Knowledge based genetic algorithm for dynamic route selection

Kanoh, Hitoshi; Nakamura, T.

doi:10.1109/kes.2000.884123

Cited by 30 publications

(10 citation statements)

References 6 publications

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“…Hitoshi Kanoh and Tomohiro Nakamura studied the route choice problem under a dynamic environment [23]. They used a genetic algorithm which employs the method of viruses as domain-specific knowledge.…”

Section: Previous Workmentioning

confidence: 99%

Survey of Route Choice Models in Transportation Networks

Sharma

Gupta

Lala

2014

Intelligent Computing, Networking, and Informatics

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Finding a shortest and convenient route by taking into account all the relevant factors is not an easy task. The accuracy and efficiency of the route depend on precision with which all the variables in the problem are incorporated. A lot of research has been undertaken on developing such route guidance system, and several procedures have been developed for this purpose. In the present paper, a survey of different route choice models has been discussed.

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Section: Previous Workmentioning

confidence: 99%

Survey of Route Choice Models in Transportation Networks

Sharma

Gupta

Lala

2014

Intelligent Computing, Networking, and Informatics

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“…The route guidance algorithm using VGA was proposed by H.Kanoh [2] [3]. In the route guidance algorithm, a road that includes a spot is regarded as a virus.…”

Section: B Base Algorithmmentioning

confidence: 99%

“…As a result, the DA can not solve it within a practical time span. On the other hand, the route selection algorithm using Virus Genetic Algorithm (VGA) is proposed for the route selection model [2], [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Architecture of virus evolutionary genetic algorithm for car navigation system

Yoshikawa

Terai

2007

2007 50th Midwest Symposium on Circuits and Systems

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This Route selection is an important problem for a car navigation system. In general car navigation system, the Dijkstra algorithm (DA) is used as route selection algorithm. From the viewpoint of practical convenience of the driver, we assume a route selection model that a driver must visit at shops (for example, restaurant) on the way to a destination, but it is not necessary for these shops to be specific shops. Several studies have dealt with conducted this problem using Virus Genetic Algorithm (VGA). However, the VGA requires much calculation time, because VGA is multipoint search algorithm. In this paper, we propose an architecture for high-speed car navigation system based on VGA. Moreover, the route guidance function for sightseeing is newly added to the proposed architecture. The proposed architecture, implemented on the field-programmable gate array (FPGA), achieves high-speed processing. Measurement evaluating the proposed architecture demonstrated speeds 20 times greater than software processing.

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“…This hierarchical Voronoi graph based route planning algorithm [6] utilized the characteristics of the road network hierarchy to reduce searching time and the expanded node number of route searching. However, as mentioned in [9], if a car accident occurred in the route generated by the shortest path algorithm, this planned path cannot be used at all. Road network database was adopted in [9] to store all computed paths in the past.…”

Section: Introductionmentioning

confidence: 99%

“…However, as mentioned in [9], if a car accident occurred in the route generated by the shortest path algorithm, this planned path cannot be used at all. Road network database was adopted in [9] to store all computed paths in the past. When a car accident occurs, the situation will be immediately updated in the road network database and case-based reasoning is used to locate the path in the database by examining if the origin and the destination are the same as the data stored in the database.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Vehicle Path Planning System

Huang¹,

Hu²,

Wang³

et al. 2015

IJCCE

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Abstract-Nowadays, most of the road navigation systems planning optimal routes are conducted by the On Board Unit (OBU). If drivers want to obtain the real-time road status, a Traffic Message Channel (TMC) module is needed. However, this module can only provide the current road conditions, instead of planning appropriate routes for users. In this work, the concept of the cellular automata is used to collect the real-time road conditions and derives the appropriate paths for users. Notably, fuzzy logic is adopted for path analysis for each cell established in the cellular automata algorithm. Besides establishing the optimal routes, this research is expected to automatically meet the personal demands of all drivers, reach the load balancing in all road sections to avoid the problem of traffic jams, and allow the drivers enjoy better driving experiences. A series of simulations were conducted to compare the proposed approach with the well-known A* Search algorithm and the latest state-of-the-art path planning algorithm in the literature. The experimental results exhibited that the proposed approach is scalable in terms of the turnaround time to individual users. The practicality and feasibility of applying the proposed approach in real-time environment is thus justified.Index Terms-Search algorithm, cellular automata, fuzzy logic, optimal path planning.

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Knowledge based genetic algorithm for dynamic route selection

Cited by 30 publications

References 6 publications

Survey of Route Choice Models in Transportation Networks

Survey of Route Choice Models in Transportation Networks

Architecture of virus evolutionary genetic algorithm for car navigation system

An Adaptive Vehicle Path Planning System

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