Transit Signal Priority Accommodating Conflicting Requests Under Connected Vehicles Technology

Significance Statement

The conventional transit signal priority CTSP bears several limitations which are impeding the roll-out of the technology. One major limitation it has is negative effects on competing travel direction. When traffic signal allocates more green time to the direction of transit bus, the traffic signal coordination on the competing direction is compromised, so does its traffic progression. During peak hours, the compromised progression can take hours to recover causing tremendous additional delay. The other limitation is using “first come first serve” strategy for multiple TSP requests, which not only does not benefit transits but also causes extra bus delay compared to not having CTSP.

Jia Hu and colleagues discussed a newly enhanced approach, the transit signal priority with connected vehicles conflicting requests TSPCV-CR with the aim of improving the CTSP by having wide-ranging features such as green re-allocation, simultaneous accommodation of multiple buses and traffic signal-transit cooperation. These features are designed to reduce the amount green time provided to transit and minimize the adverse effect on the competing travel direction. In addition, the design of having transits adjusting speed to minimize the change in traffic signal schedule presents a very interesting (probably the first) example of coordination between Connected Automated Vehicles (CAVs) and traffic signal control.

The TSPCV-CR formulates the problem into a binary mixed integer linear program BMILP and was solved by standard branch-and-bound routine. The tool is applicable to any isolated intersection. The research work is now published in the peer-reviewed journal, Transportation Research Part C.

The authors evaluated the proposed TSPCV-CR against two other control logic cases: conventional transit signal priority CTSP and no transit signal priority NTSP. Three different scenarios of conflicting requests were considered. The first involved two conflicting requests from opposite directions, followed by two conflicting requests from competing perpendicular directions and lastly three conflicting requests from three directions.

The evaluation results showed that the TSPCV-CR is effective in minimizing both bus delay and delay per person. The TSPCV-CR had a reduced delay of total buses by 44% and 50% compared to the conventional transit signal priority and no transit signal priority, respectively when observing conflicting request from opposite directions. Moreover, the TSPCV-CR also reduced bus delay up to 57%, showing a greater advantage over conventional transit signal priority. The TSPCV-CR is more effective for the two conflicting conditions, while it was also able to show clear advantages over conventional and no transit signal priority when receiving three conflicting requests.

The results offer a great platform for consideration of the TSPCV-CR technology within the near future. It also shows the potential of the coordination between Connected Automated Vehicles (CAVs) and signal control.

Transit Signal Priority Accommodating Conflicting Requests Under Connected Vehicles Technology - Advance in Engineering

About The Author

Young-Jae Lee is an Associate Professor of the Department of Transportation and Urban Infrastructure Studies at Morgan State University in Baltimore, Maryland. He received his B.S. and M.S. from the Seoul National University in Seoul, Korea in 1988 and 1990, respectively, and another M.S. and Ph.D. from the University of Pennsylvania for optimizing a transit network design problem in 1994 and 1998, respectively.

His main research focuses are the improvement of transit systems, intelligent transportation systems, optimizing transportation systems and traffic safety. He has conducted different types of research projects and published papers on improving public transportation systems, including network design, operational efficiency, and ITS application for public transportation. Dr. Lee has published over 60 research reports, journal and conference papers.

Currently he is a committee member of the Transportation Research Board (a division of the National Academies) Automated Transit Systems (AP040), an associate editor of the Korea Society of Civil Engineering (KSCE) Journal of Civil Engineering, and an associate editor of the Urban Rail Transit.

About The Author

Brian Park is an Associate Professor of Civil and Environmental Engineering Department at the University of Virginia. Prior to joining the University of Virginia, he was a Research Fellow at the National Institute of Statistical Sciences and a Post-Doctoral Research Associate at North Carolina State University. Dr. Park received the B.S. and the M.S. from the Hanyang University, Seoul, Korea, in 1993 and 1995, respectively, and the Ph.D. from the Texas A&M University in 1998.

Dr. Park is a recipient of PTV America Best Paper Award, Outstanding Reviewer Award from the American Society of Civil Engineers, Jack H. Dillard Outstanding Paper Award from the Virginia Transportation Research Council and Charley V. Wootan Award (for best Ph.D. dissertation) from the Council of University Transportation Centers. He is an ASCE ExCEEd teaching fellow.

He is an Editor in Chief of the International Journal of Transportation, an Associate Editor of the American Society of Civil Engineers Journal of Transportation Engineering, Journal of Intelligent Transportation Systems and the KSCE Journal of Civil Engineering, and an editorial board member of the International Journal of Sustainable Transportation. Furthermore, he is a member of TRB (a division of the National Academies) Vehicle Highway Automation Committee and Artificial Intelligence and Advanced Computing Applications Committee, and chair of Simulation subcommittee of Traffic Signal Systems Committee. He is also Chair of Advanced Technologies Committee of ASCE Transportation and Development Institute.

Dr. Park has published over 120 journal and conference papers in the area of transportation system operations and managements, and intelligent transportation system. His research interests include cyber-physical system for transportation, stochastic optimization, connected and automated vehicle safety assessment, microscopic simulation model application, and transportation system sustainability.

About The Author

Jia Hu works as a research associate at the Federal Highway Administration (FHWA). He graduated with a Ph.D. degree from the University of Virginia. He received his Master degree in transportation engineering from the North Carolina State University. He holds a BS degree in structure engineering from Zhejiang University.

Dr. Hu is a recipient of Best Scientific Paper-Americas Award from the ITS World Congress, Research Associateship Award from the National Academy of Sciences, and Academic Excellence Award from the University of Virginia.

He is an Associate Editor of the American Society of Civil Engineers Journal of Transportation Engineering and an editorial board member of the International Journal of Transportation. Furthermore, he is a member of TRB (a division of the National Academies) Vehicle Highway Automation Committee and Simulation subcommittee of Traffic Signal Systems Committee. He is also Chair of Vehicle Automation and Connectivity Committee of the World Transport Convention.

Dr. Hu has published over 40 journal and conference papers in the area of vehicle automation, transportation system operations and managements, and intelligent transportation system. His research interests include connected and automated vehicles, microscopic simulation model application, system optimization, and transportation system sustainability.

Reference

Jia Hu1 , Byungkyu Brian Park2, Young-Jae Lee3 . Transit Signal Priority Accommodating Conflicting Requests Under Connected Vehicles Technology, Transport Research Part C 69 (2016) 173-192.

Show Affiliations

1 Turner Fairbank Highway Research Center, Federal Highway Administration, United States

2 Department of Civil and Environmental Engineering, University of Virginia, P.O. Box 400742, Charlottesville, VA 22904-4742, United States

3 Department of Transportation and Urban Infrastructure Studies, Morgan State University, 1700 E. Cold Spring Lane, Baltimore, MD 21251, United States.

 

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