Dynamic Timetable and Route Optimized Public Transport System

Abstract

The current bus transportation system relies on experience-based manual decisions for route planning and timings which may result in longer ride times and total distance travelled as well as increasing cost and carbon emissions along with usage of resources more than required. On the other hand, timetables are often outdated and created based on static information resulting in suboptimal results and an increase in waiting time of passengers due to unreliable scheduling of buses. We propose a three-fold solution to the current system by Route Optimization which provides the most effective route connections concerning traffic and population using a genetic algorithm, Dynamic Timetable Generation considering peak hour traffic and seasonal patterns, and Application which provides real-time information and recommendation about buses, automatic personalized notifications about new stops and timings on modification of routes/timetables.