Estimation of real-time travel times on arterial streets has been a challenging task due to the intersection control delay as well as bottleneck delay from the downstream link. Therefore, few transportation professionals have conducted research at utilizing the dynamic flow methods to estimate travel times on arterial street networks. This thesis is to develop dynamic flow algorithms that estimates the real-time travel time on an arterial street network by utilizing the traffic information obtained from detectors. A modified method to the one adopted in HCM2000 in computing the intersection control delay is developed and utilized to estimate the real-time travel time for a short-time interval update under non-incident and incident situations. Simulation model is developed in CORSIM to validate developed algorithms under different traffic situations. / Master of Science

Assuming that vehicle connectivity technology matures and connected vehicles hit the market, many of the running vehicles will be equipped with highly sophisticated sensors and communication hardware. Along with the goal of eliminating human distracted driving and increasing vehicle automation, it is necessary to develop novel intersection control strategies. Accordingly, the research presented in this dissertation develops an innovative system that controls the movement of vehicles using cooperative cruise control system (CACC) capabilities entitled: iCACC (intersection management using CACC). In the iCACC system, the main assumption is that the intersection controller receives vehicle requests from vehicles and advises each vehicle on the optimum course of action by ensuring no crashes occur while at the same time minimizing the intersection delay. In addition, an innovative framework has been developed (APP framework) using the iCACC platform to prioritize the movements of vehicles based on the number of passengers in the vehicle. Using CACC and vehicle-to-infrastructure connectivity, the system was also applied to a single-lane roundabout. In general terms, this application is considered quite similar to the concept of metering single-lane entrance ramps. The proposed iCACC system was tested and compared to three other intersection control strategies, namely: traffic signal control, an all-way stop control (AWSC), and a roundabout, considering different traffic demand levels ranging from low to high levels of congestion (volume-to-capacity ration from 0.2 to 0.9). The simulated results showed savings in delay and fuel consumption in the order of 90 to 45 %, respectively compared to AWSC and traffic signal control. Delays for the roundabout and the iCACC controller were comparable. The simulation results showed that fuel consumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuel consumption for the traffic signal, AWSC and roundabout control strategies, respectively. In summary, the developed iCACC system is an innovative system because of its ability to optimize/model different levels of vehicle automation market penetrations, weather conditions, vehicle classes/models, shared movements, roundabouts, and passenger priority. In addition, the iCACC is capable of capturing the heterogeneity of roadway users (cyclists, pedestrians, etc.) using a video detection technique developed in this dissertation effort. It is anticipated that the research findings will contribute to the application of automated systems, connected vehicle technology, and the future of driverless vehicle management. Finally, the public acceptability of the new advanced in-vehicle technologies is a challenging task and this research will provide valuable feedback for researchers, automobile manufacturers, and decision makers in making the case to introduce such systems. / Ph. D.

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