The development of connected and automated vehicle (CAV) technologies motivate modeling efforts and studies to understand CAVs' collective behaviors on public roads. In this thesis, we study CAV traffic flows through macroscopic models under two mathematical frameworks: the nonlocal conservation laws and the mean field games.The nonlocal conservation law models incorporate traffic information in a nonlocal range into each vehicle's driving control. We study one such model with a finite spatial nonlocal range, and demonstrate that proper use of the nonlocal information will offer better traffic stability. We also discuss numerical computation of the model that is robust under the changes of the nonlocal range. The mean field game models consider strategic interactions between CAVs, assuming each vehicle anticipates future traffic conditions and plans its driving control to minimize a predefined driving cost. A systematic approach is developed to derive the model, solve the model, and test the equilibrium solution. We take this approach in several traffic scenarios for CAVs on a single road or on a network, and demonstrate that proper design of the CAV driving cost function can lead to more efficient and stable traffic flows than human traffics. The established results in the thesis will bring more mathematical understandings on the proposed and studied models. The results may also provide insights on how to utilize the vehicle connectivity and automation to improve the overall traffic, and help to the CAV driving algorithm design.

This thesis describes the design and implementation of a traffic generator that can simulate the traffic of tens of thousands of networking devices from a given traffic model. It is designed to handle traffic models created with Unified Traffic Modelling. The traffic generator is then evaluated and different solutions are compared in an effort to find the best solution for each issue. This thesis is meant to serve as a guideline for future development of traffic generators by providing insight into the problems faced during the development of one.

The dissertation presents a connected vehicle based traffic signal control model (CVTSCM) for signalized arterials. The model addresses different levels of traffic congestion starting with the initial deployment of connected vehicle technologies focusing on two modules created in CVTSCM. For near/under-saturated intersections, an arterial-level traffic progression optimization model (ALTPOM) is being proposed. ALTPOM improves traffic progression by optimizing offsets for an entire signalized arterial simultaneously. To optimize these offsets, splits of coordinated intersections are first adjusted to balance predicted upcoming demands of all approaches at individual intersections. An open source traffic simulator was selected to implement and evaluate the performance of ALTPOM. The case studies’ field signal timing plans were coordinated and optimized using TRANSYT-7F as the benchmark. ALTPOM was implemented with connected vehicles penetration rates at 25% and 50%, ALTPOM significantly outperforms TRANSYT-7F with at least 26.0% reduction of control delay (sec/vehicle) and a 4.4% increase of throughput for both directions of major and minor streets. This technique differs from traditional traffic coordination which prioritizes major street traffic, and thereby generally results in degrading performance on minor streets. ALTPOM also provides smooth traffic progression for the coordinated direction with little impact on the opposite direction. The performance of ALTPOM improves as the penetration rate of connected vehicles increases. For saturated/oversaturated conditions, two queue length management based Active Traffic Management (ATM) strategies are proposed, analytically investigated, and experimentally validated. The first strategy distributes as much green time as possible for approaches with higher saturation discharge rate in order to reduce delay. For the second approach, green times are allocated to balance queue lengths of major and minor streets preventing queue spillback or gridlock. Both strategies were formulated initially using uniform arrival and departure, and then validated using field vehicle trajectory data. After validation of the modules, the effectiveness of CVTSCM is proven. Then, conclusions and recommendations for future researches are presented at the end.

This thesis presents a collection of network optimization strategies aimed at aiding the local practitioner in selecting, implementing, and evaluating appropriate strategies to achieve community goals and objectives in the urban environment. The urban environment is often challenging due to the plethora of activity and variety in mode choice. Growing interest in sustainable transportation practices along with encouragement at the Federal, State, and Local levels to is leading to the growing use of non-motorized modes of transportation such as walking and bicycling. The combination of high population density and mixed land use in the urban environment creates unique safety and operational challenges. This research presents a synthesis of strategies designed to improve local transportation safety and efficiency by targeting speeding and cut-through volumes as improving pedestrian and bicycle facilities in urban areas such as those found in Western Massachusetts. Additionally, this research evaluates two local network optimization strategies; speed cushions and reverse angle parking. The effectiveness of the speed cushions in achieving the community’s goal of reducing speeds was evaluated and determined to be a recommended strategy for future implementation, especially when couple with enforcement. Reverse angle parking, however, was not determined to be an effective strategy due to the high occurrence of events as well as lower parking volume exhibited during implementation.

This research effort first characterizes the trucks traveling along US highways by analyzing data from Interstate 81. It is hypothesized that I-81 is typical of US highways and thus can provide some insight into typical truck characteristics. These truck characteristics are important for the development of an exhaustive vehicle performance procedure. Analysis was done based on data collected at the Troutville weigh station. The characterization involves an analysis of vehicle class distribution, GVW (Gross Vehicle Weight) distribution, vehicle volume distribution, Average Weight on Tractive Axle (AWTA), and typical weight-to-power ratios. The thesis then assembles a database of systematic field data that can be utilized for the validation of vehicle performance models. This database is unique because it was conducted in a controlled field environment where the vehicle is only constrained by its dynamics. Using the assembled field database, a simple constant power vehicle dynamics model for estimating maximum vehicle acceleration levels based on a vehicle's tractive effort and aerodynamic, rolling, and grade resistance forces was tested and validated. In addition, typical model input parameters for different vehicle, pavement, and tire characteristics are included in the thesis. The model was found to predict vehicle speeds at the conclusion of the travel along the section to within 5 km/h (3.1 mi/h) of field measurements, thus demonstrating the validity and applicability of the model. Finally, the research effort introduces the concept of variable power in order to enhance current state-of-the-art vehicle dynamics models and capture the build-up of power as a vehicle engages in gearshifts at low travel speeds. The proposed enhancement to the current state-of-practice vehicle dynamics model allows the model to reflect typical vehicle acceleration behavior more accurately. Subsequently, the model parameters are calibrated using field measurements along a test roadway facility. / Master of Science

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. 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.

The scope of this study was to evaluate the impact of the air traffic controller-to-pilot communication standard known as CPDLC or Data-Communication on the future air traffic operations. The impact was evaluated from the double viewpoint of airport delays and air traffic controllers' workload. RAMS simulation software is used to perform all the runs and from its output data the values of terminal area delays and controllers workload are obtained. The New York Metroplex terminal area was used as a case study. Because of its complexity, where three major airports (i.e. JFK, Newark, and La Guardia) interact and constraint each other, this area was particularly interesting to be studied and the data analyzed gave a valuable insight on the possible future impact of Data-Communication in congested terminal areas. The results of the study, based on some previous man-in-the-loop simulations performed by the FAA in the nineties, showed that significant potential benefits could be obtained with the complete implementation of such technologies in the workload experienced by air traffic controllers. Moreover some small but not negligible benefits were obtained in the total delays accrued by each airport studied. On the other hand, the simulations of the future demand predicted by the FAA demonstrated that without a significant increment in capacity or limitation on the traffic growth intolerable delays would be recorded across the NAS in the future. For the complexity of the simulation model calibration and for the very time-consuming run time not all the scenarios described in the methodology were tested, demonstrating the weakness of RAMS as a ground simulation model. / Master of Science

High-speed transmission over contemporary communication networks has drawn many research efforts. Traffic scheduling schemes which play a critical role in managing network transmission have been pervasively studied and widely implemented in various practical communication networks. In a sophisticated communication system, a variety of applications co-exist and require differentiated Quality-of-Service (QoS). Innovative scheduling schemes and hybrid scheduling disciplines which integrate multiple traditional scheduling mechanisms have emerged for QoS differentiation. This study aims to develop novel analytical models for commonly interested scheduling schemes in communication systems under more realistic network traffic and use the models to investigate the issues of design and development of traffic scheduling schemes. In the open literature, it is commonly recognized that network traffic exhibits self-similar nature, which has serious impact on the performance of communication networks and protocols. To have a deep study of self-similar traffic, the real-world traffic datasets are measured and evaluated in this study. The results reveal that selfsimilar traffic is a ubiquitous phenomenon in high-speed communication networks and highlight the importance of the developed analytical models under self-similar traffic. The original analytical models are then developed for the centralized scheduling schemes including the Deficit Round Robin, the hybrid PQGPS which integrates the traditional Priority Queueing (PQ) and Generalized Processor Sharing (GPS) schemes, and the Automatic Repeat reQuest (ARQ) forward error control discipline in the presence of self-similar traffic. Most recently, research on the innovative Cognitive Radio (CR) techniques in wireless networks is popular. However, most of the existing analytical models still employ the traditional Poisson traffic to examine the performance of CR involved systems. In addition, few studies have been reported for estimating the residual service left by primary users. Instead, extensive existing studies use an ON/OFF source to model the residual service regardless of the primary traffic. In this thesis, a PQ theory is adopted to investigate and model the possible service left by selfsimilar primary traffic and derive the queue length distribution of individual secondary users under the distributed spectrum random access protocol.

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The flow of traffic at an intersection is often controlled by a traffic signal. This research report models a T-intersection with a disjoint network for each direction of traffic flow, eastbound, westbound and southbound. The traffic signal is modeled with a fourth network. Three types of signal control (pretimed, semi-actuated and full-actuated) are modeled to examine the effect of each type on the average delay time and average length of queues for each lane of traffic queue at the intersection. The computer models presented in the report use SLAM computer language to simulate the traffic signal and vehicle flow.