Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Simulating social influences on sustainable mobility shifts for heterogeneous agents
Abstract Greenhouse gas emissions by vehicle traffic should be reduced not only through innovations in automotive technology but also through a modal shift to sustainable transport. The modal shift to sustainable transport corresponding to the transport policy, as well as the purchase of clean energy vehicles (CEV) is regarded as the mobility shift. Therefore, both service improvement for sustainable transport modes, such as the bus rapid transit system, and economic incentive policies are considered in transport policy. Conversely, as the local community influences decisions on mobility shift, the estimation of $ CO_{2} $ emissions should describe local interaction. Particularly, heterogeneity of local interaction should be described in the modeling of the mobility shift. Therefore, the mobility shift is modeled to incorporate heterogeneity and local interaction to estimate the effect of transport policies in reducing $ CO_{2} $ emissions. The research question is how much do heterogeneity and local interaction influence mobility shift with the policy for sustainable transport. A multi-agent mobility shift simulation model that considers heterogeneity and local interaction is developed. For this purpose, the stated preference for mode change and purchase CEV policies is investigated via a questionnaire survey. The proposed multi-agent simulation model includes the decision process of the agent regarding mobility shift, the social influence process in the social network, and the $ CO_{2} $ emission process. The decision process for commuting mode is modeled using the hierarchical Bayesian method mainly to describe the heterogeneity of the influence of the local mode share. The day-to-day dynamics of commuting mode choice and the purchase of CEVs corresponding to the transport policy are estimated using the proposed multi-agent simulation model. The results confirm that the heterogeneity of influence on social conformity should be considered in the modeling of modal shift as both conformity effects and non-conformity effects are observed. However, the assumption of homogeneous commuters might cause estimates that are too high, since the heterogeneity of commuters decreases the share of the sustainable transport mode. Furthermore, the green tax policy is confirmed to be suitable for maximizing the reduction rate of $ CO_{2} $ emissions, as pricing based on fuel consumption maximizes reduction efficiency.
Simulating social influences on sustainable mobility shifts for heterogeneous agents
Abstract Greenhouse gas emissions by vehicle traffic should be reduced not only through innovations in automotive technology but also through a modal shift to sustainable transport. The modal shift to sustainable transport corresponding to the transport policy, as well as the purchase of clean energy vehicles (CEV) is regarded as the mobility shift. Therefore, both service improvement for sustainable transport modes, such as the bus rapid transit system, and economic incentive policies are considered in transport policy. Conversely, as the local community influences decisions on mobility shift, the estimation of $ CO_{2} $ emissions should describe local interaction. Particularly, heterogeneity of local interaction should be described in the modeling of the mobility shift. Therefore, the mobility shift is modeled to incorporate heterogeneity and local interaction to estimate the effect of transport policies in reducing $ CO_{2} $ emissions. The research question is how much do heterogeneity and local interaction influence mobility shift with the policy for sustainable transport. A multi-agent mobility shift simulation model that considers heterogeneity and local interaction is developed. For this purpose, the stated preference for mode change and purchase CEV policies is investigated via a questionnaire survey. The proposed multi-agent simulation model includes the decision process of the agent regarding mobility shift, the social influence process in the social network, and the $ CO_{2} $ emission process. The decision process for commuting mode is modeled using the hierarchical Bayesian method mainly to describe the heterogeneity of the influence of the local mode share. The day-to-day dynamics of commuting mode choice and the purchase of CEVs corresponding to the transport policy are estimated using the proposed multi-agent simulation model. The results confirm that the heterogeneity of influence on social conformity should be considered in the modeling of modal shift as both conformity effects and non-conformity effects are observed. However, the assumption of homogeneous commuters might cause estimates that are too high, since the heterogeneity of commuters decreases the share of the sustainable transport mode. Furthermore, the green tax policy is confirmed to be suitable for maximizing the reduction rate of $ CO_{2} $ emissions, as pricing based on fuel consumption maximizes reduction efficiency.
Simulating social influences on sustainable mobility shifts for heterogeneous agents
Okushima, Masashi (Autor:in)
Transportation ; 42
2015
Aufsatz (Zeitschrift)
Englisch
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