Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction

The dynamic paths planning problem of emergency vehicles is usually constrained by the factors including time efficiency, resources requirement, and reliability of the road network. Therefore, a two-stage model of dynamic paths planning of emergency vehicles is built with the goal of the shortest tr...

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Main Authors: Jiandong Zhao, Yujie Guo, Xiaohong Duan
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2017/9184891
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spelling doaj-e76d92de1069484ba4a24a35f8005ca02020-11-24T21:25:47ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952017-01-01201710.1155/2017/91848919184891Dynamic Path Planning of Emergency Vehicles Based on Travel Time PredictionJiandong Zhao0Yujie Guo1Xiaohong Duan2School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, ChinaThe dynamic paths planning problem of emergency vehicles is usually constrained by the factors including time efficiency, resources requirement, and reliability of the road network. Therefore, a two-stage model of dynamic paths planning of emergency vehicles is built with the goal of the shortest travel time and the minimum degree of traffic congestion. Firstly, according to the dynamic characteristics of road network traffic, a polyline-shaped speed function is constructed. And then, based on the real-time and historical data of travel speed, a new kernel clustering algorithm based on shuffled frog leaping algorithm is designed to predict the travel time. Secondly, combined with the expected travel time, the traffic congestion index is defined to measure the reliability of the route. Thirdly, aimed at the problem of solving two-stage target model, a two-stage shortest path algorithm is proposed, which is composed of K-paths algorithm and shuffled frog leaping algorithm. Finally, based on the data of floating vehicles of expressway in Beijing, a simulation case is used to verify the above methods. The results show that the optimization path algorithm meets the needs of the multiple constraints.http://dx.doi.org/10.1155/2017/9184891
collection DOAJ
language English
format Article
sources DOAJ
author Jiandong Zhao
Yujie Guo
Xiaohong Duan
spellingShingle Jiandong Zhao
Yujie Guo
Xiaohong Duan
Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
Journal of Advanced Transportation
author_facet Jiandong Zhao
Yujie Guo
Xiaohong Duan
author_sort Jiandong Zhao
title Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
title_short Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
title_full Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
title_fullStr Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
title_full_unstemmed Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction
title_sort dynamic path planning of emergency vehicles based on travel time prediction
publisher Hindawi-Wiley
series Journal of Advanced Transportation
issn 0197-6729
2042-3195
publishDate 2017-01-01
description The dynamic paths planning problem of emergency vehicles is usually constrained by the factors including time efficiency, resources requirement, and reliability of the road network. Therefore, a two-stage model of dynamic paths planning of emergency vehicles is built with the goal of the shortest travel time and the minimum degree of traffic congestion. Firstly, according to the dynamic characteristics of road network traffic, a polyline-shaped speed function is constructed. And then, based on the real-time and historical data of travel speed, a new kernel clustering algorithm based on shuffled frog leaping algorithm is designed to predict the travel time. Secondly, combined with the expected travel time, the traffic congestion index is defined to measure the reliability of the route. Thirdly, aimed at the problem of solving two-stage target model, a two-stage shortest path algorithm is proposed, which is composed of K-paths algorithm and shuffled frog leaping algorithm. Finally, based on the data of floating vehicles of expressway in Beijing, a simulation case is used to verify the above methods. The results show that the optimization path algorithm meets the needs of the multiple constraints.
url http://dx.doi.org/10.1155/2017/9184891
work_keys_str_mv AT jiandongzhao dynamicpathplanningofemergencyvehiclesbasedontraveltimeprediction
AT yujieguo dynamicpathplanningofemergencyvehiclesbasedontraveltimeprediction
AT xiaohongduan dynamicpathplanningofemergencyvehiclesbasedontraveltimeprediction
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