Day-to-Day Evolution Model Based on Dynamic Reference Point with Heterogeneous Travelers
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Day-to-Day Evolution Model Based on Dynamic Reference Point with Heterogeneous Travelers Huijun Sun 1 & Si Zhang 1 & Linghui Han 2 & Xiaomei Zhao 1 & Lu Lou 1 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This paper investigates the implementation of a dynamic reference point scheme to capture traveler’s mental characteristics, with their day-to-day route choice behavior and heterogeneity. The traveler’s heterogeneity focuses on their different risk attitudes. On each day, travelers choose the routes based on their estimated travel costs, which can be affected by the reference point structure and its update. Most existing studies on the day-to-day traffic assignment models are proposed to capture day-to-day flow fluctuations through a learning model based on traveler’s past experience and information, but did not work on the consideration of gain and loss, which is described by the reference point scheme, comparing with traveler’s previous experience. This study aims to develop a day-to-day dynamic evolution model, in which travelers take on a tendency to refer to their previous travel experience as a reference when coping with different travel scenarios. First, the multi-class dynamic system is proposed to model traveler’s route choice behavior in a transportation network with two traveler classes. Then, the equilibrium state and stability of the evolution model is examined. We further investigate the classspecified update structure of the reference point. Finally, numerical experiments are presented to illustrate the application of our method. Keywords Traffic flow evolution . Dynamic reference point . Route choice .
Heterogeneous travelers
* Huijun Sun [email protected]
1
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, China
2
Shool of Maritime Economics and Management, Dalian Maritime University, Dalian, China
Sun H. et al.
1 Introduction Traffic assignment models have received continuous attention due to its strong applicability and can be divided into static equilibrium model and dynamic traffic assignment model (Li and Li 2017; Peeta and Ziliaskopoulos 2001; Waller et al. 2013; Chen et al. 2017). The static equilibrium model focuses on the final equilibrium state of the system, such as user equilibrium (UE) proposed by Wardrop (1952). After that, Stochastic user equilibrium (SUE) was developed to allow incomplete information or perception error when travelers make choice decisions. Equilibrium-based traffic assignment model implicitly contains an assumption that traffic flows on the road end up to be at their equilibrium values if the equilibrium state exists and is unique. This assumption is very idealistic, and the equilibrium state might not exist in the real world situation. Based on a dynamic route adjustment process, Horowitz (1984) found that even for a transportation system whose equilibrium was known to exist, the system might fail to reach it
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