T3e Webinar Overview

Signal Timing Optimization Using Connected Vehicle Technology

Date: Monday, August 13, 2018
Time: 1:00 PM – 2:00 PM ET
Cost: All T3e webinars are free of charge.
PDH: 1.0 View PDH Policy

T3e Webinars are brought to you by the Intelligent Transportation Systems (ITS) Professional Capacity Building Program (PCB) of the U.S. Department of Transportation’s (U.S. DOT) ITS Joint Program Office (JPO). The purpose of this webinar series is to provide a platform for students to share their research findings. References in this webinar to any specific commercial products, processes, or services, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the U.S. DOT.


Traffic signals serve as a major source of congestion in urban environments and are considered large contributors to travel delays, vehicle emissions, and wasted fuel. Recent advances in vehicular communications and mobile computing technologies are offering flexible traffic signal control paradigms. For example, new communication technologies now allow vehicles to collect and share information about their surroundings with adjacent vehicles and infrastructure, which can be used to change signal timings more dynamically than previously possible. Furthermore, the introduction of autonomous vehicles means that vehicles and signals can work in cooperation to improve signalized intersection operations.

This presentation introduces a real-time traffic signal optimization algorithm in the presence of Connected and Autonomous Vehicles (CAVs). It leverages information from CAVs arriving to the intersection to identify the existence of some non-Connected Vehicles. Signal timings are then selected to optimize the sequence at which these CAVs and identified non-Connected Vehicles are allowed to discharge through the intersection to minimize total vehicle delay. Furthermore, longitudinal trajectory guidance that explicitly accounts for vehicle acceleration and deceleration behavior is provided to Autonomous Vehicles to minimize the total number of stopping maneuvers performed by all vehicles. This algorithm results in a reduction of average vehicle delay by almost half when penetration ratio of Connected Vehicles is more than 40 percent and a decrease in number of stops by up to 30 percent with high market penetration ratio of Autonomous Vehicles. A platoon-based algorithm further reduces computation effort by identifying naturally occurring platoons, considering departure sequence of platoons instead of individual vehicles, and designing trajectories only for the lead Autonomous Vehicle in any platoon.

Learning Objectives

The audience will learn about:

  • Identifying non-connected vehicles using data from Connected Vehicles
  • Grouping vehicles into platoons that naturally discharge together
  • Optimizing platoon discharge sequence to minimize vehicle delays
  • Altering vehicle trajectories to minimize number of stops
  • Examining trade-off between computational complexity and operational performance

Target Audience

The target audience includes anyone interested in urban traffic signal control, CAV technology, and an effective and efficient traffic signal control method utilizing CAV technology.


Dr. S. Ilgin Guler, Assistant Professor, Department of Civil & Environmental Engineering, The Pennsylvania State University
S. Ilgin Guler Dr. S. Ilgin Guler is an assistant professor in the Department of Civil and Environmental Engineering. Her research interests include multi-modal urban traffic operations and control, intelligent transportation systems, connected and autonomous vehicles, and infrastructure management. Dr. Guler received dual B.S. degrees from Bogazici University, Istanbul, Turkey in Civil Engineering and Industrial Engineering and Operations Research. She received her M.S. and Ph.D. degrees from the University of California, Berkeley in Civil and Environmental Engineering. After completing her Ph.D., she served as a post-doctoral scholar in the Institute of Transport Systems and Planning at ETH Zurich, Switzerland. Dr. Guler has over 7 years of research, teaching, and industry experience on traffic operations. Dr. Guler has been the primary author of multiple research proposals funded by institutions such as the Pennsylvania DOT, South Dakota DOT, Swiss National Science Foundation, and Swiss Association of Road Transportation Experts. She is currently serving as the Penn State PI on NCHRP 17-84: Pedestrian and Bicycle Safety Performance Functions for the Highway Safety Manual.

Dr. Guler’s research has resulted in 20 peer-refereed journal articles and 28 refereed conference proceedings on topics that include multi-modal traffic safety, multi-modal traffic operations, and multi-modal traffic control. Dr. Guler serves as the major research advisor for Ph.D., Master’s, and undergraduate students. She teaches courses on Highway Engineering, Traffic Operations, Public Transportation, and Infrastructure Systems Management. Dr. Guler is the winner of the 2018 Fred Burggraf Award for the Best Paper in Transportation Research Record, the Journal of the Transportation Research Board of the National Academies. Dr. Guler serves as an active member of the Transportation Research Board’s Traffic Flow Theory and Characteristics committee (AHB 45) and serves on the Editorial Board of Transportation Research Part C.

Dr. Vikash V. Gayah, Assistant Professor, Department of Civil & Environmental Engineering, The Pennsylvania State University
Vikash V. Gayah Dr. Vikash V. Gayah is an assistant professor in the Department of Civil and Environmental Engineering. He received his B.S. and M.S. degrees from the University of Central Florida and his Ph.D. degree from the University of California, Berkeley. Dr. Gayah’s research focuses on urban mobility, traffic operations, traffic flow theory, public transportation, and traffic safety. His research approach includes a combination of analytical models, micro-simulations, and empirical analysis of transportation data. He has authored over 45 peer-reviewed journal articles, over 50 refereed conference proceedings, and numerous research reports to sponsors. Dr. Gayah currently serves as an editorial advisory board member of two leading transportation journals, Transportation Research Part B: Methodological and Transportation Research Part C: Emerging Technologies. He is an associate editor for the IEEE Intelligent Transportation Systems Magazine (an international peer-reviewed journal) and is a member of the Transportation Research Board’s Committee on Traffic Flow Theory and Characteristics (AHB 45). He has been recognized with multiple awards, including: the Dwight D. Eisenhower Transportation Fellowship, Gordon F. Newell Award for Excellence in Transportation Science, University of California Transportation Center Student of the Year Award, New Faculty Award by the Council of University Transportation Centers, the Cunard, Fred Burggraf and D. Grant Mickle outstanding paper awards by the Transportation Research Board, Harry West Teaching Award by the Department of Civil and Environmental Engineering at Penn State, and CAREER Award by the National Science Foundation.


Xiao (Joyce) Liang, Ph.D. candidate in Civil Engineering, The Pennsylvania State University
Joyce Liang Ms. Xiao (Joyce) Liang joined the research group of Dr. Vikash Gayah and Dr. Ilgin Guler’s in the Department of Civil & Environmental Engineering at Pennsylvania State University as a Ph.D. student in August 2016. She received her BEng (Hons) in Electrical Engineering and BBA (Hons) in Management at The Hong Kong Polytechnic University. Her research focuses on traffic signal control optimization utilizing connected and autonomous vehicle technology. She has published one journal paper and one conference paper, with another conference paper under review and another manuscript in preparation. Ms. Liang is the winner of the Graduate Excellence Fellowship in 2016, awarded by Penn State College of Engineering.


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