Modeling Concurrent Day-to-Day Departure Time and Route Choices With Multiple Micro-Preferences

Jingyi Hao,Dongyang Xia,Wenyi Zhang,Shixiong Jiang,Zhao Kou

doi:10.1109/access.2020.3034873

Abstract

Day-to-day traffic dynamics is to model the day-to-day evolution of travelers' travel choices, which helps to understand the aggregate traffic evolution of a non-equilibrium network and then develop scientific managements. This topic is attracting increasing interests. In the literature, day-to-day route and departure time choices are usually addressed separately; and the existing models commonly adhere to the rational behavior adjustment criterion (RBAC), but pay little attention to extra behavior preferences. In this article, we formulate the day-to-day departure time and route choices in a united model. Moreover, besides the RBAC, three microscopic behavior preferences (i.e., simplicity-seeking, proximity-prone and marginal cost preference) are suggested for modeling. The problem is formulated as a discrete-time dynamics named by the day-to-day departure time and route adjustment process (DTRAP). Basic properties of the model are verified theoretically; and numerical results indicate that the suggested micro-preferences have significant impact on traffic evolution. Thus, serious treatment and more in-depth research attention need to be laid on these micro-preferences for obtaining scientific understanding on the day-to-day network traffic evolution or for avoiding ineffective (or even wrong) traffic managements.

Highlights

The urban transportation network is open, which can sustain disturbances, such as accidents, traffic controls, bad weather, and work zones
Guo et al [43] reformulated the proportionalswitch adjustment process (PAP) model [4] and the network tatonnement process [19] to look into the day-to-day evolution of departure time choices with bounded rationality at a single bottleneck; and reported that the doubly dynamics models may lead to instability, even if their stable states are equivalent to the bounded rational user equilibrium
MICROSCOPIC BEHAVIOR PREFERENCES In existing day-to-day traffic dynamics, travelers are assumed to adjust travel choices according to rational behavior adjustment criterion (RBAC), i.e., travelers can only adjust to less costly options

Summary

INTRODUCTION

The urban transportation network is open, which can sustain disturbances, such as accidents, traffic controls, bad weather, and work zones. Guo et al [43] reformulated the PAP model [4] and the network tatonnement process [19] to look into the day-to-day evolution of departure time choices with bounded rationality at a single bottleneck; and reported that the doubly dynamics models may lead to instability, even if their stable states are equivalent to the bounded rational user equilibrium. In existing path-based deterministic day-to-day dynamics models, the route and departure time choices are usually addressed separately These models commonly adhere to the rational behavior adjustment criterion (RBAC) [24] stating that travelers can only swap onto less costly objective choices, but pay little attention to other behavior preferences, such as the simplicity-seeking, proximity-prone and marginal cost preference suggested in this article.

MICROSCOPIC BEHAVIOR PREFERENCES

THEORETICAL ANALYSES

SUFFICIENCY

EXPERIMENTAL DESIGNATION

CONCLUSION AND FUTURE RESEARCH