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
Changzhou city , algebraic method , Pareto optimisation , comprehensive modal emission model , microscopic emission simulation platform , traffic emission reduction , Pareto solutions , signal processing , multiobjective genetic algorithm , CMEM , arrival-departure curves , air pollution control , algebra , VISSIM , real-world traffic data , optimal signal coordination scheme , genetic algorithms , microscopic multimodal traffic flow simulation model
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