Multiagent Routing Simulation with Partial Smart Vehicles Penetration

Bogumił Kamiński,Atefeh Mashatan,Przemysław Szufel,Łukasz Kraiński,Paweł Prałat

doi:10.1155/2020/3152020

Bogumił Kamiński, Atefeh Mashatan + Show 3 more

Open Access

https://doi.org/10.1155/2020/3152020

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Abstract

The invention and implementation of smart connected cars will change the way how the transportation networks in cities around the world operate. This technological shift will not happen instantaneously—for many years, both human-driven and smart connected vehicles will coexist. In this paper, using a multiagent simulation framework, we model a complex urban transportation system that involves heterogeneous participants. Vehicles are assigned into two groups: the first one consists of smart cars and the second one involves regular ones. Vehicles in the former group are capable of rerouting in response to changes in the observed traffic while regular ones rely on historical information only. The goal of the paper is to analyze the effect of changing smart cars penetration on system characteristics, in particular, the total travelling time. The smart car routing algorithm proposed in this paper reduced travelling time up to 30%. Analysis has shown that the behaviour of the system and optimal configuration of underlying algorithms change dynamically with smart vehicles penetration level.

Highlights

Due to an increasing number of traffic participants, especially in urban areas, the current transportation infrastructure becomes insufficient
In order to fill the gap in the related work, we have developed novel microscopic simulation framework for assessing Traffic Management Systems under varying smart vehicles penetration level
We proposed centralized Traffic Management Systems (TMS) based on the k-shortest path algorithm and conducted experiments using the framework. e experiments have shown that the proposed service can significantly reduce the travelling time in urban environment

Summary

Introduction

Due to an increasing number of traffic participants, especially in urban areas, the current transportation infrastructure becomes insufficient. Traffic Management Systems (TMS) effectively increasing road network efficiency are in high demand. A theoretical design assumes implementation of the system within Vehicular Ad Hoc Network (VANET) consisted of three main components: in-vehicle On-Board Units (OBU) embedded with sensors, processing units and wireless interfaces, Road Side Units (RSU) creating communication infrastructure, and Traffic Management Center providing centralized processing power and storage [15]. Taking the above described factors into account, in this paper we test how the increasing adoption of smart cars, which can adaptively update their routing decisions using information obtained from a TMS, influences the expected congestion and total travelling time of commuters. Discrete-event based approach was reported in earlier research to produce more accurate results compared to standard discrete-time simulations due to character of numerical calculations [42]

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