•  
  •  
 

Journal of System Simulation

Abstract

Abstract: In order to alleviate urban road congestion and improve the traffic and environmental benefits at intersections, a multi-objective timing optimization model with total delay time, total number of stops, capacity, and total tailpipe emission at intersections as optimization objectives was developed. The model incorporated tailpipe emissions into a mathematical optimization model and quantified the mathematical relationship between traffic efficiency indicators and tailpipe emissions by constructing a specific power-based algorithm for measuring total tailpipe emissions. According to the intersection delay time and the number of stops, the total tailpipe emissions could be estimated. Both the NDX crossover operator and the shift-based density estimation (SDE) strategy were introduced to improve the design of the traditional NSGA-II algorithm, and the timing optimization model and the improved NSGA-II algorithm were coded to solve the multi-objective timing optimization model. The simulation results show that the error of the total tailpipe emission measurement model is less than 10%, and the convergence speed of the improved NSGA-II algorithm is improved by about 54% compared with the traditional NSGA-II algorithm.

First Page

2687

Last Page

2700

CLC

T391.9

Recommended Citation

Ding Xinhuan, Wang Huaqing, Dang Xu. Multi-objective Optimization of Signal Timing at Intersections Considering Tailpipe Emissions[J]. Journal of System Simulation, 2025, 37(10): 2687-2700.

Corresponding Author

Wang Huaqing

DOI

10.16182/j.issn1004731x.joss.24-0376

Download

Share

COinS