Signal coordination scheme based on traffic emission. Issue 2 (1st March 2016)

• Record Type: Journal Article
• Authors: Ji, Yanjie; Hu, Bo; Hill, Graeme; Guo, Weihong; Blythe, Phil; Gao, Liangpeng
• Is Part Of: IET intelligent transport systems. Volume 10:Issue 2(2016)
• Page Start: 89
• Page End: 96
• Publication Date: 2016-03-01
• Subjects: signal processing -- air pollution control -- genetic algorithms -- algebra -- Pareto optimisation; optimal signal coordination scheme -- algebraic method -- arrival‐departure curves -- microscopic emission simulation platform -- VISSIM -- microscopic multimodal traffic flow simulation model -- traffic emission reduction -- multiobjective genetic algorithm -- comprehensive modal emission model -- CMEM -- Pareto solutions -- real‐world traffic data -- Changzhou city; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2014.0255
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : 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.