Pedestrian crash avoidance mitigation

Part of a series on
Self-driving cars & self-driving vehicles
Enablers
Assured clear distance ahead Autonomous racing Datasets History Impact Lane centering Pedestrian crash avoidance mitigation Vehicle infrastructure integration
Topics
Automatic parking Platoon Regulation Liability Robotaxi Self-driving truck Tunnel problem
Related topics
Automatic train operation Unmanned surface vehicle Vehicular automation
v t e

Pedestrian crash avoidance mitigation (PCAM) systems (USDOT Volpe Center^[1]), also known as pedestrian protection or detection systems, use computer and artificial intelligence technology to recognize pedestrians and bicycles in an automobile's path to take action for safety. PCAM systems are often part of a pre-collision system available in several high end car manufacturers, such as Volvo and Mercedes and Lexus,^[2] and used less widely in lower end cars such as Ford and Nissan.^[3] As of 2018 using 2016 data, more than 6,000 pedestrians and 800 cyclists are killed every year in the US in car crashes. Effective systems deployed widely could save up to 50% of these lives. More than 270,000 pedestrians are killed every year in the world. An excellent analysis of technology capabilities and limitations is provided in Death of Elaine Herzberg. Pedestrian safety has traditionally taken a secondary role to passenger safety.