis indicated that DYNASMART-P was able to adequately reproduce the observed morning peak hourly flows over suitably selected locations.Ten scenarios were designed to evaluate the benefits of ITS information strategies under incident conditions. The results indicated that these ITS traveler information technologies can result in great travel time saving. It was found that commuters who use traveler information via the pre-trip information or en-route information to switch their routes benefit significantly in terms of delay reduction when incidents occur. It was found that there exists an optimal value for the fraction users with information at which the network performs best. This optimal fraction may be different for different source of information. Also this may vary with different incidents. This study demonstrates how one can realistically simulate the network under various scenarios without actually conducting the high cost operational tests. DYNASMART-P can produce useful variables such as speeds, travel time, queue lengths, and stop time to better assess the impacts of ITS components. It can be applied in ITS equipped networks.
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Date Issued: 2004
Identifier: CFE0000107, ucf:46199
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000107

Title: INVESTIGATING AND MODELING THE IMPACTS OF ILLEGAL U-TURN VIOLATIONS AT MEDIANS LOCATED ON FLORIDA'S LIMITED ACCESS HIGHWAYS.
Creator: Al-Sahili, Omar, Al-Deek, Haitham, Hasan, Samiul, Mantzaris, Alexander, University of Central Florida
Abstract / Description: Illegal U-turn violations are considered part of the Wrong-Way Driving (WWD) maneuvers that could result in head-on crashes and severe injuries, which are often severe because of the high speed of the approaching traffic and limited time to avoid such crash. Therefore, reviewing this type of violation and understanding the contributing factors that may lead drivers to commit such illegal maneuver would help officials foresee and consequently minimize the potential risks that could lead to WWD...
Show moreIllegal U-turn violations are considered part of the Wrong-Way Driving (WWD) maneuvers that could result in head-on crashes and severe injuries, which are often severe because of the high speed of the approaching traffic and limited time to avoid such crash. Therefore, reviewing this type of violation and understanding the contributing factors that may lead drivers to commit such illegal maneuver would help officials foresee and consequently minimize the potential risks that could lead to WWD crashes. The purpose of this thesis is to investigate the illegal U-turn maneuvers on limited access facilities and find the significant contributing factors that encourage or discourage drivers to commit this type of violation. The study area included the Central Florida area (CF), and the South Florida (SF) area. About 6 crossover crashes and 620 citations were found at the median facilities in the study areas from year 2011 to 2016.The modeling methodology for this thesis had three goals: predicting the number of illegal U-turn violations across the traversable grass median sections per year using a Poisson regression model, selecting the most effective variables in predicting the illegal U-turn violations using the least absolute shrinkage and selection operator (LASSO) variable selection method, and estimating the probability of an illegal U-turn violation occurrence at a paved median opening for official use only per year, using a logistic regression model. To determine the variables that influence the illegal U-turn violations, 9 geometric design and 2 traffic conditions exploratory variables were analyzed in the models mentioned earlier. Several variables were found significant from the Poisson model such as the distance to the nearest interchange, the length of the median segment, the number of access points in the segment, the median design, and the speed limit. Afterwards, the LASSO method concluded that the most effective variables found were the median design and the distance of to the nearest interchange. The logistic regression model in the CF area indicated that the speed limit and the AADT as the significant contributing factors. However, in the SF area the significant variables were the distance to the nearest access point and the spacing between the median openings. The variation in results indicates a considerable difference between the two study areas that should be accounted for during the planning phases for allocating the median countermeasures. The significant variables found in the mentioned modeling approach provide a first attempt to understand the illegal U-turn violations on limited access highways, and interpret the variables which influence drivers' behavior in performing such illegal maneuver. Along with required design guidelines, the models found could be used as effective planning tools to select the appreciate locations for installing new median openings and reevaluating the existing median openings to identify locations with the lowest potential risk.Other modeling techniques that include additional factors could be tested in future research so that appropriate countermeasures can be installed to reduce or eliminate these illegal U-turns. Furthermore, the methodology could be extended to arterials (or roads with partially controlled access).
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Date Issued: 2017
Identifier: CFE0006708, ucf:51905
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006708

Title: Sustainability Analysis of Intelligent Transportation Systems.
Creator: Ercan, Tolga, Tatari, Mehmet, Al-Deek, Haitham, Oloufa, Amr, University of Central Florida
Abstract / Description: Commuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable...
Show moreCommuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable impacts of the congested roadway problem, Intelligent Transportation Systems (ITS) has been utilized to improve sustainable transportation systems in the world. The purpose of this thesis is to analyze the sustainable impacts and performance of the utilization of ITS in the United States. This thesis advances the body of knowledge of sustainability impacts of ITS related congestion relief through a triple bottom line (TBL) evaluation in the United States. TBL impacts analyze from a holistic perspective, rather than considering only the direct economic benefits. A critical approach to this research was to include both the direct and the indirect environmental and socio-economic impacts associated with the chain of supply paths of traffic congestion relief. To accomplish this aim, net benefits of ITS implementations are analyzed in 101 cities in the United States. In addition to the state level results, seven metropolitan cities in Florida are investigated in detail among these 101 cities. For instance, the results of this study indicated that Florida saved 1.38 E+05 tons of greenhouse gas emissions (tons of carbon dioxide equivalent), $420 million of annual delay reduction costs, and $17.2 million of net fuel-based costs. Furthermore, to quantify the relative impact and sustainability performance of different ITS technologies, several ITS solutions are analyzed in terms of total costs (initial and operation (&) maintenance costs) and benefits (value of time, emissions, and safety). To account for the uncertainty in benefit and cost analyses, a fuzzy-data envelopment analysis (DEA) methodology is utilized instead of the traditional DEA approach for sustainability performance analysis. The results using the fuzzy-DEA approach indicate that some of the ITS investments are not efficient compared to other investments where as all of them are highly effective investments in terms of the cost/benefit ratios approach. The TBL results of this study provide more comprehensive picture of socio-economic benefits which include the negative and indirect indicators and environmental benefits for ITS related congestion relief. In addition, sustainability performance comparisons and TBL analysis of ITS investments contained encouraging results to support decision makers to pursue ITS projects in the future.
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Date Issued: 2013
Identifier: CFE0004994, ucf:49549
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004994

Title: SPATIO-TEMPORAL ANALYSES FOR PREDICTION OF TRAFFIC FLOW, SPEED AND OCCUPANCY ON I-4.
Creator: Chilakamarri Venkata, Srinivasa Ravi Chandra, Al-Deek, Haitham, University of Central Florida
Abstract / Description: Traffic data prediction is a critical aspect of Advanced Traffic Management System (ATMS). The utility of the traffic data is in providing information on the evolution of traffic process that can be passed on to the various users (commuters, Regional Traffic Management Centers (RTMCs), Department of Transportation (DoT),etc) for user-specific objectives. This information can be extracted from the data collected by various traffic sensors. Loop detectors collect traffic data in the form of...
Show moreTraffic data prediction is a critical aspect of Advanced Traffic Management System (ATMS). The utility of the traffic data is in providing information on the evolution of traffic process that can be passed on to the various users (commuters, Regional Traffic Management Centers (RTMCs), Department of Transportation (DoT),…etc) for user-specific objectives. This information can be extracted from the data collected by various traffic sensors. Loop detectors collect traffic data in the form of flow, occupancy, and speed throughout the nation. Freeway traffic data from I-4 loop detectors has been collected and stored in a data warehouse called the Central Florida Data Warehouse (CFDWTM) by the University of Central Florida for the periods between 1993 – 1994 and 2000 - 2003. This data is raw, in the form of time stamped 30-second aggregated data collected from about 69 stations over a 36 mile stretch on I-4 from Lake Mary in the east to Disney-World in the west. This data has to be processed to extract information that can be disseminated to various users. Usually, most statistical procedures assume that each individual data point in the sample is independent of other data points. This is not true to traffic data as they are correlated across space and time. Therefore, the concept of time sequence and the layout of data collection devices in space, introduces autocorrelations in a single variable and cross correlations across multiple variables. Significant autocorrelations prove that past values of a variable can be used to predict future values of the same variable. Furthermore, significant cross-correlations between variables prove that past values of one variable can be used to predict future values of another variable. The traditional techniques in traffic prediction use univariate time series models that account for autocorrelations but not cross-correlations. These models have neglected the cross correlations between variables that are present in freeway traffic data, due to the way the data are collected. There is a need for statistical techniques that incorporate the effect of these multivariate cross-correlations to predict future values of traffic data. The emphasis in this dissertation is on the multivariate prediction of traffic variables. Unlike traditional statistical techniques that have relied on univariate models, this dissertation explored the cross-correlation between multivariate traffic variables and variables collected across adjoining spatial locations (such as loop detector stations). The analysis in this dissertation proved that there were significant cross correlations among different traffic variables collected across very close locations at different time scales. The nature of cross-correlations showed that there was feedback among the variables, and therefore past values can be used to predict future values. Multivariate time series analysis is appropriate for modeling the effect of different variables on each other. In the past, upstream data has been accounted for in time series analysis. However, these did not account for feedback effects. Vector Auto Regressive (VAR) models are more appropriate for such data. Although VAR models have been applied to forecast economic time series models, they have not been used to model freeway data. Vector Auto Regressive models were estimated for speeds and volumes at a sample of two locations, using 5-minute data. Different specifications were fit – estimation of speeds from surrounding speeds; estimation of volumes from surrounding volumes; estimation of speeds from volumes and occupancies from the same location; estimation of speeds from volumes from surrounding locations (and vice versa). These specifications were compared to univariate models for the respective variables at three levels of data aggregation (5-minutes, 10 minutes, and 15 minutes) in this dissertation. For data aggregation levels of <15 minutes, the VAR models outperform the univariate models. At data aggregation level of 15 minutes, VAR models did not outperform univariate models. Since VAR models were used for all traffic variables reported by the loop detectors, this made the application of VAR a true multivariate procedure for dynamic prediction of the multivariate traffic variables – flow, speed and occupancy. Also, VAR models are generally deemed more complex than univariate models due to the estimation of multiple covariance matrices. However, a VAR model for k variables must be compared to k univariate models and VAR models compare well with AutoRegressive Integrated Moving Average (ARIMA) models. The added complexity helps model the effect of upstream and downstream variables on the future values of the response variable. This could be useful for ATMS situations, where the effect of traffic redistribution and redirection is not known beforehand with prediction models. The VAR models were tested against more traditional models and their performances were compared against each other under different traffic conditions. These models significantly enhance the understanding of the freeway traffic processes and phenomena as well as identifying potential knowledge relating to traffic prediction. Further refinements in the models can result in better improvements for forecasts under multiple conditions.
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Date Issued: 2009
Identifier: CFE0002593, ucf:48276
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002593

Title: Evaluating Travelers Experience with Highway Advisory Radio (HAR) And Citizens Band Radio Advisory System (CBRAS) On Florida's Turnpike Enterprise Toll Roadways And Florida Interstate Highways.
Creator: Muhaisen, Nabil, Al-Deek, Haitham, Eluru, Naveen, Tatari, Omer, University of Central Florida
Abstract / Description: The goal of this thesis is to evaluate travelers' experience with Highway Advisory Radio (HAR) and Citizens' Band Radio Advisory System (CBRAS) technologies on both Florida Interstate Highway system (FIH) and the Florida Turnpike Enterprise (FTE) toll roads. To achieve this goal, two different survey tools were used. The first tool is a random digit dialing phone survey known as CATI (Computer-Assisted Telephone Interviewing). The second tool is a field survey that intercepts travelers at the...
Show moreThe goal of this thesis is to evaluate travelers' experience with Highway Advisory Radio (HAR) and Citizens' Band Radio Advisory System (CBRAS) technologies on both Florida Interstate Highway system (FIH) and the Florida Turnpike Enterprise (FTE) toll roads. To achieve this goal, two different survey tools were used. The first tool is a random digit dialing phone survey known as CATI (Computer-Assisted Telephone Interviewing). The second tool is a field survey that intercepts travelers at the Florida Turnpike Enterprise (FTE) service plazas and the Florida Interstate Highway (FIH) rest areas.HAR and CBRAS are traditional components of the Advanced Traveler Information Systems (ATIS). This thesis pays special attention to the effectiveness of HAR and CBRAS in improving travelers' experience. Feedback to analyze these two technologies was collected via a telephonic survey and a field survey. Two different field surveys (one for HAR and one for CBRAS) were designed and implemented to obtain feedback on these technologies. The field survey for CBRAS is unique and has never been done before for this purpose.A sample size of 1000 HAR surveys was collected through the CATI phone survey. Field surveys were collected at five locations across the state, including central, southeast, and southwest regions of Florida. The HAR field survey sample size was 1610 and the CBRAS field survey sample size was 613. All field surveys were conducted by UCF students at each of the five locations, over a 13-week data collection period. The HAR messages were designed to alert drivers of any adverse roadway traffic or weather conditions. The CBRAS is limited to truck drivers with the closed system radio pre-installed in their vehicles. However, truck drivers were also asked some questions on HAR if they do not use CBRAS.Basic statistical analysis was used to determine a number of performance indicators which include system's use and awareness, usability of provided information, route diversion, and travelers' demographics. In addition, the two HAR phone and field samples were combined together and examined using a decision tree model. Target questions were selected from the survey to build the tree network. The tree model aimed at identifying trends between categorical differences of travelers with respect to specific questions. Understanding travelers' satisfaction with HAR is critical to knowing its benefits. The ending results indicated that both basic statistical analysis and the decision tree model are in agreement. A comparison between HAR phone and field surveys indicates the following. Travelers interviewed for the HAR field survey were more aware of the HAR than travelers surveyed by phone. A small portion of the surveyed samples used HAR (22% and this was consistent between the phone and the field surveys). Also, 80% or more were satisfied with HAR for both phone and field samples and the majority (85% or more) supported its continuation as an indication of willingness to use it in the future, especially in emergency conditions. In terms of the types of messages they want to hear from HAR, traffic congestion was the most common. Dynamic Message Signs (DMS) were the most preferred source of travel information and were the alternative for HAR, if HAR gets terminated. This was followed by smartphone applications which received twice as much support from field surveyed travelers (28%) when compared to phone surveyed travelers (15%).The CATI Phone Survey was biased towards elderly people (60% of the sample) and mainly females (58%) that use the FTE roadway system. Users satisfied with the system are those who only use these roadways once per week or less. The survey ultimately shows that travelers rely on modern modes of obtaining traffic information than traditional ones, such as HAR. DMS, and smart phone applications are leading communication tools among all type of travelers. The HAR field survey was less biased with respect to age and gender distribution (56% were under 50 and 62% were males). Both surveys indicate that the sample is well educated (about 60% have an associate degree or higher). CBRAS serves a small segment of commercial truck drivers (only 12% out of 613 used CBRAS). However, this small segment used it heavily (84% used it sometimes, often, or always). And 92% of CBRAS users were satisfied or strongly satisfied with it. CBRAS was used mostly for route divergence, with 72% of the drivers relying on it for this purpose. Truck drivers who never used CBRAS (88% of the sample) were asked questions about HAR. Only 27% of them used HAR and 57% of these used it sometimes, often, or always with 72% of the truck users being satisfied with HAR compared to the 92% satisfied with CBRAS. The most common complaint about HAR by truck drivers was that it is not easy to access or understand. Based on responses of truck drivers for both HAR and CBRAS field surveys above, it seems that GPS navigation was the most preferred source of travel information (28%). In addition to the basic statistics, a decision tree model, using SAS Enterprise Miner was performed. The statistical analysis results indicated satisfaction of travelers. The decision tree model was used to predict and profile responses to all answered questions that each survey shared. Training data was included in the model and the model was able to leverage the questions. Results of the decision tree model predicted high user satisfaction rates.Analyses of the three implemented surveys show that HAR and CBRAS technologies are not used by a large proportion of travelers, but their users are typically satisfied with these technologies. A small portion of the surveyed sample of truck drivers uses CBRAS but they use it heavily and were very satisfied with it. The travelers' satisfaction level with HAR was high. The HAR and CBRAS systems are in the middle of a heated competition lead by digital communication, it may be a sign of the time to create HAR/CBRAS smart phone applications for the longevity of these traditional technologies.
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Date Issued: 2015
Identifier: CFE0006045, ucf:50983
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006045

Title: Wrong-Way Driving: A Regional Approach To A Regional Problem.
Creator: Faruk, Md. Omar, Al-Deek, Haitham, Uddin, Nizam, Hasan, Samiul, University of Central Florida
Abstract / Description: Wrong-way driving (WWD) has been problematic on United States highways for decades despite its rare occurrence. Since WWD crashes are rare, recent researchers have studied WWD non-crash events such as WWD 911 calls and WWD citations to understand the overall nature and trend of WWD. This paper demonstrates the regional nature of the WWD problem and proposes regional transportation systems management and operations (Regional TSM(&)O) solutions to combat this problem. Specifically, it was found...
Show moreWrong-way driving (WWD) has been problematic on United States highways for decades despite its rare occurrence. Since WWD crashes are rare, recent researchers have studied WWD non-crash events such as WWD 911 calls and WWD citations to understand the overall nature and trend of WWD. This paper demonstrates the regional nature of the WWD problem and proposes regional transportation systems management and operations (Regional TSM(&)O) solutions to combat this problem. Specifically, it was found that 11% of all WWD multi-data events (e.g., multiple 911 calls for the same WWD event) traveled from one county to another. Additionally, 30% of all WWD single-data and multi-data events occurred at or near interchanges between two limited access highways in counties with multiple operating agencies. This indicates that a significant proportion of WWD events could potentially travel from one limited access facility to another. Moreover, 28% of WWD events occurred on limited access facilities shared by multiple agencies. To emphasize the regional nature of WWD, this paper determined the vulnerable demographic groups in different regions of Florida by developing WWD crash and citation prediction models. The models' findings indicate that certain demographic groups (such as elderly or Hispanic) increase WWD risk. The models' results can be used to improve driver education and increase law enforcement presence in high risk WWD locations. Regional TSM(&)O solutions, such as coordination and communication among agencies and regional traffic management centers (RTMCs), law enforcement co-location with RTMCs, and strengthening statewide TSM(&)O programs to manage WWD events are also proposed.
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Date Issued: 2017
Identifier: CFE0006874, ucf:51736
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006874

Title: Development and Application of an Optimization Approach for Cost-Effective Deployment of Advanced Wrong-Way Driving Countermeasures.
Creator: Sandt, Adrian, Al-Deek, Haitham, Eluru, Naveen, Hasan, Samiul, Zheng, Qipeng, University of Central Florida
Abstract / Description: Wrong-way driving (WWD) is a dangerous behavior, especially on high-speed divided highways. The nature of WWD crashes makes it difficult for agencies to combat them effectively. Advanced WWD countermeasures equipped with flashing lights, detection devices, and cameras can significantly reduce WWD. However, these countermeasures' high costs mean that agencies often cannot deploy them at all exit ramps. To help agencies identify the most cost-effective deployment locations for advanced WWD...
Show moreWrong-way driving (WWD) is a dangerous behavior, especially on high-speed divided highways. The nature of WWD crashes makes it difficult for agencies to combat them effectively. Advanced WWD countermeasures equipped with flashing lights, detection devices, and cameras can significantly reduce WWD. However, these countermeasures' high costs mean that agencies often cannot deploy them at all exit ramps. To help agencies identify the most cost-effective deployment locations for advanced WWD countermeasures, an innovative WWD countermeasure optimization approach was developed. This approach consists of a WWD hotspots model and a WWD countermeasures optimization algorithm. The WWD hotspots model uses non-crash WWD events, interchange designs, and traffic volumes to predict the number of WWD crashes on multi-exit roadway segments and identify hotspot segments with high WWD crash risk (WWCR). Then, the optimization algorithm uses these WWCR values to identify the optimal exits for advanced WWD countermeasure deployment based on available resources and other applicable constraints. This approach was applied to the Central Florida Expressway Authority (CFX) and Florida's Turnpike Enterprise (FTE) toll road networks. In both applications, the optimization algorithm provided significant WWCR reduction while meeting investment and other constraints and better allocated the agencies' resources compared to only deploying advanced WWD countermeasures in WWD hotspots. The optimization algorithm was also used to identify mainline sections on the CFX network with high WWCR. Additionally, the optimization algorithm was used to evaluate existing Rectangular Flashing Beacon (RFB) and Light-Emitting Diode (LED) advanced WWD countermeasures on the CFX (RFBs) and FTE (RFBs and LEDs) networks. These evaluations showed that the crash reduction and injury reduction benefits of these advanced WWD countermeasures have exceeded their costs since these countermeasures have been deployed. By using this WWD countermeasures optimization approach, agencies throughout the United States could proactively and cost-effectively deploy advanced WWD countermeasures to reduce WWD.
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Date Issued: 2018
Identifier: CFE0007364, ucf:52093
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007364

Title: Modeling of Wrong Way Driving Entries and Developing Innovative Approaches for Evaluating the Effectiveness of Advanced Wrong Way Driving Countermeasures.
Creator: Kayes, Md Imrul, Al-Deek, Haitham, Eluru, Naveen, Hasan, Samiul, Uddin, Nizam, University of Central Florida
Abstract / Description: Wrong-way driving (WWD) is a hazardous behavior on interstates, toll roads, and other high-speed limited access facilities. Since WWD crashes are rare, recent researchers have studied WWD events such as WWD 911 calls and WWD citations to understand the overall nature and trend of WWD. It is very difficult to build credible statistical models based solely on crashes due to the small sample size since these are only 3% of all crashes. Modeling of WWD non-crash events can result in more accurate...
Show moreWrong-way driving (WWD) is a hazardous behavior on interstates, toll roads, and other high-speed limited access facilities. Since WWD crashes are rare, recent researchers have studied WWD events such as WWD 911 calls and WWD citations to understand the overall nature and trend of WWD. It is very difficult to build credible statistical models based solely on crashes due to the small sample size since these are only 3% of all crashes. Modeling of WWD non-crash events can result in more accurate models. A model was developed for Florida limited access facilities to identify roadway factors and traffic characteristics of exit ramp terminals that influence WWD entries. This model indicated that interchange type, intersection angle of exit ramp terminals, presence of tolling at the entrance ramp, presence of channelizing island between the exit ramp lanes, number of lanes on the exit ramp, area (rural or urban), and traffic volumes significantly affect the likelihood of WWD entries at exit ramps. Conventional (")Wrong Way(") signs can reduce WWD incidents but can be insufficient in some cases. In areas with many WWD crash and non-crash events, transportation agencies can be proactive by considering the use of countermeasures with advanced technologies to actively warn motorists of WWD violations. To help agencies select the most effective countermeasure, two innovative evaluation of performance approaches were developed so they can be used to evaluate and compare among different advanced WWD countermeasures. These approaches consist of before-after analysis of WWD non-crash events (WWD 911 calls and citations) and turn around rates of wrong way vehicles to self-correct their WWD acts. With this research, transportation agencies can better predict WWD entries at exit ramps; identify suitable locations for possible countermeasures deployment; and improve their current design, signing, and pavement marking practices while still following national and state standards.
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Date Issued: 2019
Identifier: CFE0007474, ucf:52672
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007474

Title: Multi-Objective Optimization for Construction Equipment Fleet Selection and Management In Highway Construction Projects Based on Time, Cost, and Quality Objectives.
Creator: Shehadeh, Ali, Tatari, Omer, Al-Deek, Haitham, Abou-Senna, Hatem, Flitsiyan, Elena, University of Central Florida
Abstract / Description: The sector of highway construction shares approximately 11% of the total construction industry in the US. Construction equipment can be considered as one of the primary reasons this industry has reached such a significant level, as it is considered an essential part of the highway construction process during highway project construction. This research addresses a multi-objective optimization mathematical model that quantifies and optimize the key parameters for excavator, truck, and motor...
Show moreThe sector of highway construction shares approximately 11% of the total construction industry in the US. Construction equipment can be considered as one of the primary reasons this industry has reached such a significant level, as it is considered an essential part of the highway construction process during highway project construction. This research addresses a multi-objective optimization mathematical model that quantifies and optimize the key parameters for excavator, truck, and motor-grader equipment to minimize time and cost objective functions. The model is also aimed to maintain the required level of quality for the targeted construction activity. The mathematical functions for the primary objectives were formulated and then a genetic algorithm-based multi-objective was performed to generate the time-cost Pareto trade-offs for all possible equipment combinations using MATLAB software to facilitate the implementation. The model's capabilities in generating optimal time and cost trade-offs based on optimized equipment number, capacity, and speed to adapt with the complex and dynamic nature of highway construction projects are demonstrated using a highway construction case study. The developed model is a decision support tool during the construction process to adapt with any necessary changes into time or cost requirements taking into consideration environmental, safety and quality aspects. The flexibility and comprehensiveness of the proposed model, along with its programmable nature, make it a powerful tool for managing construction equipment, which will help saving time and money within the optimal quality margins. Also, this environmentally friendly decision-support tool model provided optimal solutions that help to reduce the CO2 emissions reducing the ripple effects of targeted highway construction activities on the global warming phenomenon. The generated optimal solutions offered considerable time and cost savings.
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Date Issued: 2019
Identifier: CFE0007863, ucf:52800
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007863

Title: MULTI-OBJECTIVE OPTIMIZATION FOR HEAVY EARTHMOVING CONSTRUCTION EQUIPMENT MANAGEMENT BASED ON TIME, COST, AND POLLUTANT EMISSIONS.
Creator: Alshboul, Odey, Tatari, Omer, Al-Deek, Haitham, Abou-Senna, Hatem, Awad, Amro, University of Central Florida
Abstract / Description: Earthmoving activity is considered a significant activity in the construction project. The cost of earthmoving activity in the construction projects in some cases reaches about 30% of the overall cost of the project. Moreover, heavy equipment selection needs to be utilized in this activity, such as trucks and excavators. Such equipment emits a huge amount of carbon that has a negative effect on environmental dimensions. A mathematical model to optimize all design variables (i.e., capacity,...
Show moreEarthmoving activity is considered a significant activity in the construction project. The cost of earthmoving activity in the construction projects in some cases reaches about 30% of the overall cost of the project. Moreover, heavy equipment selection needs to be utilized in this activity, such as trucks and excavators. Such equipment emits a huge amount of carbon that has a negative effect on environmental dimensions. A mathematical model to optimize all design variables (i.e., capacity, number, and speed) related to this equipment is urgently required to prevent these negative impacts. The proposed model offers a genetic algorithm-based optimization technique for earthmoving activity. The model has four main phases: (1) define all related decision variables for earthmoving equipment, (2) detect all related constraints that impact the optimization model, (3) derive the mathematical optimization model, and (4) apply the multi-objective genetic algorithms. The optimization approach is utilized to minimize the cost and duration of the earthmoving activity, along with reducing the carbon emissions and fuel consumption. A case study is applied to test and validate the addressed model. Optimization outputs have proven the model efficiency in saving substantial cost and time compared to the actual results. The results of the case study show that the innovative and original contribution of the created mathematical optimization model. These unique and new competencies are anticipated to support contractors and construction management engineers to minimize time and cost associated with earthmoving activities.
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Date Issued: 2019
Identifier: CFE0007598, ucf:52518
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007598

Title: Efficient and Scalable Evaluation of Continuous, Spatio-temporal Queries in Mobile Computing Environments.
Creator: Cazalas, Jonathan, Guha, Ratan, Bassiouni, Mostafa, Orooji, Ali, Al-Deek, Haitham, University of Central Florida
Abstract / Description: A variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. For this research, we present a two-pronged approach at addressing this problem. Firstly, we introduce an efficient and scalable system for monitoring traditional, continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a...
Show moreA variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. For this research, we present a two-pronged approach at addressing this problem. Firstly, we introduce an efficient and scalable system for monitoring traditional, continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a naive CPU-based solution for continuous range-monitoring queries, and we then extend this system using the GPU. Additionally, with mobile communication devices becoming commodity, location-based services will become ubiquitous. To cope with the very high intensity of location-based queries, we propose a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view. Our studies show that by exploiting the parallel processing power of the GPU, we are able to significantly scale the number of mobile objects, while maintaining an acceptable level of performance.Our second approach was to view this research problem as one belonging to the domain of data streams. Several works have convincingly argued that the two research fields of spatio-temporal data streams and the management of moving objects can naturally come together. [IlMI10, ChFr03, MoXA04] For example, the output of a GPS receiver, monitoring the position of a mobile object, is viewed as a data stream of location updates. This data stream of location updates, along with those from the plausibly many other mobile objects, is received at a centralized server, which processes the streams upon arrival, effectively updating the answers to the currently active queries in real time.For this second approach, we present GEDS, a scalable, Graphics Processing Unit (GPU)-based framework for the evaluation of continuous spatio-temporal queries over spatio-temporal data streams. Specifically, GEDS employs the computation sharing and parallel processing paradigms to deliver scalability in the evaluation of continuous, spatio-temporal range queries and continuous, spatio-temporal kNN queries. The GEDS framework utilizes the parallel processing capability of the GPU, a stream processor by trade, to handle the computation required in this application. Experimental evaluation shows promising performance and shows the scalability and efficacy of GEDS in spatio-temporal data streaming environments. Additional performance studies demonstrate that, even in light of the costs associated with memory transfers, the parallel processing power provided by GEDS clearly counters and outweighs any associated costs.Finally, in an effort to move beyond the analysis of specific algorithms over the GEDS framework, we take a broader approach in our analysis of GPU computing. What algorithms are appropriate for the GPU? What types of applications can benefit from the parallel and stream processing power of the GPU? And can we identify a class of algorithms that are best suited for GPU computing? To answer these questions, we develop an abstract performance model, detailing the relationship between the CPU and the GPU. From this model, we are able to extrapolate a list of attributes common to successful GPU-based applications, thereby providing insight into which algorithms and applications are best suited for the GPU and also providing an estimated theoretical speedup for said GPU-based applications.
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Date Issued: 2012
Identifier: CFE0004222, ucf:49012
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004222

DMS (4)	+ -
ITS (3)	+ -
Wrong-Way Driving (3)	+ -
Delay (2)	+ -
Intelligent Transportation Systems (2)	+ -

Optimization (2)	+ -
Simulation (2)	+ -
Toll plaza (2)	+ -
Travel Time (2)	+ -
VISSIM (2)	+ -
ANOVA (1)	+ -
ARIMA (1)	+ -
ATIS (1)	+ -
Access Management (1)	+ -
Active Traffic Management (1)	+ -
Advanced Traveler Information Systems (1)	+ -
Air Quality Impacts (1)	+ -
Artificial Neural Networks (1)	+ -
Benefit-Cost Analysis (1)	+ -
Binary Logit Model (1)	+ -
Bus Rapid Transit (1)	+ -
CATI (1)	+ -
CBRAS (1)	+ -
CMS (1)	+ -
CO2 (1)	+ -
CUDA (1)	+ -
Carbon Dioxide (1)	+ -
Civil Engineering (1)	+ -
Construction impact (1)	+ -
Countermeasure (1)	+ -

University of Central Florida (30)	+ -
Al-Deek, Haitham (28)	+ -
Uddin, Nizam (8)	+ -
Tatari, Omer (7)	+ -
Eluru, Naveen (5)	+ -

Oloufa, Amr (5)	+ -
Abdel-Aty, Mohamed (4)	+ -
Hasan, Samiul (4)	+ -
Radwan, Ahmed (4)	+ -
Abou-Senna, Hatem (3)	+ -
Al-Deek, Haitham M. (2)	+ -
Lochrane, Taylor (2)	+ -
Rogers, John (2)	+ -
Tatari, Mehmet (2)	+ -
Ahmed, Mohamed (1)	+ -
Al-Sahili, Omar (1)	+ -
Alomari, Ahmad (1)	+ -
Alshboul, Odey (1)	+ -
Awad, Amro (1)	+ -
Bassiouni, Mostafa (1)	+ -
Behzadan, Amir (1)	+ -
Cazalas, Jonathan (1)	+ -
Chilakamarri Venkata, Srinivasa Ravi Chandra (1)	+ -
Consoli, Frank (1)	+ -
Cooper, Charles (1)	+ -
Emam, Emam (1)	+ -
Ercan, Tolga (1)	+ -
Fahmy, Tarek (1)	+ -
Faruk, Md. Omar (1)	+ -
Flick, Jason (1)	+ -

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