Smart Cruise Control Steers Drivers Toward Better Decisions

Vehicle manufacturers offer smart features such as lane and braking assist to aid drivers in hazardous situations when human reflexes may not be fast enough. But most options only provide immediate benefits to a single vehicle.
What if, like a murmuration of starlings, our cars and trucks moved cooperatively on the road in response to each vehicle's environmental sensors, reacting as a group to lessen traffic jams and protect the humans inside?
This question forms the basis of Kuilin Zhang's National Science Foundation CAREER Award research. Zhang, an associate professor of civil and environmental engineering at Michigan Technological University, has published "A distributionally robust stochastic optimization-based model predictive control with distributionally robust chance constraints for cooperative adaptive cruise control under uncertain traffic conditions" in the journal Transportation Research Part B: Methodological.
The paper is coauthored with Shuaidong Zhao, now a senior quantitative analyst at National Grid, where he continues to conduct research on the interdependency between smart grid and electric vehicle transportation systems.
Creating vehicle systems adept at avoiding traffic accidents is an exercise in proving Newton's First Law: An object in motion remains so unless acted on by an external force. Without much warning of what's ahead, car accidents are more likely because drivers don't have enough time to react. So what stops the car? A collision with another car or obstacle -- causing injuries, damage and in the worst case, fatalities.







