On Designing Near-Optimum Paths on Weighted Regions for an Intelligent Vehicle

On Designing Near-Optimum Paths on Weighted Regions for an Intelligent Vehicle This paper describes an approach for designing a (near-)optimum path for an intelligent vehicle which is moving in an urban environment cluttered with weighted regions. The vehicle is requested to move from its depot, passing through a predefined set of customers and return back to its depot. In the proposed approach, first, using an image of the Urban environment, we apply the A- star algorithm in order to construct a distance matrix between the depot and the customers and between the customers. Then, a Genetic Algorithm with special encoding is used to search for a near-optimum solution. The objective consists of designing a (near-)optimum path for an intelligent vehicle so that all the customers are served as soon as possible while simultaneously respects the kinematical constraints of the vehicle and the linked constraints of the customers e.g. the time windows. The efficiency of the developed method is investigated and discussed through characteristic simulated experiments concerning a variety of operating weighted regions. . . . . Keywords Urban environment Weighted regions Near-optimum paths Intelligent transportation systems Intelligent vehicle 1 Introduction vehicles which they should deliver products to a set of customers. Nowadays, there have been increasing concern about the rapid http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Transportation Systems Research Springer Journals

On Designing Near-Optimum Paths on Weighted Regions for an Intelligent Vehicle

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Electrical Engineering; Automotive Engineering; Robotics and Automation; Computer Imaging, Vision, Pattern Recognition and Graphics; Civil Engineering; User Interfaces and Human Computer Interaction
ISSN
1348-8503
eISSN
1868-8659
D.O.I.
10.1007/s13177-018-0159-5
Publisher site
See Article on Publisher Site

Abstract

This paper describes an approach for designing a (near-)optimum path for an intelligent vehicle which is moving in an urban environment cluttered with weighted regions. The vehicle is requested to move from its depot, passing through a predefined set of customers and return back to its depot. In the proposed approach, first, using an image of the Urban environment, we apply the A- star algorithm in order to construct a distance matrix between the depot and the customers and between the customers. Then, a Genetic Algorithm with special encoding is used to search for a near-optimum solution. The objective consists of designing a (near-)optimum path for an intelligent vehicle so that all the customers are served as soon as possible while simultaneously respects the kinematical constraints of the vehicle and the linked constraints of the customers e.g. the time windows. The efficiency of the developed method is investigated and discussed through characteristic simulated experiments concerning a variety of operating weighted regions. . . . . Keywords Urban environment Weighted regions Near-optimum paths Intelligent transportation systems Intelligent vehicle 1 Introduction vehicles which they should deliver products to a set of customers. Nowadays, there have been increasing concern about the rapid

Journal

International Journal of Intelligent Transportation Systems ResearchSpringer Journals

Published: Jun 4, 2018

References

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