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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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2017/9184891 |
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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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1725982752243712000 |