A Group-Based Signal Timing Optimization Model Considering Safety for Signalized Intersections with Mixed Traffic Flows

Author:

Wang Fen1ORCID,Tang Keshuang2ORCID,Li Keping2,Liu Zhigang1,Zhu Lin1

Affiliation:

1. School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, China

2. Department of Traffic Engineering, Tongji University, Shanghai, China

Abstract

The conventional stage-based signal control approach with uniform phase structure has been dominantly applied at signalized intersections in China. However, this approach cannot efficiently handle mixed traffic flows with unbalanced volumes. Moreover, this signal control approach has resulted in many safety issues, such as traffic conflicts (a) between the right-turning motorized vehicles and the straight-through bicycles and (b) at the change of phases due to bicycles’ clearance failure. Hence, the objective of this paper is to propose a group-based signal optimization model that considers both safety and delay for the intersections with mixed traffic flows. In the proposed model, safety was evaluated based on the traffic conflicts during the inter-green period and was incorporated into the signal timing procedure. A probabilistic approach was developed to estimate the probability of occurrence of conflicts, with a novel safety indicator combining postencroachment time and kinetic energy for measuring conflict severity. The average delay per person, according to the Highway Capacity Manual 2010 method, was adopted in this paper. Then, the multiobjective optimization issue was formulated as a nonlinear program and solved by a Nondominated Sorting Genetic Algorithm. A numerical study was performed to demonstrate the applicability and performance of the proposed model. Results indicated that the proposed model can provide an effective tool for researchers and practitioners to simultaneously optimize traffic safety and efficiency in signal planning. It may also overcome the disadvantages of most of the conventional models, which are incapable of quantifying safety in the optimization process.

Funder

National Key Research and Development Plan of China

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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