Differentiable road pricing for environment-oriented electric vehicle and gasoline vehicle users in the bi-objective transportation network

ABSTRACT

The environmental traffic assignment problem in the bimodal network with electric vehicles (EVs) and gasoline vehicles (GVs) has become a hot topic recently. However, few previous works consider the psychological difference between EV users and GV users in terms of environmental awareness , in order to fill in this research gap, we formulate an environment-oriented mixed-behavior user equilibrium (EMUE) model to distinguish the route choice criterion between EV users and GV users by considering the Pro-environmental behavior (PEB) of EV users. . We formulate a bi-objective optimization model and propose a differentiable road pricing scheme for EV and GV users to manage the congestion and emissions simultaneously. We investigate whether the differentiable road pricing can decentralize the Pareto-efficient flow as a unique mixed-behavior equilibrium. Moreover, we conduct numerical experiments based on the Sioux Falls network and the existing urban network in Qianhai Zone to evaluate the effectiveness of the proposed pricing scheme, models and algorithms.

KEYWORDS:

• Electric vehicle (ev)
• gasoline vehicle (gv)
• environmental awareness
• differentiable road pricing
• environment-oriented mixed-behavior
• pareto-efficient

Acknowledgments

The authors wish to give thanks to Shenzhen Urban Transport Planning Center (SUTPC) for providing the software and data.

Data Availability

The data used to support the findings of this study are included within the supplementary information file(s). Moreover, if anyone needs the data in this paper, you can contact [email protected]

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supporting Information

S1 Codes. Code-QH.rsc

S2 Input OD of Qianhai. OD Qianhai.txt

S3 Map and street information of Qianhai. Map.rar