Paper Info
Title
On Designing Near-Optimum Paths on Weighted Regions for an Intelligent Vehicle
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.
Year
DOI
Venue
2019
10.1007/s13177-018-0159-5
International Journal of Intelligent Transportation Systems Research
Keywords
Field
DocType
Urban environment, Weighted regions, Near-optimum paths, Intelligent transportation systems, Intelligent vehicle
Urban environment,Computer network,Real-time computing,Distance matrix,Intelligent transportation system,Engineering,Genetic algorithm,Encoding (memory)
Journal
Volume
Issue
ISSN
17
2
1868-8659
Citations 
PageRank 
References 
0
0.34
15
Authors
1
Name
Order
Citations
PageRank
Elias k. Xidias1537.16