Analyzing Efficiency Of Different Snow Removal Strategies in terms of The System Wide Time Savings Using Dynamic Link Capacity In Large-Scale Microsimulation

被引：5

作者：

Soloveva, Valentina ^{[1
,2
]}

Kuchinskaya, Elena ^{[1
]}

Antonov, Nikita ^{[2
]}

Volotskiy, Timofey ^{[1
,2
]}

机构：

[1] ITMO Univ, Kronverkskiy Pr 49, St Petersburg 197101, Russia

[2] OTSLAB, 13 Liniya VO 44b, St Petersburg 191784, Russia

来源：

9TH INTERNATIONAL YOUNG SCIENTISTS CONFERENCE IN COMPUTATIONAL SCIENCE, YSC2020 | 2020年 / 178卷

基金：

俄罗斯科学基金会;

关键词：

Snow removal strategy; vehicle routing problem; microsimulation; dynamic link capacity;

D O I：

10.1016/j.procs.2020.11.013

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we address the problem of removal of the snow from the urban streets and propose a way to assess different snow removal strategies in terms of travelers' benefits. We use multi-agent approach to simulate the effects of the snowfall and the corresponding reduction of road link capacity and free flow speed on the travel times in the full-day dynamic. We then introduce the snow removal vehicles (SRVs) in the simulation and analyze different routing and task scheduling strategies of the road cleaning from the user benefit perspective. MATSim framework is used to simulate dynamic capacity and free speed changes and the Jsprit extension is used solve the routing problem for SRVs. Tests on a transport model of the city of Kronstadt have shown the ability of the proposed method to assess and compare snow removal strategies and to fmd an optimal one. Traffic and passenger delays due to snowfall and snow removal were calculated and compared. (C) 2020 The Authors. Published by Elsevier B.V.

引用

页码：116 / 124

页数：9