This research develops an optimization model for eco-driving at signalized intersection. In urban areas, signalized intersections are the “hot spots” of air emissions and have significant negative environmental and health impacts. Eco-driving is a strategy which aims to reduce exclusive fuel consumption and emissions by modifying or optimizing drivers’ behaviors. With the help of vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure communication (V2I), eco-driving could utilize the signal phase and the queue-discharging time information to optimize the speed trajectories for the vehicles approaching an intersection in order to reduce fuel consumption and emissions. A few research studies have been conducted on the development of algorithms that utilize traffic signal information to reduce fuel consumption and emissions. Hence, the goal of this research is to develop an optimization model to determine the optimal eco-driving trajectory (the speed profile) at a signalized intersection, which aims to achieve the minimization of a linear combination of emissions and travel time. Then enumeration method, simplex optimization and genetic algorithm are investigated to determine a practicable and efficient method to solve the proposed optimization problem. As various scenarios of distance from the vehicle to the intersection, queue discharging time and weights of emission/travel time will lead to different optimal trajectories and different emissions and travel times. A sensitivity study is conducted to analyze and compare the performance of the optimal solution in various scenarios of different such parameters. In addition, a baseline study is conducted to investigate the benefits of eco-driving when drivers only decelerate in advance but not apply the recommended speed trajectory. The results of case study show that genetic algorithm is a preferred method to solve the proposed optimization problem; Eco-driving could achieve satisfied reduction in emissions without significantly increasing travel time and emissions is more sensitive to various scenarios than travel time; Eco-driving still could achieve reduction in emissions as long as the drivers decelerate earlier even though the they would not apply the recommended speed trajectory under certain conditions.

This dissertation analyzes two unsolved problems to fulfill the gap in the literature: (1). What is the vehicle delay and intersection capacity considering left-turn traffic at a pre-timed signal? (2). What are the mean and variance of delay to vehicles at a vehicle-actuated signal? The first part of this research evaluates the intersection performance in terms of capacity and delay at an isolated pre-timed signal intersection. Despite of a large body of literature on pre-timed signals, few work has examined the interactions be- tween left-turn and through vehicles. Usually a protected left-turn signal phase, before (leading) or after (lagging) through signal, is applied to a signalized inter- section when the traffic demand is relatively high. A common problem for leading left-turn operation is the blockage to left-turn vehicles by through traffic, particularly at an intersection with a short left-turn bay. During the peak hour, some vehicles on the through lane might not be able to depart at the end of a cycle, resulting in an increased probability of left-turn blockage. In turn, the blocked left-turn vehicles may also delay the through traffic to enter the intersection during the following cycle. Those problems may not exist for a lagging left-turn operation, since left-turn vehicles intend to spill out of the bay under heavy traffic. In this case, the through capacity is reduced, leading to an increase of total delay. All of these factors contribute to the difficulties of estimating the delay and capacity for an isolated intersection. In order to examine this missing part of study on the signalized intersection, two probabilistic models are proposed to deal with the left-turn bay blockage and queue spillback in a heuristic manner. Numerical case studies are also provided to test the proposed models. The second part of this research studies an isolated intersection with vehicle-actuated signal. Typically an advanced detector is located at a distance prior to the intersection such that an arriving vehicle triggers a green time extension in or- der to pass through without any stop. This extended time period actuated by the vehicle is called unit extension in this study. If no vehicle actuation occurs during a unit extension, the green phase would terminate in order to clear queues in other approaches. In this way, the actuated system dynamically allocates the green time among multiple approaches according to vehicle arrivals. And the unit extension is the only control parameter in this case. We develop a model to study the vehicle delay under a general arrival distribution with a given unit extension. Our model allows optimizing the intersection performance over the unit extension. The third part of this research applies graphical methods and diffusion approximations to the traffic signal problems. We reinterpret a graphical method which is originally proposed by Newell in order to directly measure the variance of the time for the queue clearance at a signalized intersection, which remains yet to be carefully examined in practice and would be rather challenging if only using the conventional queuing techniques. Our results demonstrate that graphical method explicitly presents both the deterministic and stochastic delay. We also illustrate that the theoretical background for the graphical methods in this particular application is inherently the diffusion approximation. Furthermore, we investigate the problems of disruptions occurred during a pre-timed traffic signal cycle. By diffusion approximation, we provide quantitative estimation on the duration that the effects of disruptions would dissipate.

The research analyzes the operating performance of three vehicle detection technologies for use in the City of Winnipeg. The technologies were: Autoscope Encore (video sensor), Iteris Vantage Edge2 (video sensor) and Matrix Wavetronix (microwave sensor). The sensors were tested in the tow eastbound lanes and two turning lanes on the intersection of Bishop Grandin Blvd and St.Mary's Road in Winnipeg, Manitoba. The research considered 24 weather, illumination, wind and traffic conditions. Testing and analysis was completed at the stop bar, and advance zone as well as for count performance. Sensitivity is a measure of the number of calls missed by the sensor. In terms of sensitivity, Iteris performed best overall, performing with greater sensitivity than Autoscope and Matrix in 17 of 24 conditions at the stop bar and outperforming in 11 of 12 conditions for advanced zone detection in this research. For count performance the Iteris had better accuracy when compared to ground truth established by Miovision Technologies, than Autoscope and Matrix.

The research analyzes the operating performance of three vehicle detection technologies for use in the City of Winnipeg. The technologies were: Autoscope Encore (video sensor), Iteris Vantage Edge2 (video sensor) and Matrix Wavetronix (microwave sensor). The sensors were tested in the tow eastbound lanes and two turning lanes on the intersection of Bishop Grandin Blvd and St.Mary's Road in Winnipeg, Manitoba. The research considered 24 weather, illumination, wind and traffic conditions. Testing and analysis was completed at the stop bar, and advance zone as well as for count performance. Sensitivity is a measure of the number of calls missed by the sensor. In terms of sensitivity, Iteris performed best overall, performing with greater sensitivity than Autoscope and Matrix in 17 of 24 conditions at the stop bar and outperforming in 11 of 12 conditions for advanced zone detection in this research. For count performance the Iteris had better accuracy when compared to ground truth established by Miovision Technologies, than Autoscope and Matrix.

Advance warning signals installed upstream of a high-speed signalized intersection (HSSI) warn motorists of impending signal changes in an effort to reduce the frequency of red-light running (RLR) and crashes. A new advance warning signal design was tested on an approach to an HSSI in Utah to study the effects of the modified design on motorist behavior. The new design utilized an overhead dynamic blank-out sign and flashers. A state-of-the-art digital wave radar evaluation system was installed at the study site to collect continuous data of vehicle speeds and RLR events by a non-intrusive method. Crash data were collected from the jurisdiction responsible for the study site and for an additional control intersection. Data were collected prior to, immediately after, and eight months after installation The blank-out overhead dynamic advance warning signal (BODAWS) system reduced RLR at the site during the time period immediately after installation. Eight months later, the number of RLR violations was slightly higher on one approach than before BODAWS system installation. Crash results showed that six months after BODAWS installation, the number of crashes declined at the study site. The number of crashes proportionately declined at the control intersection as well indicating a need to continue to evaluate and monitor changes. Mean vehicle speeds recorded before the onset of the yellow signal increased on the approaches to the study site immediately after BODAWS installation, and remained higher eight months later. Mean vehicle speeds recorded during the yellow signal, increased eight months after BODAWS installation to speeds higher than before the system was installed. Higher speeds during the yellow signal, combined with an increase in the number of RLR violations eight months after BODAWS installation, suggest that motorists may have begun to use the advance warning to speed up in an attempt to enter the intersection before the signal turned red. It is recommended that the lead flash time between activation of the BODAWS signs and flashers and the onset of the yellow signal should be adjusted so that motorists are not provided with more time than is necessary to safely clear the intersection.

As more and more trips increase in the decades, the conflicts between the participants are more and more frequent. The main topic of the thesis is to study the impact of the conflicts: the impacts of conflicts between right turn motor vehicles and pedestrians at signalized intersection. The study focus the impacts on urban area. In these areas, the conflicts between pedestrians and motor vehicles are particularly distinct. The situation thesis describes is: most of the signalized intersections whose signal for right-turn vehicle and pedestrian going through are at the same phase, thus unavoidably causes a lot of conflicts between pedestrians and motor vehicles during that time, and it also brings about a great chance of accidents as well. The behavior of motor vehicles drivers and pedestrians highly affects the how they will be conflicted. In addition, the impacts could be different with different flow of motor vehicle and pedestrians. In this process, gap acceptance of the pedestrian weighs a lot. And two models are used here to analyze the conflict. One is from the Swedish Capacity Manual and the other is from HCM 2010. In the thesis, a typical signalized intersection is chosen and the video are recorded to obtain data. The thesis discusses the differences of the two models, and some observed behaviors. And, according to the result, 500 pedestrian flow increase will bring 100 saturation flow rate decrease; and pedestrians flow at peak hour will increase travel time of motor vehicle over 100%. After that, some further studies and alternate methods are discussed.

No description available.

Advance warning signals (AWS) provide information warning drivers in advance of the end-of-green phase for an approaching signalized intersection. The purpose of this research was to develop guidelines for the placement of AWS in Utah, both conditions to evaluate the need for AWS installation and guidelines for the AWS system design. The conditions were based on literature of other transportation agencies that had similar AWS systems and were developed using the Policy Delphi method. The Policy Delphi method is the development of a specific policy area through the means of discussion by a committee of experts correlating views and information involving opportunity to react and assess different viewpoints until the committee is in agreement over the policies being recommended. Six conditions are recommended and discussed in detail, including: limited sight distance, posted speed, isolated intersection, high crash rate, approach grade, and heavy vehicle traffic volume. The guidelines for the AWS system design included details about three components: AWS component, advance detection component, and signal timing component. An evaluation matrix was developed by the Policy Delphi method for the purpose of evaluating and prioritizing a group of intersections for AWS installation. A total of 24 intersections were identified by the Utah Department of Transportation for this project that helped to develop and verify the conditions and evaluation matrix. The recommended guidelines and evaluation matrix results are described.

This study focuses on bicycle travel flow to prevent traffic accidents at non-signalized intersections. A bicycle's behavior can be characterized by various parameters, such as travel speed position, trajectory, acceleralion, and deceleration. The prevention of vehicle collisions with bicycles traveling at 10-15 km/h was regulated in the Advanced Emergency Braking System (AEBS) for passenger cars in regulation No. 152 of the World Forum for Harmonization of Vehicle Regulations in the United Nations. Therefore, it is essential to analyze the characteristics of bicycles in a reall trafflc environment to prevent traffic accidents involving cyclists. Meijer et. al. (2017) investigated bicycle behavior and charactericics using measurement devices installed on biccycles [1 ]. Ma et al. (2016) conducted a model of acceleration behavior on eleven cyclists using GPS data [2]. And it was pointed out that there was a need for modeling research for more cyclists.Hirose et al. (2021) examined bicycles' both travel speed and trajectory as bicycle travel flows based on data obtained from fixed-point observations at a non-signalized intersection in Tokyo, Japan [3]. This used fixed-point observalions to obtain raw data of bicycle travel flows in real traffic environment and reported various traffel speed, trajectory, and acceleration/deceleration patterns for bicycles entering intersections. The purpose of this study was to construct a model of bicycle travel flows based on fixed-point observations. It could simulate actual bicycle behaviors based on data that was obtained from measuring bicycle travel flows for 2828 cases from fixed-point observations. Furthermore, the data was divided into five patterns of bicycles entering intersections, and the accuracy of the model was evaluated for each pattern.

With the introduction of different forms of adaptive and actuated signal control, there is a need for effective evaluation tools that can capture the intricacies of real-life applications. While the current state-of-the-art analytical procedures provide simple approaches for estimating delay, queue length and stops at signalized intersections, they are limited in scope. Alternatively, several microscopic simulation softwares are currently available for the evaluation of signalized intersections. The objective of this dissertation is fourfold. First, it evaluates the consistency, accuracy, limitations and scope of the alternative analytical models. Second, it evaluates the validity of micro simulation results that evolve as an outcome of the car-following relationships. The validity of these models is demonstrated for idealized hypothetical examples where analytical solutions can be derived. Third, the dissertation expands the scope of current analytical models for the evaluation of oversaturated signalized intersections. Finally, the dissertation demonstrates the implications of using analytical models for the evaluation of real-life network and traffic configurations. This dissertation compared the delay estimates from numerous models for an undersaturated and oversaturated signalized intersection considering uniform and random arrivals in an attempt to systematically evaluate and demonstrate the assumptions and limitations of different delay estimation approaches. Specifically, the dissertation compared a theoretical vertical queuing analysis model, the queue-based models used in the 1994 and 2000 versions of the Highway Capacity Manual, the queue-based model in the 1995 Canadian Capacity Guide for Signalized Intersections, a theoretical horizontal queuing model derived from shock wave analysis, and the delay estimates produced by the INTEGRATION microscopic traffic simulation software. The results of the comparisons for uniform arrivals indicated that all delay models produced identical results under such traffic conditions, except for the estimates produced by the INTEGRATION software, which tended to estimate slightly higher delays than the other approaches. For the random arrivals, the results of the comparisons indicated that the delay estimates obtained by a micro-simulation model like INTEGRATION were consistent with the delay estimates computed by the analytical approaches. In addition, this dissertation compared the number of stops and the maximum extent of queue estimates using analytical procedures and the INTEGRATION simulation model for both undersaturated and oversaturated signalized intersections to assess their consistency and to analyze their applicability. For the number of stops estimates, it is found that there is a general agreement between the INTEGRATION microscopic simulation model and the analytical models for undersaturated signalized intersections. Both uniform and random arrivals demonstrated consistency between the INTEGRATION model and the analytical procedures; however, at a v/c ratio of 1.0 the analytical models underestimate the number of stops. The research developed an upper limit and a proposed model for estimating the number of vehicle stops for oversaturated conditions. It was demonstrated that the current state-of-the-practice analytical models can provide stop estimates that far exceed the upper bound. On the other hand, the INTEGRATION model was found to be consistent with the upper bound and demonstrated that the number of stops converge to 2.3 as the v/c ratio tends to 2.0. For the maximum extent of queue estimates, the estimated maximum extent of queue predicted from horizontal shock wave analysis was higher than the predictions from vertical deterministic queuing analysis. The horizontal shock wave model predicted lower maximum extent of queue than the CCG 1995 model. For oversaturated conditions, the vertical deterministic queuing model underestimated the maximum queue length. It was found that the CCG 1995 predictions were lower than those from the horizontal shock wave model. These differences were attributed to the fact that the CCG 1995 model estimates the remaining residual queue at the end of evaluation time. A consistency was found between the INTEGRATION model and the horizontal shock wave model predictions with respect to the maximum extent of queue for both undersaturated and oversaturated signalized intersections. Finally, the dissertation analyzed the impact of mixed traffic condition on the vehicle delay, person delay, and number of vehicle stops at a signalized intersection. The analysis considered approximating the mixed flow for equivalent homogeneous flows using two potential conversion factors. The first of these conversion factors was based on relative vehicle lengths while the second was based on relative vehicle riderships. The main conclusion of the analysis was that the optimum vehicle equivalency was dependent on the background level of congestion, the transit vehicle demand, and the Measure of Effectiveness (MOE) being considered. Consequently, explicit simulation of mixed flow is required in order to capture the unique vehicle interactions that result from mixed flow. Furthermore, while homogeneous flow approximations might be effective for some demand levels, these approximations are not consistently effective. / Ph. D.