Stable day-to-day dynamics for departure time choice

TL;DR

This paper introduces a stable day-to-day dynamical system for drivers' departure time choices at a bottleneck, using a traffic model based on scheduling payoff dynamics, and proves its stability and effectiveness through numerical examples.

Contribution

The paper develops a novel stable dynamical model for departure time choice based on scheduling payoff principles, integrating the LWR model and proving its stability.

Findings

The model converges to a stable equilibrium state.

The approach effectively captures drivers' scheduling behavior.

Numerical examples demonstrate model stability and applicability.

Abstract

In this paper we present a stable day-to-day dynamical system for drivers' departure time choice at a single bottleneck. We first define within-day traffic dynamics with the point queue model, costs, the departure time user equilibrium (DTUE), and the arrival time user equilibrium (ATUE). We then identify three behavioral principles: (i) Drivers choose their departure and arrival times in a backward fashion (backward choice principle); (ii) After choosing the arrival times, they update their departure times to balance the total costs (cost balancing principle); (iii) They choose their arrival times to reduce their scheduling costs or gain their scheduling payoffs (scheduling cost reducing or scheduling payoff gaining principle). In this sense, drivers' departure and arrival time choices are driven by their scheduling payoff choice. With a single tube or imaginary road model, we convert the nonlocal day-to-day arrival time shifting problem to a local scheduling payoff shifting problem. After introducing a new variable for the imaginary density, we apply the Lighthill-Whitham-Richards (LWR) model to describe the day-to-day dynamics of scheduling payoff choice and present splitting and cost balancing schemes to determine arrival and departure flow-rates accordingly. We also develop the corresponding discrete models for numerical solutions. We theoretically prove that the day-to-day stationary state of the LWR model leads to the scheduling payoff user equilibrium (SPUE), which is equivalent to both DTUE and ATUE and stable. We use one numerical example to demonstrate the effectiveness and stability of the new day-to-day dynamical model.