The optimal route search in Bengaluru city transport using Hamilton circuit algorithm

Area of Science:

• Transportation Engineering
• Urban Planning
• Computer Science

Background:

• Traffic congestion is a significant global issue, particularly in Indian megacities like Bengaluru.
• High volumes of private vehicles and limited road capacity exacerbate urban traffic problems, leading to road saturation.
• Current public transportation routes in Bengaluru are often inefficient, contributing to congestion.

Purpose of the Study:

• To develop and analyze an intelligent agent model for optimizing public transportation routes in Bengaluru.
• To apply traffic engineering principles, specifically the Hamilton circuit algorithm, to redesign transit routes.
• To reduce traffic load and alleviate congestion in key urban areas through route optimization.

Main Methods:

• An intelligent agent model was developed to perform route engineering for public transportation.
• The Hamilton circuit algorithm was employed to analyze and identify optimal routes.
• A backtracking algorithm was utilized to reconfigure single-path routes into circular routes.

Main Results:

• The simulation demonstrated that reconfigured circular routes significantly reduced traffic load on public transportation.
• Optimization using the backtracking algorithm led to a notable decrease in congestion.
• Improved overall traffic flow was observed in key areas of Bengaluru.

Conclusions:

• Reconfiguring public transit routes into optimized circular paths is an effective strategy for mitigating traffic congestion.
• Intelligent agent models and algorithms like Hamilton circuit and backtracking can enhance urban transportation efficiency.
• The study provides a viable solution for improving traffic conditions in congested Indian cities.