Continuum Dynamic Traffic Assignment Model for Autonomous Vehicles in a Polycentric Urban City with Environmental Consideration

Bosheng Rong,Hui Zhao,Cuiping Zhang,Shujie Cui

doi:10.1155/2018/8345979

Abstract

This paper proposed a continuum dynamic model for autonomous vehicles in a polycentric urban city by considering the environment impact of traffic emission. The model assumes that homogeneous autonomous vehicles are continuously distributed over the urban areas which tend to choose a path to minimize their total travel cost from origin to destination. To describe the path choice behavior of travelers, we presented the continuum dynamic traffic assignment model which consists of a two-dimensional hyperbolic system of nonlinear conservation laws with source terms and an Eikonal-type equation. The elastic demand is considered using a function which associating each copy of flow with its total instantaneous travel cost. For the environmental impacts, here we consider the influence of CO emission and include the cost of emission into the actual transportation cost. A solution algorithm for the model is designed as a cell-centered finite volume method for conservation law equations and a fast sweeping method for Eikonal-type equations on unstructured grids. Numerical examples are given to demonstrate the model and the proposed solution algorithm. Further, the results of the travel cost considering CO emissions and not considering CO emissions are compared.

Highlights

Air pollution has a serious negative effect in many cities, such as Beijing, Tianjin, and Shenzhen, which brings great adverse effects on people’s health
We develop a continuum dynamic traffic assignment (DTA) model with elastic demand for autonomous vehicles in an urban city where the city has multiple compact central business districts (CBDs)
We develop DTA model including the cost of vehicle CO emission for a polycentric urban city to investigate the characteristics of urban traffic flow and the path selection behavior of heterogeneous autonomous vehicles in a continuous network in order to achieve the lowest travel costs, in the case where people are environmentally conscious and intentionally want to reduce vehicle exhaust emissions (CO is mainly)

Summary

Introduction

Air pollution has a serious negative effect in many cities, such as Beijing, Tianjin, and Shenzhen, which brings great adverse effects on people’s health. Compared with discrete or microscopic modeling methods, continuum modeling methods require less data to build the model, so the problem scale of large transportation networks is reduced, thereby saving computing time and memory There is another class of models we used in the paper, which is elastic demand model. We develop a continuum DTA model with elastic demand for autonomous vehicles in an urban city where the city has multiple compact central business districts (CBDs). In this model, the CO emission costs are considered in the travel cost.

Problem Formulation

Solution Procedure

Numerical Experiments

Conclusions