Project Summary
The objective of this project is to develop optimal signal control strategies in urban networks based on Cell Transmission Model. Traffic in urban networks is getting more and more congested due to the rapid increase in travel demand. Most of the prevailing signal control strategies are developed for uncongested traffic conditions and cannot work properly when traffic gets congested during peak periods. Furthermore, most of them either consider average vehicle arrival rates or model vehicles as queues, and thus, they fail to capture important traffic flow characteristics such as kinematic waves and fundamental speed-density (or flow-density) relations on a road link. To tackle these problems, in this project, we introduce the cell transmission model (CTM) to simulate the evolution patterns of vehicles on a road link. Due to the complexity in the time-discrete control signals at signalized intersections, we develop time-continuous junction models which can correctly approximate the discrete junction outflows under different traffic conditions, capacity constraints, and signal settings. For CTM with the continuous approximate models, we formulate a nonlinear optimal control problem, in which signal settings (green splits) are control variables, and the network flow-rate in the macroscopic fundamental diagram is the objective function. This project provides a systematical framework to determine optimal signal settings for urban networks. Insights from this project can help engineers and policy makers better understand of how the signal settings, route choices, and demand patterns impact the network performance.
