Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 1054570, 12 pages
Research Article

Biobjective Optimization and Evaluation for Transit Signal Priority Strategies at Bus Stop-to-Stop Segment

1College of Civil and Transportation Engineering, Hohai University, Xi Kang Road 1, Nanjing 210098, China
2Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, CoRE 613, 96 Frelinghuysen Road, Piscataway, NJ 08854-8018, USA
3School of Transportation, Southeast University, Si Pai Lou 2, Nanjing 210096, China

Received 7 January 2016; Revised 23 April 2016; Accepted 26 April 2016

Academic Editor: M. I. Herreros

Copyright © 2016 Rui Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a new optimization framework for the transit signal priority strategies in terms of green extension, red truncation, and phase insertion at the stop-to-stop segment of bus lines. The optimization objective is to minimize both passenger delay and the deviation from bus schedule simultaneously. The objective functions are defined with respect to the segment between bus stops, which can include the adjacent signalized intersections and downstream bus stops. The transit priority signal timing is optimized by using a biobjective optimization framework considering both the total delay at a segment and the delay deviation from the arrival schedules at bus stops. The proposed framework is evaluated using a VISSIM model calibrated with field traffic volume and traffic signal data of Caochangmen Boulevard in Nanjing, China. The optimized TSP-based phasing plans result in the reduced delay and improved reliability, compared with the non-TSP scenario under the different traffic flow conditions in the morning peak hour. The evaluation results indicate the promising performance of the proposed optimization framework in reducing the passenger delay and improving the bus schedule adherence for the urban transit system.