SELF-LEARNING BASED MECHANISM FOR VEHICLE UTILIZATION AND OPTIMIZATION

摘要

There is no mechanism for vehicle utilization and optimization through continuous and incremental planning which ensures that transportation plans are based on real-time conditions. The present invention discloses systems and methods for vehicle utilization and optimization based on self-learning mechanism. A machine learning model for dynamic association of users to vehicles is provided that learns previously clubbed patterns of users with their corresponding locations. The learnt previously clubbed patterns are utilized for determining association between previously clubbed locations which is further utilized to obtain an optimal set of locations. The users are dynamically associated to vehicles allocated for the obtained optimal set of locations by honoring one or more social and vehicle constraints. The proposed system has self-learning capability which ensures effective vehicle utilization and optimization in real time.