Safe and efficient traffic control remains a challenging task with the continued increase in the number of vehicles, especially in urban areas. This manuscript focuses on traffic control at intersections, since urban roads with closely spaced intersections are often prone to queue spillbacks, which disrupt traffic flows across the entire network and increase congestion. While various intelligent traffic control solutions exist for autonomous systems, they are not applicable to or ineffective against human-operated vehicles or mixed traffic. On the other hand, existing approaches to manage intersections with human-operated vehicles, cannot adequately adjust to dynamic traffic conditions. This manuscript presents a technology-agnostic adaptive real-time server based approach to dynamically determine signal timings at an intersection based on changing traffic conditions and queue lengths (i.e., wait times) to minimize, if not eliminate, spillbacks without unnecessarily increasing delays associated with intersection crossings. We also provide timeliness guarantee bounds by analyzing the travel time delays, hence making our approach more dependable and predictable. The proposed approach was validated in simulations and on a realistic hardware testbed with robots mimicking human driving behaviors. Compared to the pre-timed traffic control and an adaptive scheduling based traffic control, our algorithm is able to avoid spillbacks under highly dynamic traffic conditions and improve the average crossing delay in most cases by 10--50 %. / Master of Science / Safe and efficient traffic control remains a challenging task with the continued increase in the number of vehicles, especially in urban areas. This manuscript focuses on traffic control at intersections, since urban roads with closely spaced intersections are often prone to congestion that blocks other intersection upstream, which disrupt traffic flows across the entire network. While various intelligent traffic control solutions exist for autonomous systems, they are not applicable to or ineffective against human-operated vehicles or mixed traffic. On the other hand, existing approaches to manage intersections with human-operated vehicles, cannot adequately adjust to dynamic traffic conditions. This work presents a technologyagnostic adaptive approach to dynamically determine signal timings at an intersection based on changing traffic conditions and queue lengths (i.e., wait times) to minimize, if not eliminate, spillbacks without unnecessarily increasing delays associated with intersection crossings. We also provide theoretical bounds to guarantee the performance of our approach in terms of the travel delays that may incur on the vehicles in the system, hence making our approach more dependable and predictable. The proposed approach was validated in simulations and on a realistic hardware testbed which uses robots to mimic human driving behaviour in an urban environment. Comparisons with widely deployed and state-of-the-art traffic control techniques show that our approach is able to minimize spillbacks as well as improve on the average crossing delay in most cases.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/89670 |
| Date | 31 May 2019 |
| Creators | Oza, Pratham Rajan |
| Contributors | Electrical and Computer Engineering, Chantem, Thidapat, Gerdes, Ryan M., Paul, JoAnn |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0023 seconds