Application of artificial intelligence for modeling driving behavior supported with real time trajectory development

The proposed research work is aimed at developing trajectory data on a real-time basis. On successful completion of the project, a real-time image processing framework will be available for developing innumerable trajectory datasets over the study sections. These datasets can enormously boost current driving behavior studies and facilitate Connected Autonomous Vehicles (CAV) research. Along with this, the trajectory database can be a potent source in understanding different traffic stream aspects, such as stability, safety, and attention. Later, the research work will also test AI concepts in modeling driving behavior. In addition, the potential of AI in simulating driving behavior will be assessed. Such driving behavior simulation has a huge potential in addressing the limitations of conventional behavioral models, like expressing stochastic driving behavior, assuming non-uniformity, finally improving the precision in modeling. Besides, in the present project, it is planned to carry the traffic flow modeling using Artificial Intelligence (AI), on successful modeling this can act as frame work in understanding traffic flow characteristics with AI.

Faculty Supervisor:

Said Easa

Student:

Partner:

Sardar Vallabhbhai National Institute of Technology, Surat

Discipline:

Engineering

Sector:

Transportation (excluding aerospace); Other

University:

Toronto Metropolitan University

Program: