Human Factors

Automated driving allows for at least some degree of vehicle control to be shifted from the driver to the vehicle. It changes not only the driving behavior but also the travel decision making process. The change of driving behavior will impact the design of the automated vehicle system that further impacts travelers’ adaption of CAV. In addition, the change of travel behavior may affect the system performance. The objectives of this research topic are to (i) leverage the capability of driving simulators at both UM and Purdue to investigate the factors that impact drivers’ decisions to take over driving tasks, (ii) optimize in-vehicle alarm systems to inform drivers to take over, (iii) investigate the psychological effect on users’ acceptance of CAVs using driving simulator and biosensors, and (iv) understand route choice behavior of CAV users. The research will be conducted by applying analytical models (psychological models, driver behavior models) to driving simulator experiments integrated with biosensors. The research results are expected to foster safe driving of CAV and increases users’ acceptance of CAV technology.

Research Focusing on Human Factors


CAV Developed Vehicles as Real-Time Sensors for Assessing Greenhouse Gases
Principal Investigator:
Krishnakumar Nedunuri & Ramanitharan Kandiah
Research Thrusts: Enabling TechnologyHuman FactorsModeling & Implementation
CAV Systems Incorporating Air Pollution Information from Traffic Congestion
Principal Investigator:
Krishnakumar Nedunuri & Ramanitharan Kandiah
Research Thrusts: Enabling TechnologyHuman FactorsModeling & Implementation
Supporting People with Vision Impairments in Automated Vehicles
Principal Investigator:
Robin Brewer & Nicole Ellison
Research Thrusts: Human Factors