Biography

Arash's research intends to understand the behavior of current and future transportation systems and to improve safety, mobility, and sustainability by utilizing data-driven approaches, emerging technologies, and simulation. He has been exploring innovative data collection methods such as using smartphones and instrumented vehicles/bicycles. In particular, he conducted a bicycle naturalistic data collection experiment to study violation behavior of cyclists at intersections and presented how Vehicle/Bicycle-to-Infrastructure Communications can be a potential countermeasure for crashes resulting from drivers' and cyclists' violations at intersections. He also employed machine learning algorithms and statistical tools to develop models to identify the transportation modes using smartphone sensor data collected through a smartphone application that he developed. In the area of big data analytics in transportation, he has been working on adopting artificial intelligence algorithms to develop predictive models such as red light running violation prediction models. His other research experience includes modeling large-scale networks and emergency evacuation management. Integrating traffic simulation and optimization, he has examined evacuation mitigation strategies such as contraflow, crossing elimination at intersections, and ramp closure.

Research Interests

• Intelligent transportation systems (ITS)
• Traffic safety
• Connected and autonomous vehicles
• Advanced data collection methods (smartphones, naturalistic)
• Artificial Intelligence
• Big data analytics

Education

Appointments