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- Title
- Understanding Crisis Communication and Mobility Resilience during Disasters from Social Media.
- Creator
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Roy, Kamol, Hasan, Samiul, Eluru, Naveen, Wu, Yina, University of Central Florida
- Abstract / Description
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Rapid communication during extreme events is one of the critical aspects of successful disaster management strategies. Due to their ubiquitous nature, social media platforms offer a unique opportunity for crisis communication. Moreover, social media usage on GPS enabled devices such as smartphones allow us to collect human movement data which can help understanding mobility during a disaster. This study leverages social media (Twitter) data to understand the effectiveness of social media...
Show moreRapid communication during extreme events is one of the critical aspects of successful disaster management strategies. Due to their ubiquitous nature, social media platforms offer a unique opportunity for crisis communication. Moreover, social media usage on GPS enabled devices such as smartphones allow us to collect human movement data which can help understanding mobility during a disaster. This study leverages social media (Twitter) data to understand the effectiveness of social media-based communication and the resilience of human mobility during a disaster. This thesis has two major contributions. First, about 52.5 million tweets related to hurricane Sandy are analyzed to assess the effectiveness of social media communication during disasters and identify the contributing factors leading to effective crisis communication strategies. Effectiveness of a social media user is defined as the ratio of attention gained over the number of tweets posted. A model is developed to explain more effective users based on several relevant features. Results indicate that during a disaster event, only few social media users become highly effective in gaining attention. In addition, effectiveness does not depend on the frequency of tweeting activity only; instead it depends on the number of followers and friends, user category, bot score (controlled by a human or a machine), and activity patterns (predictability of activity frequency). Second, to quantify the impacts of an extreme event to human movements, we introduce the concept of mobility resilience which is defined as the ability of a mobility infrastructure system to manage shocks and return to a steady state in response to an extreme event. We present a method to detect extreme events from geo-located movement data and to measure mobility resilience and loss of resilience due to those events. Applying this method, we measure resilience metrics from geo-located social media data for multiple types of disasters occurred all over the world. Quantifying mobility resilience may help us to assess the higher-order socio-economic impacts of extreme events and guide policies towards developing resilient infrastructures as well as a nation's overall disaster resilience.
Show less - Date Issued
- 2018
- Identifier
- CFE0007362, ucf:52090
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007362
- Title
- A Joint Econometric Approach for Modeling Crash Counts by Collision Type.
- Creator
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Bhowmik, Tanmoy, Eluru, Naveen, Abdel-Aty, Mohamed, Yasmin, Shamsunnahar, University of Central Florida
- Abstract / Description
-
In recent years, there is growing recognition that common unobserved factors that influence crash frequency by one attribute level are also likely to influence crash frequency by other attribute levels. The most common approach employed to address the potential unobserved heterogeneity in safety literature is the development of multivariate crash frequency models. The current study proposes an alternative joint econometric framework to accommodate for the presence of unobserved heterogeneity ...
Show moreIn recent years, there is growing recognition that common unobserved factors that influence crash frequency by one attribute level are also likely to influence crash frequency by other attribute levels. The most common approach employed to address the potential unobserved heterogeneity in safety literature is the development of multivariate crash frequency models. The current study proposes an alternative joint econometric framework to accommodate for the presence of unobserved heterogeneity (-) referred to as joint negative binomial-multinomial logit fractional split (NB-MNLFS) model. Furthermore, the study undertakes a first of its kind comparison exercise between the most commonly used multivariate model (multivariate random parameter negative binomial model) and the proposed joint approach by generating an equivalent log-likelihood measure. The empirical analysis is based on the zonal level crash count data for different collision types from the state of Florida for the year 2015. The model results highlight the presence of common unobserved effects affecting the two components of the joint model as well as the presence of parameter heterogeneity. The equivalent log-likelihood and goodness of fit measures clearly highlight the superiority of the proposed joint model over the commonly used multivariate approach.
Show less - Date Issued
- 2018
- Identifier
- CFE0007392, ucf:52740
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007392
- Title
- Accommodating Exogenous Variable and Decision Rule Heterogeneity in Discrete Choice Models: Application to Bicyclist Route Choice.
- Creator
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Dey, Bibhas, Eluru, Naveen, Abdel-Aty, Mohamed, Anowar, Sabreena, University of Central Florida
- Abstract / Description
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The thesis contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, we evaluate latent segmentation based mixed models that allow for segmenting population based on decision rules while also incorporating unobserved heterogeneity within the segment level decision rule models. In our analysis, we choose to consider the random utility framework along with random regret minimization approach....
Show moreThe thesis contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, we evaluate latent segmentation based mixed models that allow for segmenting population based on decision rules while also incorporating unobserved heterogeneity within the segment level decision rule models. In our analysis, we choose to consider the random utility framework along with random regret minimization approach. Further, instead of assuming the number of segments (as 2), we conduct an exhaustive exploration with multiple segments across the two decision rules. Within each segment we also allow for unobserved heterogeneity. The model estimation is conducted using a stated preference data from 695 commuter cyclists compiled through a web-based survey. The probabilistic allocation of respondents to different segments indicates that female commuter cyclists are more utility oriented, however the majority of the commuter cyclist's choice pattern is consistent with regret minimization mechanism. Overall, cyclists' route choice decisions are influenced by roadway attributes, cycling infrastructure availability, pollution exposure, and travel time. The analysis approach also allows us to investigate time based trade-offs across cyclists of different classes. Interestingly, we observed that the trade-off values in regret and utility based segments for roadway attributes are similar in magnitude; but the values differ greatly for cycling infrastructure and exposure attributes, particularly for maximum exposure levels.
Show less - Date Issued
- 2018
- Identifier
- CFE0007398, ucf:52059
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007398
- Title
- Analyzing Destination Choices of Tourists and Residents from Location Based Social Media Data.
- Creator
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Hasnat, Md Mehedi, Hasan, Samiul, Abdel-Aty, Mohamed, Eluru, Naveen, University of Central Florida
- Abstract / Description
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Ubiquitous uses of social media platforms in smartphones have created an opportunity to gather digital traces of individual activities at a large scale. Traditional travel surveys fall short in collecting longitudinal travel behavior data for a large number of people in a cost effective way, especially for the transient population such as tourists. This study presents an innovating methodological framework, using machine learning and econometric approaches, to gather and analyze location...
Show moreUbiquitous uses of social media platforms in smartphones have created an opportunity to gather digital traces of individual activities at a large scale. Traditional travel surveys fall short in collecting longitudinal travel behavior data for a large number of people in a cost effective way, especially for the transient population such as tourists. This study presents an innovating methodological framework, using machine learning and econometric approaches, to gather and analyze location-based social media (LBSM) data to understand individual destination choices. First, using Twitter's search interface, we have collected Twitter posts of nearly 156,000 users for the state of Florida. We have adopted several filtering techniques to create a reliable sample from noisy Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The performance of the proposed classifier has been validated using manually labeled data and compared against the state-of-the-art classification methods. Second, using different clustering methods, we have analyzed the spatial distributions of destination choices of tourists and residents. The clusters from tourist destinations revealed most popular tourist spots including emerging tourist attractions in Florida. Third, to predict a tourist's next destination type, we have estimated a Conditional Random Field (CRF) model with reasonable accuracy. Fourth, to analyze resident destination choice behavior, this study proposes an extensive data merging operation among the collected Twitter data and different geographic database from state level data libraries. We have estimated a Panel Latent Segmentation Multinomial Logit (PLSMNL) model to find the characteristics affecting individual destination choices. The proposed PLSMNL model is found to better explain the effects of variables on destination choices compared to trip-specific Multinomial Logit Models. The findings of this study show the potential of LBSM data in future transportation and planning studies where collecting individual activity data is expensive.
Show less - Date Issued
- 2018
- Identifier
- CFE0007012, ucf:52028
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007012
- Title
- Explore Contributing Geometric Factors and Built-Environment on Bicycle Activity and Safety at Intersections.
- Creator
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Castro, Scott, Abdel-Aty, Mohamed, Cai, Qing, Eluru, Naveen, University of Central Florida
- Abstract / Description
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This study attempts to explore all factors associated with bicycle motor-vehicle crashes at intersections in order to improve bicycle safety and bicycle activity. Factors such as exposure (bicycle and vehicle volumes), existing facilities (bike lanes, sidewalks, shared-use paths), geometric design (# of lanes, speed limit, medians, legs, roadway conditions), and land-use were collected and evaluated using Poisson, Zero-Inflated Poisson, and Negative Binomial models in SAS 9.4 software....
Show moreThis study attempts to explore all factors associated with bicycle motor-vehicle crashes at intersections in order to improve bicycle safety and bicycle activity. Factors such as exposure (bicycle and vehicle volumes), existing facilities (bike lanes, sidewalks, shared-use paths), geometric design (# of lanes, speed limit, medians, legs, roadway conditions), and land-use were collected and evaluated using Poisson, Zero-Inflated Poisson, and Negative Binomial models in SAS 9.4 software. Increasing the bicycle travel mode can have positive lasting effects on personal health, the environment, and improve traffic conditions. Deterrents that keep users from riding bicycles more are the lack of facilities and most importantly, safety concerns. Florida has consistently been a national leader in bicyclist deaths, which made this area a great candidate to study. Vehicle and bicycle volumes for 159 intersections in Orlando, Florida were collected and compared with crash data that was obtained. All existing facilities, geometric design properties, and land-uses for each intersection were collected for analysis. The results confirmed that an increase of motor-vehicles and bicyclists would increase the risk of a crash at an intersection. The presence of a keyhole lane (bike lane in-between a through and exclusive right turn lane), was shown to be statistically significant, and although it still had a positive correlation with injury risk, it had a much lower risk of crashes than a typical bike lane at intersections. The presence of a far shared path (more than 4 feet from the edge of curb) was shown to be statistically significant in decreasing the risk of crashes between bicycles and motor-vehicles at intersections. Institutional, agricultural, residential, government, and school land uses had positive correlations and were statistically significant with increasing activity of bicyclists at intersections. This study is unique because it uses actual bicycle volume as an exposure to determine the effects of bicycle safety and activity at intersections and not many others have done this. It is important for transportation planners and designers to use this information to design better complete streets in the future.
Show less - Date Issued
- 2018
- Identifier
- CFE0007318, ucf:52134
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007318
- Title
- A System Dynamics Approach on Sustainability Assessment of the United States Urban Commuter Transportation.
- Creator
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Ercan, Tolga, Tatari, Omer, Oloufa, Amr, Eluru, Naveen, Xanthopoulos, Petros, University of Central Florida
- Abstract / Description
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Transportation sector is one of the largest emission sources and is a cause for human health concern due to the high dependency on personal vehicle in the U.S. Transportation mode choice studies are currently limited to micro- and regional-level boundaries, lacking of presenting a complete picture of the issues, and the root causes associated with urban passenger transportation choices in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships...
Show moreTransportation sector is one of the largest emission sources and is a cause for human health concern due to the high dependency on personal vehicle in the U.S. Transportation mode choice studies are currently limited to micro- and regional-level boundaries, lacking of presenting a complete picture of the issues, and the root causes associated with urban passenger transportation choices in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships among the critical system parameters affecting alternative transportation mode choices in the U.S. as well as to identify possible policy areas to improve alternative transportation mode choice rates for future years up to 2050. Considering the high degree of uncertainties inherent to the problem, multivariate sensitivity analysis is utilized to explore the effectiveness of existing and possible policy implications in dynamic model in the terms of their potential to increase transit ridership and locating critical parameters that influences the most on mode choice and emission rates. Finally, the dissertation advances the current body of knowledge by integrating discrete event simulation (multinomial fractional split model) and system dynamics for hybrid urban commuter transportation simulation to test new scenarios such as autonomous vehicle (AV) adoption along with traditional policy scenarios such as limiting lane-mile increase on roadways and introducing carbon tax policy on vehicle owners. Overall, the developed simulation models clearly indicate the importance of urban structures to secure the future of alternative transportation modes in the U.S. as the prevailing policy practices fail to change system behavior. Thus, transportation system needs a paradigm shift to radically change current impacts and the market penetration of AVs can be one of the reforms to provoke this transition since it is expected to revolutionize mode choice, emission trends, and the built environment.
Show less - Date Issued
- 2019
- Identifier
- CFE0007626, ucf:52554
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007626
- Title
- Impact of Dynamic Message Signs on Driver Behavior Under Reduced Visibility Conditions.
- Creator
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Selby, Ryan, Abdel-Aty, Mohamed, Eluru, Naveen, Lee, JaeYoung, University of Central Florida
- Abstract / Description
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Fog along roadways is a dangerous hazard that leads to crashes resulting from limited visibility. Low visibility gives drivers less time to react to potential obstacles that can suddenly appear and require immediate action. To solve this issue, early warning systems involving Dynamic Message Signs or other types of devices are used to alert drivers of the impending visibility condition so that they are prepared. This research focuses on testing the effectiveness of one form of warning systems...
Show moreFog along roadways is a dangerous hazard that leads to crashes resulting from limited visibility. Low visibility gives drivers less time to react to potential obstacles that can suddenly appear and require immediate action. To solve this issue, early warning systems involving Dynamic Message Signs or other types of devices are used to alert drivers of the impending visibility condition so that they are prepared. This research focuses on testing the effectiveness of one form of warning systems to investigate how it impacts driver behavior in foggy conditions. To accomplish this objective, a simulation study is developed to test variables of interest including: Roadway Type, Fog Level, DMS Presence, Beacon Presence, Traffic Volume, and DMS Message Provided. Using a factorial design, 24 scenarios are created by randomizing the variables listed using statistical software to be tested on 72 volunteer participants. Using a NADS MiniSim Driving Simulator, the participants driving behavior is recorded including speed and breaking behavior under an initial clear condition followed by a reduced visibility fog condition. From demographics, drivers age 35 and over consistently showed a higher likelihood of speed reduction between clear and fog conditions with overall reduction increasing with age. This is seen when looking at the mean change in speed based on driver age where young drivers (18-25 yrs) reduced speeds by 7MPH, older drivers (35-45 yrs) reduced by 12MPH, and elder drivers (65+ yrs) reduced by 17MPH. The more often a person drove and those that were educated at a graduate level also showed a higher chance of speed reductions. This demonstrates the impact of experience and exposure to driving performance under reduced visibility conditions. Those who recently drove under fog conditions or learned to drive in Florida were found to be less likely to reduce their speeds when entering the fog. This is attributed to these drivers being confident or familiar with the environment resulting in risky driving behavior. For the scenario variables, it is determined that the type of roadway a driver travels plays a major role in how much speed reduction occurs and thus how much a driver decelerates when entering a low visibility environment. On average, drivers traversed the fog zone at 50MPH with the lowest travel speed being 30MPH. Since the speed limit on the freeway is 5MPH higher than the arterial, drivers' traveling along this road are noted to decelerate at higher rates to achieve this target speed. Additionally, DMS presence and message also provided an impact on the drivers' choice to decelerate and reduce travel speed within the fog condition. Under the most severe conditions, the probability of a driver reducing speed increases as the number of DMS present increases. Additionally, when a DMS presents a warning and specifies the action that a driver should take, in this case 'reduce speed,' greater speed reductions and decelerations are observed and are more likely to occur. Interestingly the number of DMS did not have a significant impact on driver behavior under every fog condition like the message presented did except in the most severe fog condition. Taking into account that 33% of drivers did not accurately remember the number of DMS encountered it can be concluded that the warning message itself is the most important aspect of the early warning system. This indicates that drivers accurately remember being directed to reduce speed whether they are given the advisement once or multiple times based on the number of DMS present. Further research into how the warning message is presented or worded could provide additional insight into the impact it can have on driver behavior. Since it is observed that drivers acknowledge the 'reduce speed' advisement, it is likely that specifying a specific speed limit could also warrant driver obedience. Additional testing and observation of driver reaction to larger traffic volumes and situations within the fog would also allow for further analysis of driver behavior under reduced visibility and the impact the early warning system has on their behavior.
Show less - Date Issued
- 2016
- Identifier
- CFE0006179, ucf:51116
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006179
- Title
- Joint modeling of traffic related crashes: a Copula based approch.
- Creator
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Nashad, Tammam, Eluru, Naveen, Abdel-Aty, Mohamed, Radwan, Essam, University of Central Florida
- Abstract / Description
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The study contributes to safety literature on transportation safety by employing copula based models for count frequency analysis at a macro-level. Most studies in the transportation safety area identify a single count variable (such as vehicular, pedestrian or bicycle crash counts) for a spatial unit and study the impact of exogenous variables. While the traditional count models perform adequately in the presence of a single count variable, it is necessary to modify these approaches to...
Show moreThe study contributes to safety literature on transportation safety by employing copula based models for count frequency analysis at a macro-level. Most studies in the transportation safety area identify a single count variable (such as vehicular, pedestrian or bicycle crash counts) for a spatial unit and study the impact of exogenous variables. While the traditional count models perform adequately in the presence of a single count variable, it is necessary to modify these approaches to examine multiple dependent variables for each study unit. To that extent, the current research effort contributes to literature by developing two multivariate models based on copula methodology. First, a copula based bivariate negative binomial model for pedestrian and bicyclist crash frequency analysis is developed. Second, a multivariate negative binomial model for crashes involving non-motorized road users, passenger cars, vans, light trucks and heavy trucks is proposed. The proposed approaches also accommodate for potential heterogeneity (across zones) in the dependency structure. The formulated models are estimated using traffic crash count data at the Statewide Traffic Analysis Zone (STAZ) level for the state of Florida for the years 2010 through 2012. The STAZ level variables considered in our analysis include exposure measures, socio-economic characteristics, road network characteristics and land use attributes. A policy analysis is also conducted along with a representation of hotspot identification to illustrate the applicability of the proposed model for planning purposes. The development of such spatial profiles will allow planners to identify high risk zones for screening and treatment purposes.
Show less - Date Issued
- 2016
- Identifier
- CFE0006153, ucf:51124
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006153
- 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
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Muhaisen, Nabil, Al-Deek, Haitham, Eluru, Naveen, Tatari, Omer, University of Central Florida
- Abstract / Description
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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.
Show less - Date Issued
- 2015
- Identifier
- CFE0006045, ucf:50983
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006045
- Title
- Evaluation of Real World Toll Plazas Using Driving Simulation.
- Creator
-
Carroll, Kali, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
- Abstract / Description
-
Toll plazas are becoming an essential part of the highway system, especially within the state of Florida. Many crashes reported on highways occur at toll plazas. A primary reason for many vehicle collisions happening at these facilities is the fact that each toll plaza agency has different design, signage and marking criteria. This, in turn, causes driver confusion and possible last minute weaving maneuvers. Even though the varying design of toll plazas is a clear highway safety factor,...
Show moreToll plazas are becoming an essential part of the highway system, especially within the state of Florida. Many crashes reported on highways occur at toll plazas. A primary reason for many vehicle collisions happening at these facilities is the fact that each toll plaza agency has different design, signage and marking criteria. This, in turn, causes driver confusion and possible last minute weaving maneuvers. Even though the varying design of toll plazas is a clear highway safety factor, research in the field is very limited but expanding. This study focuses on one toll plaza, in particular the Dean Mainline Toll Plaza, located in Orlando, Florida. The toll plaza is located directly between two roads that are in close proximity of each other. Because of this, the toll plaza is very close to the on- and off- ramps, which can be even more confusing and stressful for a driver entering or leaving the highway. The purpose of this study is to evaluate the safety and efficiency of the Dean Mainline Toll Plaza in order to make recommendations to improve or maintain the current toll plaza design, as well as potentially contribute to a nationally set design standard for toll plazas. Using the NADS miniSimTM Simulator, 72 subjects were recruited, and each subject was asked to drive 3 scenarios that were randomly selected from a pool of 24 scenarios. The following factors were changed in order to study the driver's behavior: signage and their location, pavement markings, distances between the toll plaza and ramps, and traffic conditions. All of these factors were altered and observed on five of the eight possible routes than can be taken through the toll plaza. The subjects were asked to complete questionnaires before and after all of the scenarios, as well as in between each driving scenario. These questionnaires included demographic characteristics, such as age, education, income, E-PASS ownership, etc. The data that were collected by the driving simulator and questionnaires were analyzed by ANOVA and multinomial logistic regression models. A positive relationship was found between non-urgent lane changing and the current real-world sign conditions prior to the toll plaza. Relationships were also found between the subjects' speed in various locations and signage before the toll plaza and segment length after the toll plaza. Along with specified recommendations for future research in toll plaza safety, recommendations for the Dean Mainline Toll Plaza include maintaining the current signs and pavement markings, as they were found to be beneficial in drivers performing safe lane changing maneuvers.
Show less - Date Issued
- 2016
- Identifier
- CFE0006085, ucf:50960
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006085
- Title
- Impact of the longer change and clearance intervals on signalized intersections and corridors.
- Creator
-
Alfawzan, Mohammed, Radwan, Essam, Eluru, Naveen, Abou-Senna, Hatem, University of Central Florida
- Abstract / Description
-
Evaluating the impact of longer change and clearance intervals on signalized intersections and corridors is the main goal of this study. In fact, the Florida department of Transportation (FDOT) has adopted a new signal retiming effort in a number of signalized intersections along several corridors. The Orange County started implementing the new signal timing from December, 2013 and completed it in June, 2015. The other objective of this new signal timing is to minimize the red light running...
Show moreEvaluating the impact of longer change and clearance intervals on signalized intersections and corridors is the main goal of this study. In fact, the Florida department of Transportation (FDOT) has adopted a new signal retiming effort in a number of signalized intersections along several corridors. The Orange County started implementing the new signal timing from December, 2013 and completed it in June, 2015. The other objective of this new signal timing is to minimize the red light running rate. This study is dedicated to investigate the signal retiming effort adopted by the FDOT and how the new signal timing might impact the studied signalized intersections' performance and safety. To address this issue, a number of signalized intersections along three corridors in Orange County were investigated during different three time of the day periods AM, MD, and PM. Additionally, three categories of signal timings were adopted to better understand the performance and safety of old (pattern 1), current (pattern 2), and proposed (pattern 3) signal timings. The analysis was based on the Simtraffic simulation which is a part of Synchro 8 software. The research results provide that the signalized intersection's performance along the three corridors during the three plans of the day were found significantly affected by lengthening the change and clearance intervals. Signal timing 2 and 3 were observed significantly different than signal timing 1 which have greater intersection delay, queue length, intersection overall volume to capacity v/c ratio, and Intersection capacity utilization ICU. Furthermore, the results show that the signal timing 2 and signal timing 3 significantly increase the total delay and travel time along the studied arterials during the three plans of the day.
Show less - Date Issued
- 2016
- Identifier
- CFE0006064, ucf:50970
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006064
- Title
- Estimating a Freight Mode Choice Model: A Case Study of Commodity Flow Survey 2012.
- Creator
-
Keya, Nowreen, Eluru, Naveen, Abdel-Aty, Mohamed, Radwan, Essam, University of Central Florida
- Abstract / Description
-
This research effort develops a national freight mode choice model employing data from the 2012 Commodity Flow Survey (CFS). While several research efforts have developed mode choice model with multiple modes in the passenger travel context, the literature is sparse in the freight context. The primary reasons being unavailability and/or the high cost associated with the acquisition of mode choice and level of service (LOS) measures (-) such as travel time and travel cost. The first...
Show moreThis research effort develops a national freight mode choice model employing data from the 2012 Commodity Flow Survey (CFS). While several research efforts have developed mode choice model with multiple modes in the passenger travel context, the literature is sparse in the freight context. The primary reasons being unavailability and/or the high cost associated with the acquisition of mode choice and level of service (LOS) measures (-) such as travel time and travel cost. The first contribution of the research effort is to develop travel time and cost measures for various modes reported in the CFS. The study considers five modes: hire truck, private truck, air, parcel service and other modes (rail, ship, pipeline, and other miscellaneous single and multiple modes). The LOS estimation is undertaken for a sample of CFS 2012 data that is partitioned into estimation sample and holdout sample. Subsequently, a mixed multinomial logit model is developed using the estimation sample. The exogenous variables considered in the model include LOS measures, freight characteristics, and transportation network and Origin-Destination variables. The model also accounts for unobserved factors that influence the mode choice process. The estimated mode choice model is validated using the holdout sample. Finally, a policy sensitivity analysis is conducted to illustrate the applicability of the proposed model.
Show less - Date Issued
- 2016
- Identifier
- CFE0006835, ucf:51766
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006835
- Title
- Improving Safety under Reduced Visibility Based on Multiple Countermeasures and Approaches including Connected Vehicles.
- Creator
-
Wu, Yina, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
- Abstract / Description
-
The effect of low visibility on both crash occurrence and severity is a major concern in the traffic safety field. Different approaches were utilized in this research to analyze the effects of fog on traffic safety and evaluate the effectiveness of different fog countermeasures. First, a (")Crash Risk Increase Indicator (CRII)(") was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash...
Show moreThe effect of low visibility on both crash occurrence and severity is a major concern in the traffic safety field. Different approaches were utilized in this research to analyze the effects of fog on traffic safety and evaluate the effectiveness of different fog countermeasures. First, a (")Crash Risk Increase Indicator (CRII)(") was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash risk with traffic flow characteristics. Second, a new algorithm was proposed to evaluate the rear-end crash risk under fog conditions. Logistic and negative binomial models were estimated in order to explore the relationship between the potential of rear-end crashes and the reduced visibility together with other traffic parameters. Moreover, the effectiveness of real-time fog warning systems was assessed by quantifying and characterizing drivers' speed adjustments through driving simulator experiments. A hierarchical assessment concept was suggested to explore the drivers' speed adjustment maneuvers. Two linear regression models and one hurdle beta regression model were estimated for the indexes. Also, another driving simulator experiment was conducted to explore the effectiveness of Connected-Vehicles (CV) crash warning systems on the drivers' awareness of the imminent situation ahead to take timely crash avoidance action(s). Finally, a micro-simulation experiment was also conducted to evaluate the safety benefits of a proposed Variable Speed limit (VSL) strategy and CV technologies. The proposed VSL strategy and CV technologies were implemented and tested for a freeway section through the micro-simulation software VISSIM. The results of the above mentioned studies showed the impact of reduced visibility on traffic safety, and the effectiveness of different fog countermeasures.
Show less - Date Issued
- 2017
- Identifier
- CFE0006928, ucf:51704
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006928
- Title
- Analysis of Driving Behavior at Expressway Toll Plazas using Driving Simulator.
- Creator
-
Saad, Moatz, Abdel-Aty, Mohamed, Eluru, Naveen, Lee, JaeYoung, University of Central Florida
- Abstract / Description
-
The objective of this study is to analyze the driving behavior at toll plazas by examining multiple scenarios using a driving simulator to study the effect of different options including different path decisions, various signs, arrow markings, traffic conditions, and extending auxiliary lanes before and after the toll plaza on the driving behavior. Also, this study focuses on investigating the effect of drivers' characteristics on the dangerous driving behavior (e.g. speed variation, sudden...
Show moreThe objective of this study is to analyze the driving behavior at toll plazas by examining multiple scenarios using a driving simulator to study the effect of different options including different path decisions, various signs, arrow markings, traffic conditions, and extending auxiliary lanes before and after the toll plaza on the driving behavior. Also, this study focuses on investigating the effect of drivers' characteristics on the dangerous driving behavior (e.g. speed variation, sudden lane change, drivers' confusion). Safety and efficiency are the fundamental goals that transportation engineering is always seeking for the design of highways. Transportation agencies have a crucial challenging task to accomplish traffic safety, particularly at the locations that have been identified as crash hotspots. In fact, toll plaza locations are one of the most critical and challenging areas that expressway agencies have to pay attention to because of the increasing traffic crashes over the past years near toll plazas.Drivers are required to make many decisions at expressway toll plazas which result in drivers' confusion, speed variation, and abrupt lane change maneuvers. These crucial decisions are mainly influenced by three reasons. First, the limited distance between toll plazas and the merging areas at the on-ramps before the toll plazas. In additional to the limited distance between toll plazas and the diverging areas after the toll plazas at the off-ramps. Second, it is also affected by the location and the configuration of signage and pavement markings. Third, drivers' decisions are affected by the different lane configurations and tolling systems that can cause drivers' confusion and stress. Nevertheless, limited studies have explored the factors that influence driving behavior and safety at toll plazas. There are three main systems of the toll plaza, the traditional mainline toll plaza (TMTP), the hybrid mainline toll plaza (HMTP), and the all-electronic toll collection (AETC). Recently, in order to improve the safety and the efficiency of the toll plazas, most of the traditional mainline toll plazas have been converted to the hybrid toll plazas or the all-electronic toll collection plazas. This study assessed driving behavior at a section, including a toll plaza on one of the main expressways in Central Florida. The toll plaza is located between a close on-ramp and a nearby off-ramp. Thus, these close distances have a significant effect on increasing driver's confusion and unexpected lane change before and after the toll plaza. Driving simulator experiments were used to study the driving behavior at, before and after the toll plaza. The details of the section and the plaza were accurately replicated in the simulator. In the driving simulator experiment, Seventy-two drivers with different age groups were participated. Subsequently, each driver performed three separate scenarios out of a total of twenty-four scenarios. Seven risk indicators were extracted from the driving simulator experiment data by using MATLAB software. These variables are average speed, standard deviation of speed, standard deviation of lane deviation, acceleration rate, standard deviation of acceleration (acceleration noise), deceleration rate, and standard deviation of deceleration (braking action variation). Moreover, various scenario variables were tested in the driving simulator including different paths, signage, pavement markings, traffic condition, and extending auxiliary lanes before and after the toll plaza. Divers' individual characteristics were collected from a questionnaire before the experiment. Also, drivers were filling a questionnaire after each scenario to check for simulator sickness or discomfort. Nine variables were extracted from the simulation questionnaire for representing individual characteristics including, age, gender, education level, annual income, crash experience, professional drivers, ETC-tag use, driving frequency, and novice international drivers. A series of mixed linear models with random effects to account for multiple observations from the same participant were developed to reveal the contributing factors that affect driving behavior at toll plazas. The results uncovered that all drivers who drove through the open road tolling (ORT) showed higher speed and lower speed variation, lane deviation, and acceleration noise than other drivers who navigate through the tollbooth. Also, the results revealed that providing adequate signage, and pavement markings are effective in reducing risky driving behavior at toll plazas. Drivers tend to drive with less lane deviation and acceleration noise before the toll plaza when installing arrow pavement markings. Adding dynamic message sign (DMS) at the on-ramp has a significant effect on reducing speed variation before the toll plaza. Likewise, removing the third overhead sign before the toll plaza has a considerable influence on reducing aggressive driving behavior before and after the toll plaza. This result may reflect drivers' desire to feel less confusion by excessive signs and markings. Third, extending auxiliary lanes with 660 feet (0.125 miles) before or after the toll plaza have an effect on increasing the average speed and reducing the lane deviation and the speed variation at and before the toll plaza. It also has an impact on increasing the acceleration noise and the braking action variation after the toll plaza. Finally, it was found that in congested conditions, participants drive with a lower speed variation and lane deviation before the toll plaza but with a higher acceleration noise after the toll plaza. On the other hand, understanding drivers' characteristics is particularly important for exploring their effect on risky driving behavior. Young drivers (18-25) and old drivers (older than 50 years) consistently showed a higher risk behavior than middle age drivers (35 to 50). Also, it was found that male drivers are riskier than female drivers at toll plazas. Drivers with high education level, drivers with high income, ETC-tag users, and drivers whose driving frequency is less than three trips per day are more cautious and tend to drive at a lower speed.
Show less - Date Issued
- 2016
- Identifier
- CFE0006492, ucf:51391
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006492
- Title
- The effectiveness of Child Restraint and Bicycle Helmet Policies to Improve Road Safety.
- Creator
-
Bustamante, Claudia, Abdel-Aty, Mohamed, Eluru, Naveen, Lee, JaeYoung, University of Central Florida
- Abstract / Description
-
Analyzing the effect of legislation in children's safety when they travel as motor-vehicle passengers and bicycle riders can allow us to evaluate the effectiveness in transportation policies. The Child Restraint Laws (CRL) and Bicycle Helmet Laws (BHL) were studied by analyzing the nationwide Fatality Analysis Reporting System (FARS) to estimate the fatality reduction as well as drivers' decisions to use Child Restraint Systems (CRS) and bicycle helmets respectively. Differences in...
Show moreAnalyzing the effect of legislation in children's safety when they travel as motor-vehicle passengers and bicycle riders can allow us to evaluate the effectiveness in transportation policies. The Child Restraint Laws (CRL) and Bicycle Helmet Laws (BHL) were studied by analyzing the nationwide Fatality Analysis Reporting System (FARS) to estimate the fatality reduction as well as drivers' decisions to use Child Restraint Systems (CRS) and bicycle helmets respectively. Differences in legislation could have different effects on traffic fatalities. Therefore, this study presents multiple methodologies to study these effects. In the evaluation of traffic safety issues, several proven statistical models have shown to be effective at estimating risky factors that might influence crash prevention. These proven models and predictive data analysis guided the process to attempt different models, leading to the development of three specific models used in this study to best estimate the effectiveness of these laws. Then, it was found that legislation in Child Safety Policy has consequences in traffic fatalities. A negative binomial model was created to analyze the CRL influence at the state-level in fatal crashes involving children, and showed that legislating on CRS can reduce the number of fatalities by 29% for children aged 5 to 9. Additionally, at the drivers-level a logistic regression model with random effects was used to determine the significant variables that influence the driver's decision to restrain his/her child. Such variables include: driver's restraint use, road classification, weather condition, number of occupants in the vehicle, traffic violations and driver's and child's age. It was also shown that drivers from communities with deprived socio-economic status are less likely to use CRS. In the same way, a binary logistic regression model was developed to evaluate the effect of BHL in bicycle helmet-use. Findings from this model show that bicyclists from states with the BHL are 236 times more likely to wear a helmet compared to those from states without the BHL. Moreover, the bicyclist's age, gender, education, and income level also influences bicycle helmet use. Both studies suggest that enacting CRL and BHL at the state-level for the studied age groups can be combined with education, safety promotion, enforcement, and program evaluation as proven countermeasures to increase children's traffic safety. This study evidenced that there is a lack of research in this field, especially when policy making requires having enough evidence to support the laws in order to not become an arbitrary legislation procedure affecting child's protection in the transportation system.
Show less - Date Issued
- 2017
- Identifier
- CFE0006571, ucf:51315
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006571
- Title
- A comparative analysis of different Dilemma Zone countermeasures at signalized intersections based on Cellular Automaton Model.
- Creator
-
Wu, Yina, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
- Abstract / Description
-
In the United States, intersections are among the most frequent locations for crashes. One of the major problems at signalized intersection is the dilemma zone, which is caused by false driver behavior during the yellow interval. This research evaluated driver behavior during the yellow interval at signalized intersections and compared different dilemma zone countermeasures. The study was conducted through four stages.First, the driver behavior during the yellow interval were collected and...
Show moreIn the United States, intersections are among the most frequent locations for crashes. One of the major problems at signalized intersection is the dilemma zone, which is caused by false driver behavior during the yellow interval. This research evaluated driver behavior during the yellow interval at signalized intersections and compared different dilemma zone countermeasures. The study was conducted through four stages.First, the driver behavior during the yellow interval were collected and analyzed. Eight variables, which are related to risky situations, are considered. The impact factors of drivers' stop/go decisions and the presence of the red-light running (RLR) violations were also analyzed. Second, based on the field data, a logistic model, which is a function of speed, distance to the stop line and the lead/follow position of the vehicle, was developed to predict drivers' stop/go decisions. Meanwhile, Cellular Automata (CA) models for the movement at the signalized intersection were developed. In this study, four different simulation scenarios were established, including the typical intersection signal, signal with flashing green phases, the intersection with pavement marking upstream of the approach, and the intersection with a new countermeasure: adding an auxiliary flashing indication next to the pavement marking. When vehicles are approaching the intersection with a speed lower than the speed limit of the intersection approach, the auxiliary flashing yellow indication will begin flashing before the yellow phase. If the vehicle that has not passed the pavement marking before the onset of the auxiliary flashing yellow indication and can see the flashing indication, the driver should choose to stop during the yellow interval. Otherwise, the driver should choose to go at the yellow duration. The CA model was employed to simulate the traffic flow, and the logistic model was applied as the stop/go decision rule. Dilemma situations that lead to rear-end crash risks and potential RLR risks were used to evaluate the different scenarios. According to the simulation results, the mean and standard deviation of the speed of the traffic flow play a significant role in rear-end crash risk situations, where a lower speed and standard deviation could lead to less rear-end risk situations at the same intersection. High difference in speed are more prone to cause rear-end crashes. With Respect to the RLR violations, the RLR risk analysis showed that the mean speed of the leading vehicle has important influence on the RLR risk in the typical intersection simulation scenarios as well as intersections with the flashing green phases' simulation scenario.Moreover, the findings indicated that the flashing green could not effectively reduce the risk probabilities. The pavement marking countermeasure had positive effects on reducing the risk probabilities if a platoon's mean speed was not under the speed used for designing the pavement marking. Otherwise, the risk probabilities for the intersection would not be reduced because of the increase in the RLR rate. The simulation results showed that the scenario with the pavement marking and an auxiliary indication countermeasure, which adds a flashing indication next to the pavement marking, had less risky situations than the other scenarios with the same speed distribution. These findings suggested the effectiveness of the pavement marking and an auxiliary indication countermeasure to reduce both rear-end collisions and RLR violations than other countermeasures.
Show less - Date Issued
- 2014
- Identifier
- CFE0005562, ucf:50291
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005562
- 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.
Show less - 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.
Show less - Date Issued
- 2019
- Identifier
- CFE0007474, ucf:52672
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007474
- Title
- Investigating and Facilitating the Transferability of Safety Performance Functions.
- Creator
-
Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
- Abstract / Description
-
Safety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public...
Show moreSafety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public or private, may opt to not invest their resources in data collection and processing to develop own localized SPFs. Instead, the agencies may adopt the HSM's. However, the HSM's SPFs may not necessarily be applicable to any conditions. Hence, this research is focused on SPF transferability, specifically for rural divided multilane highway segments. Use of Bayesian informative priors to aid in the transferability of NB SPFs, developed for Florida, to California's conditions and vice versa is investigated. It is demonstrated that informative priors facilitate SPF transferability. Furthermore, NB SPFs are developed for Florida, Ohio, Illinois, Minnesota, California, Washington and North Carolina. That is to evaluate the transferability of each state's SPFs to the other states' conditions. The results indicate that Ohio, Illinois, Minnesota and California have SPFs that are transferable to conditions of each of the four states. Also, two methods are proposed for calibrating transferred SPFs to the destinations' conditions and are shown to outperform the SPF calibration methods in the road safety literature. Finally, a variety of modeling frameworks are proposed for developing and transferring SPFs of the seven aforementioned states to each state's data. Not a single model exhibits the best fit when transferred in all cases. However, the Tobit model, NB model and a hybrid model that coalesces the results of both perform the best in a substantial number of the transferred SPFs.
Show less - Date Issued
- 2018
- Identifier
- CFE0007000, ucf:52054
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007000
- Title
- Warrants for Right-Turn Flashing Yellow Arrow Signal Phases.
- Creator
-
Alfawzan, Mohammed, Radwan, Ahmed, Eluru, Naveen, Abou-Senna, Hatem, Zheng, Qipeng, University of Central Florida
- Abstract / Description
-
The right-turn flashing yellow arrow (FYA) signal phasing is a new signal practice in the United States. The Manual on Uniform Traffic Control Devices MUTCD (2009) allocates a signal phasing section for the right-turn FYA, which requires a four-section head FYA signal. It supports multiple phases' indications that guide the motorist through permissive, protected, and/or permissive/protected phases. For this dissertation, I investigated three permissive right-turn FYA signal phases in various...
Show moreThe right-turn flashing yellow arrow (FYA) signal phasing is a new signal practice in the United States. The Manual on Uniform Traffic Control Devices MUTCD (2009) allocates a signal phasing section for the right-turn FYA, which requires a four-section head FYA signal. It supports multiple phases' indications that guide the motorist through permissive, protected, and/or permissive/protected phases. For this dissertation, I investigated three permissive right-turn FYA signal phases in various traffic conditions and signal timing circumstances. The first permissive right-turn FYA signal phase is the tight-turn on impeding through (RTOIT) taking place during the cross-street through traffic movement. The second permissive right-turn FYA signal phase occurs during the opposing left-turn approach movement and so is called the right-turn on impeding left (RTOIL). The third permissive right-turn phase is a right-turn on through green impeded only by the side street pedestrians called the right-turn on adjacent through (RTOAT). I aimed to develop warrants leading to efficient implementation of permissive right-turn FYA signal phases based on microsimulation analysis. I developed multinomial logit models to establish a decision support system that predicts the efficiency attributes of the permissive right-turn FYA signal phases.
Show less - Date Issued
- 2019
- Identifier
- CFE0007883, ucf:52801
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007883