Integrated Network Transport Simulator to Evaluate Transport Policy for Reduction of Carbon Dioxide Emission

• Okushima, Masashi

Abstract

Not only purchase of electric vehicle but also modal shift from vehicle traffic should be promoted for reduction of greenhouse gas emission. Effect of transport policies for reduction of carbon dioxide emission should be estimated properly with simulating vehicle traffic on a target road network. For the purpose, it is aimed that the integrated network transport simulator is developed based on the multi-agent simulation model to evaluate transport policies for reduction of CO2 emission in the present study. The proposed integrated network transport simulator consists of the vehicle traffic simulation model, the travel mode choice model and the vehicle choice model. CO2 emission is estimated with the vehicle traffic simulation model. The decision processes of the vehicle choice and the travel mode choice are respectively described considering with the social interaction. It is assumed that not only the conformity effect but also non-conformity effect should be considered as the social influence. Therefore, hierarchical Bayesian modeling is applied to describe the vehicle choice and the travel mode choice considering with heterogeneity and social interaction. The model parameters are estimated with the database of questionnaire survey in a local city of Japan and the proposed simulator is applied to estimate the effect of the carbon tax. The reduction of carbon dioxide emission as the effect of the policies is estimated using the proposed integrated network transport simulator. From the view point of CO2 emission, it can be found that the effect of reducing CO2 emissions with only the carbon tax is limited since the spread of low emission vehicles is hindered and the rate of sustainable transport mode goes down, although the EV will be popularized.

Journal

• Transportation Research Procedia

  Transportation Research Procedia 34 283-290, 2018-12-04

  Elsevier

Keywords

• greenhouse gas emission
• multi-agent simulation
• hierarchical Bayesian modeling
• carbon tax

Details

• CRID: 1050851242902596736
• NII Article ID: 120007042445
• ISSN: 23521465
• DOI: 10.1016/j.trpro.2018.11.043
• Web Site: http://repo.lib.tokushima-u.ac.jp/115818
• Web Site: https://api.elsevier.com/content/article/PII:S2352146518303326?httpAccept=text/xml
• Web Site: https://api.elsevier.com/content/article/PII:S2352146518303326?httpAccept=text/plain
• Text Lang: en
• Article Type: journal article
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