Traffic responsive plan selection (TRPS) control is considered an effective operational mode in traffic signal systems. Its efficiency stems from the fact that it can capture variations in traffic patterns and switch timing plans based on existing traffic conditions. Most of the research performed to date has focused on either small traffic networks-with up to five intersections-or theoretical networks. Past research has also focused on the threshold mechanism implemented in the National Electrical Manufacturers Association (NEMA) traffic controllers. There is very limited research on the pattern-matching mechanism implemented in the 170 controllers. This report documents a new approach to generating traffic scenarios for large networks, addressing issues such as the unequal traffic distribution and the large combination of traffic movements from multiple intersections. This approach is based on the selection of significant critical movements controlling the network using statistical correlation analysis of actual detector data and the use of synthetic origin-destination analysis of the entire network. The proposed approach was applied in the design of the traffic responsive control mode for the Reston Parkway arterial network, which has 14 intersections. Detector data were used to validate the results of the proposed approach. The validation process showed that the traffic system was correctly modeled and sufficiently represented by the proposed approach. Multi-objective optimization was used to generate the final timing plans and the TRPS pattern-matching parameters. Simulation analysis revealed that implementation of the traffic responsive control mode in the Reston Parkway network can achieve an average delay reduction of 27 percent and an average stops reduction of 14 percent on weekends and an average delay reduction of 18 percent and an average stops reduction of 21 percent on regular week days. The methodology documented in this report should be followed to implement TRPS control on large arterials in an optimal and stable manner. Optimal and stable operation of TRPS could significantly reduce congestion while capitalizing on existing traffic control infrastructure with a 46:1 benefit-cost ratio.

This dissertation develops and evaluates a new adaptive traffic signal control system for arterials. This control system is based on reinforcement learning, which is an important research area in distributed artificial intelligence and has been extensively used in many applications including real-time control. In this dissertation, a systematic comparison between the reinforcement learning control methods and existing adaptive traffic control methods is first presented from the theoretical perspective. This comparison shows both the connections between them and the benefits of using reinforcement learning. A Neural-Fuzzy Actor-Critic Reinforcement Learning (NFACRL) method is then introduced for traffic signal control. NFACRL integrates fuzzy logic and neural networks into reinforcement learning and can better handle the curse of dimensionality and generalization problems associated with ordinary reinforcement learning methods. This NFACRL method is first applied to isolated intersection control. Two different implementation schemes are considered. The first scheme uses a fixed phase sequence and variable cycle length, while the second one optimizes phase sequence in real time and is not constrained to the concept of cycle. Both schemes are further extended for arterial control, with each intersection being controlled by one NFACRL controller. Different strategies used for coordinating reinforcement learning controllers are reviewed, and a simple but robust method is adopted for coordinating traffic signals along the arterial. The proposed NFACRL control system is tested at both isolated intersection and arterial levels based on VISSIM simulation. The testing is conducted under different traffic volume scenarios using real-world traffic data collected during morning, noon, and afternoon peak periods. The performance of the NFACRL control system is compared with that of the optimized pre-timed and actuated control. Testing results based on VISSIM simulation show that the proposed NFACRL control has very promising performance. It outperforms optimized pre-timed and actuated control in most cases for both isolated intersection and arterial control. At the end of this dissertation, issues on how to further improve the NFACRL method and implement it in real world are discussed.

Under congested conditions, the road traffic states of different arterial links will interact with each other; therefore, it is necessary to understand the behavior of traffic corridors and to investigate corridor-wide traffic coordinated control strategies. In order to achieve this, traffic flow models are applied in signal control to predict future traffic states. Optimization tools are used to search for the best sequence of future control decisions, based on predictions by traffic flow models. A number of model-based adaptive control strategies have been presented in the literature and have been proved effective in practice. However, most studies have modeled the traffic dynamic either at a link-based level or at an individual movement-based level. Moreover, the efficiency of corridor-wide coordination algorithms for congested large-scale networks still needs to be further improved. A hierarchical control structure is developed to divide the complex control problem into different control layers: the highest level optimizes the cycle length, the mid layer optimizes the offsets, and the Model Predictive Control (MPC) procedure is implemented in the lowest layer to optimize the split. In addition, there is an extra multi-modal priority control layer to provide priority for different travel modes. Firstly, MPC is applied to optimize the signal timing plans for arterial traffic. The objectives are to increase the throughput. A hybrid urban traffic flow model is proposed to provide relatively accurate predictions of the traffic state dynamic, which is capable of simulating queue evolutions among different lane groups in a specific link. Secondly, this study expands the dynamic queue concept to the corridor-wide coordination problem. The ideal offset and boundary offsets to avoid spillback and starvation are found based on the shockwave profiles at each signalized intersection. A new multi-objective optimization model based on the preemptive goal programming is proposed to find the optimal offset. Thirdly, the priority control problem is formulated into a multi-objective optimization model, which is solved with a Non-dominated Sorting Genetic Algorithm. Pareto-optimal front results are presented to evaluate the trade-off among different objectives and the most appropriate solution is chosen with high-level information. Performance of the new adaptive controller is verified with software-in-the-loop simulation. The applied simulation environment contains VISSIM with the ASC/3 module as the simulation environment and the control system as the solver. The simulation test bed includes two arterial corridors in Edmonton, Alberta. The simulation network was well calibrated and validated. The simulation results show that the proposed adaptive control methods outperform actuated control in increasing throughput, decreasing delay, and preventing queue spillback.

"TRB's National Cooperative Highway Research Program (NCHRP) Report 741: Evaluation of Methodologies for Visual Impact Assessments evaluates visual impact assessment (VIA) procedures, methods, and practices that satisfy or exceed National Environmental Policy Act (NEPA) and other requirements. The report documents VIA methodologies and approaches used in the United States and other countries, describes the decision making framework used to select specific VIA techniques for a given project, includes VIA best practice case studies from state departments of transportation, and highlights promising new developments in the field."--pub. desc.

Guidelines for enhancing suburban mobility: Overview and summary of findings -- Suburban transit services: The planning context -- Actions to modify and improve the overall suburban transit framework -- Circulators and shuttles -- Subscription buses and vanpools -- Summary: Lessons and conclusions -- Bibliography -- Appendix A: Classifying suburban environments.

TCRP Report 94: Fare Policies, Structures and Technologies: Update identifies, describes, and evaluates key fare structures, policies, and technologies that are being considered by transit agencies, with a focus on their impact on customers, operations management, and effective and equitable fare integration. The report includes data on fare structures, policy-making procedures, and ongoing efforts to implement fare technology. This report provides guidance on making decisions related to fare policies, structures, and technologies. It includes practical information that can be readily used by transit professionals and policy makers in fare-related planning and decision making. This report updates information presented in TCRP Reports 10 and 32 and presents the latest developments and research results related to fare policy and technology issues.