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Title: Evaluation and Augmentation of Traffic Data from Private Sector and Bluetooth Detection System on Arterials.
Creator: Gong, Yaobang, Abdel-Aty, Mohamed, Hasan, Samiul, Cai, Qing, University of Central Florida
Abstract / Description: Traffic data are essential for public agencies to monitor the traffic condition of the roadway network in real-time. Recently, public agencies have implemented Bluetooth Detection Systems (BDS) on arterials to collect traffic data and purchased data directly from private sector vendors. However, the quality and reliability of the aforementioned two data sources are subject to rigorous evaluation. The thesis presents a study utilizing high-resolution GPS trajectories to evaluate data from HERE...
Show moreTraffic data are essential for public agencies to monitor the traffic condition of the roadway network in real-time. Recently, public agencies have implemented Bluetooth Detection Systems (BDS) on arterials to collect traffic data and purchased data directly from private sector vendors. However, the quality and reliability of the aforementioned two data sources are subject to rigorous evaluation. The thesis presents a study utilizing high-resolution GPS trajectories to evaluate data from HERE, one of the private sector data vendors, and BDS of arterial corridors in Orlando, Florida. The results showed that the accuracy and reliability of BDS data are better than private sector data, which might be credited to a better presentation of the bimodal traffic flow pattern on signalized arterials. In addition, another preliminary study aiming at improving the quality of private sector data was also demonstrated. Information about bimodal traffic flow extracted by a finite mixture model from historical BDS is employed to augment real-time private sector data by a Bayesian inference framework. The evaluation of the augmented data showed that the augmentation framework is effective for the most part of the studied corridor except for segments highly influenced by traffic from or to the expressway ramps.
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Date Issued: 2018
Identifier: CFE0007330, ucf:52120
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007330

Title: Real-Time Open Source Traffic Control Software for the Advance Traffic Controller.
Creator: Key, Justin, Radwan, Ahmed, Hua, Kien, Kincaid, John, Leonessa, Alexander, University of Central Florida
Abstract / Description: Under the initiative of Department of Transportation (DOT) a safety-critical, dual redundant, open source traffic signal control application is currently being developed. The system named SCOPE, for Signal Control Program Environment, currently implements standard 8-phase NEMA logic and the National Cooperative Highway Research Program 3-66 preemption logic. SCOPE is designed to be part of the Advanced Traffic Controller (ATC), making use of API standard 2.06b to integrate with the hardware....
Show moreUnder the initiative of Department of Transportation (DOT) a safety-critical, dual redundant, open source traffic signal control application is currently being developed. The system named SCOPE, for Signal Control Program Environment, currently implements standard 8-phase NEMA logic and the National Cooperative Highway Research Program 3-66 preemption logic. SCOPE is designed to be part of the Advanced Traffic Controller (ATC), making use of API standard 2.06b to integrate with the hardware. Safety-critical status is achieved through redundancy of application logic that constantly compares expected signal phase information. From baseline requirements, engineers independently program application code, one using Ada95 and the other using C++.The Traffic EXperimental Analytical Simulation Model, a microscopic single-intersection vehicular simulation, was used for initial validation and testing of the functionality of the system. The second demonstration of the SCOPE, used actuated detector data collected from a recording of a live intersection. Actuator calls were placed on SCOPE at the same times the vehicles triggered the detectors in the video (assuming the vehicles were not in-queue). Using SCOPE the real-world traffic was not only right-of-way safely yielded, but the traffic flow state time average time in-queue reduced. The final phase of testing will occur when the DOT performs Formal Qualification Testing, which is scheduled for 2013.Upon validation and subsequent release to the open source community SCOPE will provide users the ability to replace the proprietary application software residing in ATC cabinets. Transparency will be provided into another aspect of the traffic control signal thus taking the initiative of ATC one step further.
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Date Issued: 2012
Identifier: CFE0004562, ucf:49254
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004562

Title: A Computer Graphics Analysis of a Freeway Merge Control System.
Creator: Risher, Thomas A., Bauer, Christian, Engineering
Abstract / Description: Florida Technological University College of Engineering Thesis; In 1975, C.S. Bauer completed a doctoral dissertation at the University of Florida which treated the Green Band Merging Control System on I-75 in Tampa, Florida. In this work, Bauer suggested the possibility for the use of computer graphics as a toll for analysis of the bands generated by the Green Band Control System Simulation developed in his dissertation. The use of computer generated movies of the bands displayed to ramp...
Show moreFlorida Technological University College of Engineering Thesis; In 1975, C.S. Bauer completed a doctoral dissertation at the University of Florida which treated the Green Band Merging Control System on I-75 in Tampa, Florida. In this work, Bauer suggested the possibility for the use of computer graphics as a toll for analysis of the bands generated by the Green Band Control System Simulation developed in his dissertation. The use of computer generated movies of the bands displayed to ramp drivers by the system allows the comparison of various band control strategies without the need for field implementation and testing. With the goal of producing such films in mind, the research topic discussed in this paper was undertaken. The report introduces the reader to some of the basic aspects of computer graphics and presents specialized computer software and interface hardware for producing automated computer graphics movies from a Tektronix 4010 storage display. A brief discussion of the Tampa System and its associated simulation program is presented, and representative frames from the moves of the Tampa System produced in the research are discussed. Suggestions for additional work that could be undertaken in the research area conclude the report.
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Date Issued: 1976
Identifier: CFR0011597, ucf:53042
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0011597

Title: CREATING MODELS OF INTERNET BACKGROUND TRAFFIC SUITABLE FOR USE IN EVALUATING NETWORK INTRUSION DETECTION SYSTEMS.
Creator: LUO, SONG, Marin, Gerald, University of Central Florida
Abstract / Description: This dissertation addresses Internet background traffic generation and network intrusion detection. It is organized in two parts. Part one introduces a method to model realistic Internet background traffic and demonstrates how the models are used both in a simulation environment and in a lab environment. Part two introduces two different NID (Network Intrusion Detection) techniques and evaluates them using the modeled background traffic. To demonstrate the approach we modeled five major...
Show moreThis dissertation addresses Internet background traffic generation and network intrusion detection. It is organized in two parts. Part one introduces a method to model realistic Internet background traffic and demonstrates how the models are used both in a simulation environment and in a lab environment. Part two introduces two different NID (Network Intrusion Detection) techniques and evaluates them using the modeled background traffic. To demonstrate the approach we modeled five major application layer protocols: HTTP, FTP, SSH, SMTP and POP3. The model of each protocol includes an empirical probability distribution plus estimates of application-specific parameters. Due to the complexity of the traffic, hybrid distributions (called mixture distributions) were sometimes required. The traffic models are demonstrated in two environments: NS-2 (a simulator) and HONEST (a lab environment). The simulation results are compared against the original captured data sets. Users of HONEST have the option of adding network attacks to the background. The dissertation also introduces two new template-based techniques for network intrusion detection. One is based on a template of autocorrelations of the investigated traffic, while the other uses a template of correlation integrals. Detection experiments have been performed on real traffic and attacks; the results show that the two techniques can achieve high detection probability and low false alarm in certain instances.
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Date Issued: 2005
Identifier: CFE0000852, ucf:46667
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000852

Title: The effects of altered traffic signs upon vehicular driving modes and consequent fuel conservation and environmental benefits, as measured by vehicular noise-imprints.
Creator: Pfarrer, Mark Daniel, null, null, Engineering
Abstract / Description: Florida Technological University College of Engineering Thesis; The hypothesis is that the recorded noise-imprints of a vehicle at an intersection can be used to identify and accurately time the driving modes of deceleration, idle, slow cruise, and acceleration. This is proven by analyzing and comparing noise-imprints of vehicles at an uncontrolled intersection marked first with a 'stop' sign, and then by a 'yield' and an experimental 'dead slow' sign. By relating the duration of each driving...
Show moreFlorida Technological University College of Engineering Thesis; The hypothesis is that the recorded noise-imprints of a vehicle at an intersection can be used to identify and accurately time the driving modes of deceleration, idle, slow cruise, and acceleration. This is proven by analyzing and comparing noise-imprints of vehicles at an uncontrolled intersection marked first with a 'stop' sign, and then by a 'yield' and an experimental 'dead slow' sign. By relating the duration of each driving mode to known relations, the overall efficiency of an intersection can be characterized. A new technique for studying various types of traffic conditions at intersections is the result. Initial noise-imprint analysis and comparison shows that a 'yield' sign is to be preferred over a 'stop' sign to decrease travel time, air pollution emissions, gasoline consumption, and wear-and-tear on the car. The experimental 'dead slow' sign is used as a demonstration of the noise-imprint technique upon an unknown situation. The efficiency of a 'dead slow' sign proved to be less than that of a 'yield' sign, but still greater than that of a 'stop' sign.
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Date Issued: 1976
Identifier: CFR0003525, ucf:52986
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0003525

Title: Feasability analysis of ramp control systems, a simulation approach.
Creator: Popkin, Henry Allen, Klee, Harold, Engineering
Abstract / Description: Florida Technological University College of Engineering Thesis; The ever increasing traffic congestion being experienced on urban freeways has caused attention to be focused on methods for improving traffic operations on these facilities. The reduction or elimination of freeway congestion can be handled in two basic ways: 1) by increasing the freeway's capacity defined as the number of vehicles per unit time that can pass a given point in one lane of the freeway multiplied by the number of...
Show moreFlorida Technological University College of Engineering Thesis; The ever increasing traffic congestion being experienced on urban freeways has caused attention to be focused on methods for improving traffic operations on these facilities. The reduction or elimination of freeway congestion can be handled in two basic ways: 1) by increasing the freeway's capacity defined as the number of vehicles per unit time that can pass a given point in one lane of the freeway multiplied by the number of lanes on the freeway, or 2) by decreasing the traffic loads imposed on these freeways. Monumental costs and adverse public relations are involved in the construction of either new freeways or additional lanes in urban areas to increase freeway capacity. Due to these factors, the move in recent years has been toward decreasing traffic loads to accomplish the goals of reduction or elimination of freeway congestion. In an effort to combat the freeway congestion, traffic researchers have devoted much time and effort to the theoretical and practical aspects of systems in which controlled access is utilized to prevent or reduce congestion caused by traffic demands in excess of freeway operational capacity. Such systems perform the function of 'freeway surveillance and control'. An important aspect of these systems is the control mechanism used for the regulation of the ramp traffic to the freeway. This topic of ramp metering is the subject of this report.
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Date Issued: 1975
Identifier: CFR0003522, ucf:52998
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0003522

Title: Urban Expressway Safety and Efficiency Evaluation and Improvement using Big Data.
Creator: Shi, Qi, Abdel-Aty, Mohamed, Eluru, Naveen, Nam, Boo Hyun, Lee, Chris, University of Central Florida
Abstract / Description: In an age of data explosion, almost every aspect of social activities is impacted by the abundance of information. The information, characterized by alarming volume, velocity and variety, is often referred to as (")Big Data("). As one fundamental elements of human life, transportation also confronts the promises and challenges brought about by the Big Data era. Big Data in the transportation arena, enabled by the rapid popularization of Intelligent Transportation Systems (ITS) in the past few...
Show moreIn an age of data explosion, almost every aspect of social activities is impacted by the abundance of information. The information, characterized by alarming volume, velocity and variety, is often referred to as (")Big Data("). As one fundamental elements of human life, transportation also confronts the promises and challenges brought about by the Big Data era. Big Data in the transportation arena, enabled by the rapid popularization of Intelligent Transportation Systems (ITS) in the past few decades, are often collected continuously from different sources over vast geographical scale. Huge in size and rich in information, the seemingly disorganized data could considerably enhance experts' understanding of their system. In addition, proactive traffic management for better system performance is made possible due to the real-time nature of the Big Data in transportation.Operation efficiency and traffic safety have long been deemed as priorities among highway system performance measurement. While efficiency could be evaluated in terms of traffic congestion, safety is studied through crash analysis. Extensive works have been conducted to identify the contributing factors and remedies of traffic congestion and crashes. These studies lead to gathering consensus that operation and safety have played as two sides of a coin, ameliorating either would have a positive effect on the other. With the advancement of Big Data, monitoring and improvement of both operation and safety proactively in real-time have become an urgent call.In this study, the urban expressway network operated by Central Florida Expressway Authority's (CFX) traffic safety and efficiency was investigated. The expressway system is equipped with multiple Intelligent Transportation Systems (ITS). CFX utilizes Automatic Vehicle Identification (AVI) system for Electronic Toll Collection (ETC) as well as for the provision of real-time information. Recently, the authority introduced Microwave Vehicle Detection System (MVDS) on their expressways for more precise traffic monitoring. These traffic detection systems collect different types of traffic data continuously on the 109-mile expressway network, making them one of the sources of Big Data. In addition, multiple Dynamic Message Signs are currently in use to communicate between CFX and motorists. Due to their dynamic nature, they serve as an ideal tool for efficiency and safety improvement. Careful examination of the Big Data from the ITS traffic detection systems was carried out. Based on the characteristics of the data, three types of congestion measures based on the AVI and MVDS system were proposed for efficiency evaluation. MVDS-based congestion measures were found to be better at capturing the subtle changes in congestion in real-time compared with the AVI-based congestion measure. Moreover, considering the high deployment density of the MVDS system, the whole expressway network is well covered. Thus congestion could be evaluated at the microscopic level in both spatial and temporal dimensions. According to the proposed congestion measurement, both mainline congested segments and ramps experiencing congestion were identified. For congestion alleviation, the existing DMS that could be utilized for queue warning were located. In case of no existing DMS available upstream to the congestion area, the potential area where future DMS could be considered was suggested. Substantial efforts have also been dedicated to Big Data applications in safety evaluation and improvement. Both aggregate crash frequency modeling and disaggregate real-time crash prediction were constructed to explore the use of ITS detection data for urban expressway safety analyses. The safety analyses placed an emphasis on the congestion's effects on the Expressway traffic safety. In the aggregate analysis the three congestion measures developed in this research were tested in the context of safety modeling and their performances compared. Multi-level Bayesian ridge regression was utilized to deal with the multicollinearity issue in the modeling process. While all of the congestion measures indicated congestion was a contributing factor to crash occurrence in the peak hours, they suggested that off-peak hour crashes might be caused by factors other than congestion. Geometric elements such as the horizontal curves and existence of auxiliary lanes were also identified to significantly affect the crash frequencies on the studied expressways.In the disaggregate analysis, rear-end crashes were specifically studied since their occurrence was believed to be significantly related to the traffic flow conditions. The analysis was conducted in Bayesian logistic regression framework. The framework achieved relatively good classifier performance. Conclusions confirmed the significant effects of peak hour congestion on crash likelihood. Moreover, a further step was taken to incorporate reliability analysis into the safety evaluation. With the developed logistic model as a system function indicating the safety states under specific traffic conditions, this method has the advantage that could quantitatively determine the traffic states appropriate to trigger safety warning to motorists. Results from reliability analysis also demonstrate the peak hours as high risk time for rear-end crashes. Again, DMS would be an essential tool to carry the messages to drivers for potential safety benefits. In existing safety studies, the ITS traffic data were normally used in aggregated format or only the pre-crash traffic data were used for real-time prediction. However, to fully realize their applications, this research also explored their use from a post-crash perspective. The real-time traffic states immediately before and after crash occurrence were extracted to identify whether the crash caused traffic deterioration. Elements regarding spatial, temporal, weather and crash characteristics from individual crash reports were adopted to analyze under what conditions a crash could significantly worsen traffic conditions on urban expressways. Multinomial logit model and two separate binomial models were adopted to identify each element's effects. Expected contribution of this work is to shorten the reaction and clearance time to those crashes that might cause delay on expressways, thus reducing congestion and probability of secondary crashes simultaneously.Finally, potential relevant applications beyond the scope of this research but worth investigation in the future were proposed.
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Date Issued: 2014
Identifier: CFE0005886, ucf:50888
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005886

Title: MODELING OF ATMOSPHERIC REFRACTION EFFECTS ON TRAFFIC NOISE PROPAGATION.
Creator: El-Aassar, Ahmed, Wayson, Roger, University of Central Florida
Abstract / Description: Traffic noise has been shown to have negative effects on exposed persons in the communities along highways. Noise from transportation systems is considered a nuisance in the U.S. and the government agencies require a determination of noise impacts for federally funded projects. There are several models available for assessing noise levels impacts. These models vary from simple charts to computer design models. Some computer models, i.e. Standard Method In Noise Analysis (STAMINA), the Traffic...
Show moreTraffic noise has been shown to have negative effects on exposed persons in the communities along highways. Noise from transportation systems is considered a nuisance in the U.S. and the government agencies require a determination of noise impacts for federally funded projects. There are several models available for assessing noise levels impacts. These models vary from simple charts to computer design models. Some computer models, i.e. Standard Method In Noise Analysis (STAMINA), the Traffic Noise Model (TNM) and the UCF Community Noise Model (CNM), have been used to predict geometric spreading, atmospheric absorption, diffraction, and ground impedance. However, they have largely neglected the atmospheric effects on noise propagation in their algorithms. The purpose of this research was to better understand and predict the meteorological effects on traffic noise propagation though measurements and comparison to acoustic theory. It should be noted that this represents an approach to incorporate refraction algorithms affecting outdoor noise propagation that must also work with algorithms for geometric spreading, ground effects, diffraction, and turbulence. The new empirical model for predicting atmospheric refraction shows that wind direction is a significant parameter and should be included in future modeling for atmospheric refraction. To accomplish this, the model includes a "wind shear" and "lapse rate" terms instead of wind speed and temperature as previously needed for input of the most used models. The model is an attempt to explain atmospheric refraction by including the parameters of wind direction, wind shear, and lapse rate that directly affect atmospheric refraction.
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Date Issued: 2006
Identifier: CFE0001505, ucf:47140
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001505

Title: SIMULATION AND CONTINUANCE OF OPERATION FOR THE USE OF TRANSIT (LYNX) TO BE USED IN EMERGENCY EVACUATION INCIDENTS.
Creator: Elmitiny, Noor, Radwan, Essam, University of Central Florida
Abstract / Description: The evacuation planning has become an important issue addressed by many research studies and publications aiming to improve the security of the daily life for our public inside the United States of America. The main objective of this research was to address the growing need for evacuation planning using traffic simulation. With increased interests and awareness in emergency evacuation and first responder access to emergencies in public locations (airports, transit stations, ports or stadiums)...
Show moreThe evacuation planning has become an important issue addressed by many research studies and publications aiming to improve the security of the daily life for our public inside the United States of America. The main objective of this research was to address the growing need for evacuation planning using traffic simulation. With increased interests and awareness in emergency evacuation and first responder access to emergencies in public locations (airports, transit stations, ports or stadiums), the traffic simulation can be helpful in orchestrating the traffic flow during emergencies. Related to this issue, Federal Transit Administration has issued a large number of publications and guidelines concerning emergency preparedness and incident management. These guidelines are used to develop a simulation-based activity to evaluate the current plan and alternative plans for the deployment of transit during an emergency situation. A major task for this project is to study the effect of evacuation on the surrounding traffic network and help the local transit company (LYNX) to evaluate their evacuation plan and consider different possibilities without the risk and cost of actual evacuation drills. A set of different scenarios and alternatives for each scenario were simulated and studied to reach the best possible evacuation strategy. The main findings were evacuation as pedestrians have less impact on traffic network and rerouting decreases the congestion resulting from the evacuation process.
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Date Issued: 2006
Identifier: CFE0001188, ucf:46870
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001188

Title: A Comprehensive Severity Analysis of Large Vehicle Crashes.
Creator: Laman, Haluk, Abdel-Aty, Mohamed, Tatari, Mehmet, Ahmed, Mohamed, University of Central Florida
Abstract / Description: The goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large...
Show moreThe goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large vehicle crashes.Using the crashes involving large vehicles, a model comparison between binary logit model and a Chi-squared Automatic Interaction Detection (CHAID) decision tree model is provided. There were 13 significant factors (i.e. crash type with respect to vehicle types, residency of driver, DUI, rural-urban, etc.) found significant in the logistic procedure while 7 factors found (i.e. posted speed limit, intersection, etc.) in the CHAID model. The model comparison results indicate that the logit analysis procedure is better in terms of prediction power.The following analysis is a modeling structure involving three binary logit models. The first model was conducted to estimate the crash severity of crashes that involved only personal vehicles (PV). Second model uses the crashes that involved large vehicles (LV) and passenger vehicles (PV). The final model estimated the severity level of crashes involving only large vehicles (LV). Significant differences with respect to various risk factors including driver, vehicle, environmental, road geometry and traffic characteristics were found to exist between those crash types and models. For example, driving under the influence of Alcohol (DUI) has positive effect on the severity of PV vs. PV and LV vs. PV while it has no effect on LV vs. LV. As a result, 4 of the variables found to be significant were similar in all three models (although often with quite different impact) and there were 11 variables that significantly influenced crash injury severity in PV vs. PV crashes, and 9 variables that significantly influenced crash injury severity in LV vs. PV crashes.Based on the significant variables, maximum posted speed, number of vehicles involved, and intersections are among the factors that have major impact on injury severity. These results could be used to identify potential countermeasures to reduce crash severity in general, and for LVs in particular. For example, restricting the speed limits and enforcing it for large vehicles could be a suggested countermeasure based on this study.
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Date Issued: 2012
Identifier: CFE0004566, ucf:49216
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004566

Title: Conversion and Validation of SIGART Program, a Progressive Traffic Signal Lights System Computer Model.
Creator: Troyan, Dennis F., McEwan, Stuart, Engineering
Abstract / Description: Florida Technological University College of Engineering Thesis
Date Issued: 1972
Identifier: CFR0011995, ucf:53082
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0011995

Title: A GPSS/360 Computer Model for Simulation of Automobile Traffic at Intersections.
Creator: Golovcsenko, Igor V., ,, Engineering
Abstract / Description: Florida Technological University College of Engineering Thesis
Date Issued: 1974
Identifier: CFR0011598, ucf:53135
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFR0011598

Title: Dynamic Hotspot Identification for Limited Access Facilities using Temporal Traffic Data.
Creator: Al Amili, Samer, Abdel-Aty, Mohamed, Radwan, Essam, Eluru, Naveen, Lee, JaeYoung, Wang, Chung-Ching, University of Central Florida
Abstract / Description: Crash frequency analysis is the most critical tool to investigate traffic safety problems. Therefore, an accurate crash analysis must be conducted. Since traffic continually fluctuates over time and this effects potential of crash occurrence, shorter time periods and less aggregated traffic factors (shorter intervals than AADT) need to be used. In this dissertation, several methodologies have been conducted to elevate the accuracy of crash prediction. The performance of using less aggregated...
Show moreCrash frequency analysis is the most critical tool to investigate traffic safety problems. Therefore, an accurate crash analysis must be conducted. Since traffic continually fluctuates over time and this effects potential of crash occurrence, shorter time periods and less aggregated traffic factors (shorter intervals than AADT) need to be used. In this dissertation, several methodologies have been conducted to elevate the accuracy of crash prediction. The performance of using less aggregated traffic data in modeling crash frequency was explored for weekdays and weekends. Four-time periods for weekdays and two time periods for weekends, with four intervals (5, 15, 30, and 60 minutes). The comparison between AADT based models and short-term period models showed that short-term period models perform better. As a shorter traffic interval than AADT considered, two difficulties began. Firstly, the number of zero observations increased. Secondly, the repetition of the same roadway characteristics arose. To reduce the number of zero observations, only segments with one or more crashes were used in the modeling process. To eliminate the effect of the repetition in the data, random effect was applied. The results recommend adopting segments with only one or more crashes, as they give a more valid prediction and less error.Zero-inflated negative binomial (ZINB) and hurdle negative binomial (HNB) models were examined in addition to the negative binomial for both weekdays and weekends. Different implementations of random effects were applied. Using the random effect either on the count part, on the zero part, or a pair of uncorrelated (or correlated) random effects for both parts of the model. Additionally, the adaptive Gaussian Quadrature, with five quadrature points, was used to increase accuracy. The results reveal that the model which considered the random effect in both parts performed better than other models, and ZINB performed better than HNB.
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Date Issued: 2018
Identifier: CFE0006966, ucf:51682
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006966

Title: An Analysis of the Protected-Permitted Left Turn at Intersections with a Varying Number of Opposing Through Lanes.
Creator: Navarro, Alexander, Radwan, Essam, Abou-Senna, Hatem, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: The Flashing Yellow Arrow Left Turn signal is quickly becoming prominent in Central Florida as a new method of handling left turns at traffic signals. While the concept of a protected-permitted left turn is not groundbreaking, the departure from the typical display of a five-section signal head is, for this type of operation. The signal head introduced is a four-section head with a flashing yellow arrow between the yellow and green arrows. With this signal head quickly becoming the standard,...
Show moreThe Flashing Yellow Arrow Left Turn signal is quickly becoming prominent in Central Florida as a new method of handling left turns at traffic signals. While the concept of a protected-permitted left turn is not groundbreaking, the departure from the typical display of a five-section signal head is, for this type of operation. The signal head introduced is a four-section head with a flashing yellow arrow between the yellow and green arrows. With this signal head quickly becoming the standard, there is a need to re-evaluate the operational characteristics of the left turning vehicle and advance the knowledge of the significant parameters that may affect the ability for a driver to make a left turn at a signalized intersection. With previous research into the behavioral and operational characteristics of the flashing yellow arrow conducted, there is more information becoming available about the differences between this signal and the previously accepted method of allowing left turns at an intersection. The protected-permitted signal is typically displayed at an intersection with up to two through lanes and generally a protected signal is installed when the number of through lanes increases above two unless specific criteria is met. With the advent of larger arterials and more traffic on the highway networks, the push to operate these intersections at their maximum efficiency has resulted in more of these protected-permitted signals being present at these larger intersections, including the flashing yellow arrow.The core of the research that follows is a comparative analysis of the operation and parameters that affect the left turn movement of the intersection with larger geometry to that of the smaller geometry. The significant parameters of the left turn movement were examined through means of collecting, organizing and analyzing just over 68 hours of field data. This research details the determining of the significant parameters based on the generation of a simulation model of the protected left turn using Synchro, a traffic simulation package, and regression models using field driven data to determine the significant parameters for predicting the number of left turns that can be made in the permitted phase under specific operating conditions. Intuitively, there is an expectation that a larger intersection will not allow for as many permitted lefts as a smaller intersection with all conditions remaining the same. The conclusions drawn from this analysis provide the framework to understanding the similarities and the differences that are encountered when the intersection geometry differs and help to more efficiently manage traffic at signalized intersections.The work of this field promises to enhance the operations of the left turning movement for traffic control devices. With an understanding of the statistical models generated, a broader base of knowledge is gained as to the significant parameters that affect a driver's ability to make the left turn. A discussion of the statistical differences and between the models generated from the small and large geometry intersections is critical to drive further research into standards being developed for the highway transportation network and the treatment of these large signalized intersections. The exploration of specific parameters to predict the number of permitted left turns will yield results as to if there is more to be considered with larger intersections moving forward as they become a standard sight on the roadway network.
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Date Issued: 2014
Identifier: CFE0005387, ucf:50440
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005387

Title: A New Multidimensional Psycho-Physical Framework for Modeling Car-Following in a Freeway Work Zone.
Creator: Lochrane, Taylor, Al-Deek, Haitham, Radwan, Essam, Oloufa, Amr, Harb, Rami, Uddin, Nizam, University of Central Florida
Abstract / Description: As the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation...
Show moreAs the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation hypothesizes that drivers change their driving behavior as they drive through a freeway work zone compared to normal freeway conditions which has the potential to impact traffic operations and capacity of work zones. Psycho-physical car-following models are widely used in practice for simulating car-following. However, current simulation models may not fully capture car-following driver behavior specific to freeway work zones. This dissertation presents a new multidimensional psycho-physical framework for modeling car-following based on statistical evaluation of work zone and non-work zone driver behavior. This new framework is close in character to the Wiedemann model used in popular traffic simulation software such as VISSIM. This dissertation used two methodologies for collecting data: (1) a questionnaire to collect demographics and work zone behavior data and (2) a real-time vehicle data from a field experiment involving human participants. It is hypothesized that the parameters needed to calibrate the multidimensional framework for work zone driver behavior can be derived statistically by using data collected from runs of an Instrumented Research Vehicle (IRV) in a Living Laboratory (LL) along a roadway. The design of this LL included the development of an Instrumented Research Vehicle (IRV) to capture the natural car-following response of a driver when entering and passing through a freeway work zone. The development of a Connected Mobile Traffic Sensing (CMTS) system, which included state-of-the-art ITS technologies, supports the LL environment by providing the connectivity, interoperability and data processing of the natural, real-life setting. The IRV and CMTS system are tools designed to support the concept of a LL which facilitates the experimental environment to capture and calibrate natural driver behavior. The objective is to have these participants drive the instrumented vehicle and collect the relative distance and the relative velocity between the instrumented vehicle and the vehicle in the front of the instrumented vehicle. A Phase I pilot test was conducted with 10 participants to evaluate the experiment and make any adjustments prior to the full Phase II driver test. The Phase II driver test recruited a group of 64 participants to drive the IRV through an LL set up along a work zone on I-95 near Washington D.C. in order to validate this hypothesis In this dissertation, a new framework was applied and it demonstrated that there are four different categories of car-following behavior models each with different parameter distributions. The four categories are divided by traffic condition (congested vs. uncongested) and by roadway condition (work zone vs. non-work zone). The calibrated threshold values are presented for each of these four categories. By applying this new multidimensional framework, modeling of car-following behavior can enhance vehicle behavior in microsimulation modeling.This dissertation also explored driver behavior through combining vehicle data and survey techniques to augment the model calibrations to improve the understanding of car-following behavior in freeway work zones. The results identify a set of survey questions that can potentially guide the selection of parameters for car-fallowing models. The findings presented in this dissertation can be used to improve the performance of driver behavior models specific to work zones. This in return will more acutely forecast the impact a work zone design has on capacity during congestion.
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Date Issued: 2014
Identifier: CFE0005521, ucf:50326
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005521

Title: Real-time traffic safety evaluation models and their application for variable speed limits.
Creator: Yu, Rongjie, Abdel-Aty, Mohamed, Radwan, Ahmed, Madani Larijani, Kaveh, Ahmed, Mohamed, Wang, Xuesong, University of Central Florida
Abstract / Description: Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly...
Show moreTraffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence.In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics.In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies.In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence.Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear-end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level's diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the single-vehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence.Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL's impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL's safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.
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Date Issued: 2013
Identifier: CFE0005283, ucf:50556
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005283

Title: ASSESSMENT OF THE SAFETY BENEFITS OF VMS AND VSL USING THE UCF DRIVING SIMULATOR.
Creator: Dos Santos, Cristina, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: Researchers at the University of Central Florida (UCF) have been working during the past few years on different strategies to improve freeway safety in real-time. An ongoing research at UCF has investigated crash patterns that occurred on a stretch of Interstate-4 located in Orlando, FL and created statistical models to predict in real-time the likelihood of a crash in terms of time and space. The models were then tested using PARAMICS micro-simulation and different strategies that would...
Show moreResearchers at the University of Central Florida (UCF) have been working during the past few years on different strategies to improve freeway safety in real-time. An ongoing research at UCF has investigated crash patterns that occurred on a stretch of Interstate-4 located in Orlando, FL and created statistical models to predict in real-time the likelihood of a crash in terms of time and space. The models were then tested using PARAMICS micro-simulation and different strategies that would reduce the risk of crashes were suggested. One of the main recommended strategies was the use of Variable Speed Limits (VSL) which intervenes by reducing the speed upstream the segment of high risk and increasing the speed downstream. The purpose of this study is to examine the recommendations reached by the micro-simulation using the UCF driving simulator. Drivers' speed behavior in response to changes in speed limits and different information messages are observed. Different scenarios that represent the recommendations from the earlier micro-simulation study and three different messages displayed using Variable Message Signs (VMS) as an added measure to advice drivers about changes in the speed limit were created. In addition, abrupt and gradual changes in speed were tested against the scenarios that maintained the speed limit constant or did include a VSL or VMS in the scenarios' design (base case). Dynamic congestion was also added to the scenarios' design to observe drivers' reactions and speed reductions once drivers approached congestion. A total of 85 subjects were recruited. Gender and age were the controlling variables for the subjects' recruitment. Each of the subjects drove 3 out of a total of 24 scenarios. In addition, a survey was conducted and involved hypothetical questions, including knowledge about VMS and VSL, and questions about their driving behavior. The survey data were useful in identifying the subjects' compliance with the speed limit and VSL/VMS acceptance. Two statistical analytical techniques were performed on the data that were collected from the simulator: ANOVA and PROC MIXED. The ANOVA test was used to investigate if the differences in speed and reaction distances between subjects were statistically significant for each sign compared to the base case. The PROC MIXED analysis was used to investigate the differences of all scenarios (24x24) based on the spot speed data collected for each driver. It was found from the analyses that drivers follow better the message displayed on VMS that informs them that the speed is changing, whether it is or not, strictly enforced as opposed to providing the reason for change or no information. Moreover, an abrupt change in speed produced immediate results; however both abrupt and gradual changes in speed produced the same reduction in speed at the target zone. It was also noticed that most drivers usually drive 5 mph above the speed limit, even though in the survey analysis the majority of them stated that they drive in compliance with the speed limit or with the flow of traffic. This means that if a modest speed reduction of 5 mph is requested they will ignore it, but if a 10 mph reduction is recommended they will reduce the speed by at least 5 mph. Consequently, it was noticed that drivers arrived at the congestion zone with a slower speed than the base speed limit due to the combination of VMS and VSL signage. By having drivers approaching congestion with a slower speed, potential rear-end crashes could be avoided. Comparing the two genders indicated that females are more likely to follow the VMS's recommendations to reduce the speed. Also females in general drive above the speed limit between 2 mph and 3 mph, while males drive above the speed limit between 5 mph and 8 mph. From the analysis of the age factor, it was concluded that drivers from the 16-19 age group drive faster and drivers from the 45 and above age group drive slower, than the drivers from the other groups. In general, all drivers reduced and/or increased their speed accordingly when a VMS and/or VSL was present in the scenario advising for this change in the speed limit. The investigations conducted for this thesis proved that the recommendations suggested previously based on the crash risk model and micro-simulation (Abdel-Aty et al., 2006) aid drivers in reducing their speed before they approach a segment of high risk and by doing so reduce the likelihood of a crash. Finally, the real-time safety benefits of VMS and VSL should be continuously evaluated in future studies.
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Date Issued: 2007
Identifier: CFE0001628, ucf:47167
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001628

Title: Development of Decision Support System for Active Traffic Management Systems Considering Travel Time Reliability.
Creator: Chung, Whoibin, Abdel-Aty, Mohamed, Eluru, Naveen, Hasan, Samiul, Cai, Qing, Huang, Hsin-Hsiung, University of Central Florida
Abstract / Description: As traffic problems on roadways have been increasing, active traffic management systems (ATM) using proactive traffic management concept have been deployed on freeways and arterials. The ATM aims to integrate and automate various traffic control strategies such as variable speed limits, queue warning, and ramp metering through a decision support system (DSS). Over the past decade, there have been many efforts to integrate freeways and arterials for the efficient operation of roadway networks....
Show moreAs traffic problems on roadways have been increasing, active traffic management systems (ATM) using proactive traffic management concept have been deployed on freeways and arterials. The ATM aims to integrate and automate various traffic control strategies such as variable speed limits, queue warning, and ramp metering through a decision support system (DSS). Over the past decade, there have been many efforts to integrate freeways and arterials for the efficient operation of roadway networks. It has been required that these systems should prove their effectiveness in terms of travel time reliability. Therefore, this study aims to develop a new concept of a decision support system integrating variable speed limits, queue warning, and ramp metering on the basis of travel time reliability of freeways and arterials.Regarding the data preparation, in addition to collecting multiple data sources such as traffic data, crash data and so on, the types of traffic data sources that can be applied for the analysis of travel time reliability were investigated. Although there are many kinds of real-time traffic data from third-party traffic data providers, it was confirmed that these data cannot represent true travel time reliability through the comparative analysis of measures of travel time reliability. Related to weather data, it was proven that nationwide land-based weather stations could be applicable.Since travel time reliability can be measured by using long-term periods for more than six months, it is necessary to develop models to estimate travel time reliability through real-time traffic data and event-related data. Among various matrix to measure travel time reliability, the standard deviation of travel time rate [minute/mile] representing travel time variability was chosen because it can represent travel time variability of both link and network level. Several models were developed to estimate the standard deviation of travel time rate through average travel time rate, the number of lanes, speed limits, and the amount of rainfall.Finally, a DSS using a model predictive control method to integrate multiple traffic control measures was developed and evaluated. As a representative model predictive control, METANET model was chosen, which can include variable speed limit, queue warning, and ramp metering, separately or combined. The developed DSS identified a proper response plan by comparing travel time reliability among multiple combinations of current and new response values of strategies. In the end, it was found that the DSS provided the reduction of travel time and improvement of its reliability for travelers through the recommended response plans.
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Date Issued: 2019
Identifier: CFE0007615, ucf:52542
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007615

Title: Macroscopic Crash Analysis and Its Implications for Transportation Safety Planning.
Creator: Siddiqui, Chowdhury, Abdel-Aty, Mohamed, Abdel-Aty, Mohamed, Uddin, Nizam, Huang, Helai, University of Central Florida
Abstract / Description: Incorporating safety into the transportation planning stage, which is often termed as transportation safety planning (TSP), relies on the vital interplay between zone characteristics and zonal traffic crashes. Although a few safety studies had made some effort towards integrating safety and planning, several unresolved problems and a complete framework of TSP are still absent in the literature. This research aims at examining the suitability of the current traffic-related zoning planning...
Show moreIncorporating safety into the transportation planning stage, which is often termed as transportation safety planning (TSP), relies on the vital interplay between zone characteristics and zonal traffic crashes. Although a few safety studies had made some effort towards integrating safety and planning, several unresolved problems and a complete framework of TSP are still absent in the literature. This research aims at examining the suitability of the current traffic-related zoning planning process in a new suggested planning method which incorporates safety measures. In order to accomplish this broader research goal, the study defined its research objectives in the following directions towards establishing a framework of TSP- i) exploring the existing key determinants in traditional transportation planning (e.g., trip generation/distribution data, land use types, demographics, etc.) in order to develop an effective and efficient TSP framework, ii) investigation of the Modifiable Aerial Unit Problem (MAUP) in the context of macro-level crash modeling to investigate the effect of the zone's size and boundary, iii) understanding neighborhood influence of the crashes at or near zonal boundaries, and iv) development of crash-specific safety measure in the four-step transportation planning process.This research was conducted using spatial data from the counties of West Central Florida. Analysis of different crash data per spatial unit was performed using nonparametric approaches (e.g., data mining and random forest), classical statistical methods (e.g., negative binomial models), and Bayesian statistical techniques. In addition, a comprehensive Geographic Information System (GIS) based application tools were utilized for spatial data analysis and representation.Exploring the significant variables related to specific types of crashes is vital in the planning stages of a transportation network. This study identified and examined important variables associated with total crashes and severe crashes per traffic analysis zone (TAZ) by applying nonparametric statistical techniques using different trip related variables and road-traffic related factors. Since a macro-level analysis, by definition, will necessarily involve aggregating crashes per spatial unit, a spatial dependence or autocorrelation may arise if a particular variable of a geographic region is affected by the same variable of the neighboring regions. So far, few safety studies were performed to examine crashes at TAZs and none of them explicitly considered spatial effect of crashes occurring in them. In order to understand the clear picture of spatial autocorrelation of crashes, this study investigated the effect of spatial autocorrelation in modeling pedestrian and bicycle crashes in TAZs. Additionally, this study examined pedestrian crashes at Environmental Justice (EJ) TAZs which were identified in compliance with the various ongoing practices undertaken by Metropolitan Planning Organizations (MPOs) and previous research. Minority population and the low-income group are two important criteria based on which EJ areas are being identified. These unique areal characteristics have been of particular interest to the traffic safety analysts in order to investigate the contributing factors of pedestrian crashes in these deprived areas. Pedestrian and bicycle crashes were estimated as a function of variables related to roadway characteristics, and various demographic and socio-economic factors. It was found that significant differences are present between the predictor sets for pedestrian and bicycle crashes. In all cases the models with spatial correlation performed better than the models that did not account for spatial correlation among TAZs. This finding implied that spatial correlation should be considered while modeling pedestrian and bicycle crashes at the aggregate or macro-level. Also, the significance of spatial autocorrelation was later found in the total and severe crash analyses and accounted for in their respective modeling techniques.Since the study found affirmative evidence about the inclusion of spatial autocorrelation in the safety performance functions, this research considered identifying appropriate spatial entity based on which TSP framework would be developed. A wide array of spatial units has been explored in macro-level crash modeling in previous safety research. With the advancement of GIS, safety analysts are able to analyze crashes for various geographical units. However, a clear guideline on which geographic entity should a modeler choose is not present so far. This preference of spatial unit can vary with the dependent variable of the model. Or, for a specific dependent variable, models may be invariant to multiple spatial units by producing a similar goodness-of-fits. This problem is closely related to the Modifiable Areal Unit Problem which is a common issue in spatial data analysis. The study investigated three different crash (total, severe, and pedestrian) models developed for TAZs, block groups (BGs) and census tracts (CTs) using various roadway characteristics and census variables (e.g., land use, socio-economic, etc.); and compared them based on multiple goodness-of-fit measures.Based on MAD and MSPE it was evident that the total, severe and pedestrian crash models for TAZs and BGs had similar fits, and better than the ones developed for CTs. This indicated that the total, severe and pedestrian crash models are being affected by the size of the spatial units rather than their zoning configurations. So far, TAZs have been the base spatial units of analyses for developing travel demand models. Metropolitan planning organizations widely use TAZs in developing their long range transportation plans (LRTPs). Therefore, considering the practical application it was concluded that as a geographical unit, TAZs had a relative ascendancy over block group and census tract.Once TAZs were selected as the base spatial unit of the TSP framework, careful inspections on the TAZ delineations were performed. Traffic analysis zones are often delineated by the existing street network. This may result in considerable number of crashes on or near zonal boundaries. While the traditional macro-level crash modeling approach assigns zonal attributes to all crashes that occur within the zonal boundary, this research acknowledged the inaccuracy resulting from relating crashes on or near the boundary of the zone to merely the attributes of that zone. A novel approach was proposed to account for the spatial influence of the neighboring zones on crashes which specifically occur on or near the zonal boundaries. Predictive model for pedestrian crashes per zone were developed using a hierarchical Bayesian framework and utilized separate predictor sets for boundary and interior (non-boundary) crashes. It was found that these models (that account for boundary and interior crashes separately) had better goodness-of-fit measures compared to the models which had no specific consideration for crashes located at/near the zone boundaries. Additionally, the models were able to capture some unique predictors associated explicitly with interior and boundary-related crashes. For example, the variables- 'total roadway length with 35mph posted speed limit' and 'long term parking cost' were statistically not significantly different from zero in the interior crash model but they were significantly different from zero at the 95% level in the boundary crash model.Although an adjacent traffic analysis zones (a single layer) were defined for pedestrian crashes and boundary pedestrian crashes were modeled based on the characteristic factors of these adjacent zones, this was not considered reasonable for bicycle-related crashes as the average roaming area of bicyclists are usually greater than that of pedestrians. For smaller TAZs sometimes it is possible for a bicyclist to cross the entire TAZ. To account for this greater area of coverage, boundary bicycle crashes were modeled based on two layers of adjacent zones. As observed from the goodness-of-fit measures, performances of model considering single layer variables and model considering two layer variables were superior from the models that did not consider layering at all; but these models were comparable. Motor vehicle crashes (total and severe crashes) were classified as 'on-system' and 'off-system' crashes and two sub-models were fitted in order to calibrate the safety performance function for these crashes. On-system and off-system roads refer to two different roadway hierarchies. On-system or state maintained roads typically possess higher speed limit and carries traffic from distant TAZs. Off-system roads are, however, mostly local roads with relatively low speed limits. Due to these distinct characteristics, on-system crashes were modeled with only population and total employment variables of a zone in addition to the roadway and traffic variables; and all other zonal variables were disregarded. For off-system crashes, on contrary, all zonal variables was considered. It was evident by comparing this on- and off-system sub-model-framework to the other candidate models that it provided superior goodness-of-fit for both total and severe crashes.Based on the safety performance functions developed for pedestrian, bicycle, total and severe crashes, the study proposed a novel and complete framework for assessing safety (of these crash types) simultaneously in parallel with the four-step transportation planning process with no need of any additional data requirements from the practitioners' side.
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Date Issued: 2012
Identifier: CFE0004191, ucf:49009
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004191

Title: TRAFFIC CONFLICT ANALYSIS UNDER FOG CONDITIONS USING COMPUTER SIMULATION.
Creator: Zhang, Binya, Radwan, Essam, Abdel-Aty, Mohamed, Abou-Senna, Hatem, University of Central Florida
Abstract / Description: The weather condition is a crucial influence factor on road safety issues. Fog is one of the most noticeable weather conditions, which has a significant impact on traffic safety. Such condition reduces the road's visibility and consequently can affect drivers' vision, perception, and judgments. The statistical data shows that many crashes are directly or indirectly caused by the low-visibility weather condition. Hence, it is necessary for road traffic engineers to study the relationship of...
Show moreThe weather condition is a crucial influence factor on road safety issues. Fog is one of the most noticeable weather conditions, which has a significant impact on traffic safety. Such condition reduces the road's visibility and consequently can affect drivers' vision, perception, and judgments. The statistical data shows that many crashes are directly or indirectly caused by the low-visibility weather condition. Hence, it is necessary for road traffic engineers to study the relationship of road traffic accidents and their influence factors. Among these factors, the traffic volume and the speed limits in poor visibility areas are the primary reasons that can affect the types and occurring locations of road accidents.In this thesis, microscopic traffic simulation, through the use of VISSIM software, was used to study the road safety issue and its influencing factors due to limited visibility. A basic simulation model was built based on previously collected field data to simulate Interstate 4 (I-4)'s environment, geometry characteristics, and the basic traffic volume composition conditions. On the foundation of the basic simulation model, an experimental model was built to study the conflicts' types and distribution places under several different scenarios. Taking into consideration the entire 4-mile study area on I-4, this area was divided into 3 segments: section 1 with clear visibility, fog area of low visibility, and section 2 with clear visibility. Lower speed limits in the fog area, which were less than the limits in no-fog areas, were set to investigate the different speed limits' influence on the two main types of traffic conflicts: lane-change conflicts and rear-end conflicts. The experimental model generated several groups of traffic trajectory data files. The vehicle conflicts data were stored in these trajectory data files which, contains the conflict locations' coordinates, conflict time, time-to-conflict, and post-encroachment-time among other measures. The Surrogate Safety Assessment Model (SSAM), developed by the Federal Highway Administration, was applied to analyze these conflict data.From the analysis results, it is found that the traffic volume is an important factor, which has a large effect on the number of conflicts. The number of lane-change and rear-end conflicts increases along with the traffic volume growth. Another finding is that the difference between the speed limits in the fog area and in the no-fog areas is another significant factor that impacts the conflicts' frequency. Larger difference between the speed limits in two nearing road sections always leads to more accidents due to the inadequate reaction time for vehicle drivers to brake in time. And comparing to the scenarios that with the reduced speed limits in the low visibility zone, the condition that without the reduced speed limit has higher conflict number, which indicates that the it is necessary to put a lower speed limit in the fog zone which has a lower visibility. The results of this research have a certain reference value for studying the relationship between the road traffic conflicts and the impacts of different speed limits under fog condition. Overall, the findings of this research suggest follow up studies to further investigate possible relationships between conflicts as observed by simulation models and reported crashes in fog areas.
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Date Issued: 2015
Identifier: CFE0005747, ucf:50104
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005747

Traffic Safety (7)	+ -
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Driving Simulator (3)	+ -
Signalized Intersection (3)	+ -

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VISSIM (3)	+ -
fog (3)	+ -
Intelligent Transportation Systems (2)	+ -
Red-light Running (2)	+ -
Sight Distance (2)	+ -
Traffic Engineering (2)	+ -
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Unprotected Left-turn (2)	+ -
before and after (2)	+ -
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