Abstract

As an interesting research topic in transportation field, tradable credit scheme (TCS) has been extensively explored in the latest decade. Existing studies implicitly assumed that travelers are clear about the equilibrium credit price and make their trips accordingly. However, this may not be the case in reality, since the credit price is endogenously determined by the credit-trading behavior, especially in the early stages after the implementation of a TCS. Considering travelers’ uncertainty on the equilibrium credit price, this paper aims to investigate the impacts of perception error on credit price and how to accommodate such errors by an appropriate scheme design. Transferring the perception error on credit price to a given and fixed value released by central authority, we first investigate the impacts of recommended credit price under a given TCS. The numerical results imply that it is necessary to simultaneously consider the choice of recommended credit price and charging scheme in TCS design. Regarding this, we combine the goals of social welfare and public acceptance of the scheme and propose a bilevel biobjective programming (BLBOP) model, by which the net economic benefit is maximized while the gap between the recommended and realized credit prices is minimized. Through two numerical examples, it is found that the rise in perception variance could intensify the contradiction effect between the two objectives. Additionally, a nonnegligible price gap must be allowed to occur to maintain the effectiveness of a TCS.

Highlights

  • Congestion, mainly attributed to the imbalance between supply of the transportation system and traffic demand, is becoming an increasingly disturbing problem worldwide

  • A perception error on the credit price is assumed to exist among travelers, which enhances realism in characterizing travel behaviors under tradable credit scheme (TCS). ird, we propose a bilevel biobjective programming model for optimal design of TCS, in which minimizing the gap between the recommended price and the realized one is incorporated to enhancing the public acceptance of the proposed scheme

  • On the other hand, when the objective of minimizing the price gap is ignored in the TCS design, the maximized economic benefit is still lower than EBSO regardless of the perception variance. is highlights the fact that the negative effect of perception error in terms of credit price cannot be entirely accommodated, even though we focus merely on the social welfare

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Summary

Introduction

Congestion, mainly attributed to the imbalance between supply of the transportation system and traffic demand, is becoming an increasingly disturbing problem worldwide. In a TCS, the central authority initially issues credits to all eligible travelers, and the latter needs to consume them when using the road section with credit charge Such a credit scheme has three major advantages over the monetary toll charge. It provides a framework for solving the congestion problem without increasing travelers’ travel costs. Ird, we propose a bilevel biobjective programming model for optimal design of TCS, in which minimizing the gap between the recommended price and the realized one is incorporated to enhancing the public acceptance of the proposed scheme.

Problem Statement
Probit-Based Stochastic User Equilibrium under a Tradable Credit Scheme
Origin
Optimal Design of Credit Charging Scheme with Recommended Unit Credit Price
Numerical Analysis
Findings
Concluding Remarks and Future Research
Full Text
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