MPC Helping Autonomous and Human-Operated Vehicles Navigate Traffic Together
Posted: Feb 1, 2022
While autonomous vehicles (AVs) are expected to become more commonplace in coming years, they will need to share streets and roads with human-operated vehicles for decades. Researchers at North Dakota State University developed an infrastructure support system based on infrastructure sensors and a new vehicle-to-infrastructure algorithm for AVs to effectively use for enhanced safety and mobility. The system can monitor various vehicle and road condition data, including vehicle speed, wheelbase distances, the number of axles, vehicle classification, weigh in motion, road roughness, and in-pavement cracks. The use of this real-time information in a newly developed cumulative-anticipative car-following model can significantly improve the mobility and safety of the transportation system with different penetration rates of AVs.
While autonomous vehicles (AVs) are expected to become more commonplace in coming years, they will need to share streets and roads with human-operated vehicles for decades. Researchers at North Dakota State University developed an infrastructure support system based on infrastructure sensors and a new vehicle-to-infrastructure algorithm for AVs to effectively use for enhanced safety and mobility. The system can monitor various vehicle and road condition data, including vehicle speed, wheelbase distances, the number of axles, vehicle classification, weigh in motion, road roughness, and in-pavement cracks. The use of this real-time information in a newly developed cumulative-anticipative car-following model can significantly improve the mobility and safety of the transportation system with different penetration rates of AVs.