This study presents a new optimal signal coordination scheme with an emphasis on emission reduction as a result of minimised passenger delay. By analysing the limitation of the algebraic method, a new algorithm using arrival–departure curves was proposed. A microscopic emission simulation platform based on VISSIM (a microscopic multi‐modal traffic flow simulation model) and comprehensive modal emission model (CMEM) was established to estimate traffic emission reduction. A multi‐objective genetic algorithm was used to find Pareto solutions that simultaneously reduce both passenger delay and vehicle emissions. Using the real‐world traffic data collected in Changzhou city, an example of the signal coordination scheme was developed and its impact on emissions was simulated in the VISSIM‐CMEM platform. The simulation results show that the proposed scheme achieved an average emission reduction of 28.8% on public transport vehicles and 18.7% on all vehicles over existing signal schemes.
Signal coordination scheme based on traffic emission
IET Intelligent Transport Systems ; 10 , 2 ; 89-96
2016-03-01
8 pages
Article (Journal)
Electronic Resource
English
CMEM , comprehensive modal emission model , genetic algorithms , arrival‐departure curves , microscopic emission simulation platform , algebraic method , algebra , Pareto optimisation , VISSIM , Changzhou city , real‐world traffic data , optimal signal coordination scheme , microscopic multimodal traffic flow simulation model , multiobjective genetic algorithm , signal processing , traffic emission reduction , Pareto solutions , air pollution control
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