The significant improvement of population and multiple types of vehicles causes traffic congestion and environment problem. The economic prosperity and continuing urbanization have led to quick raise in travel demand in urban areas. Rapid urbanization and motorization in cities cause congestion and an increase in vehicular emission and also increase the accident. Travelers face the practical problem of identifying the most efficient route on their daily journey. Fuel consumption, emission, long travel time, and accident can be direct and indirect consequences of vehicle traffic congestion and rough driving pattern. Personalized driving system needs some specific real-time data like vehicle volume, weather condition of the area, road condition, carbon emission factors, and safety measures. Hence in this work, genetic algorithm (GA) is proposed to find the optimal route for the drivers based on their requirement. In this work, optimal path will be identified from several paths. Route maps of Madurai City, Delhi City, Northern Utah City are considered. The GA result is compared to Bellman–Ford algorithm. The GA finds the best route for 94.6% of accurately, and Bellman–Ford algorithm finds the shortest path for 92.4% of accurately. The results have proven that the proposed GA works better for the personalized route finding system.
Personalized Route Finding System Using Genetic Algorithm
Advs in Intelligent Syst., Computing
Congress on Intelligent Systems ; 2020 ; New Delhi, India September 05, 2020 - September 06, 2020
2021-05-28
13 pages
Article/Chapter (Book)
Electronic Resource
English
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