Title :
Onboard Sensor-Based Collision Risk Assessment to Improve Pedestrians´ Safety
Author :
De Nicolao, Giuseppe ; Ferrara, Antonella ; Giacomini, Luisa
Author_Institution :
Pavia Univ., Pavia
Abstract :
Many systems have been designed for pedestrian detection and tracking. However, pedestrians may or may not be in dangerous situations. Signaling every detected pedestrian generates too many false alarms, which could lead the driver not to pay attention to the warnings. The contribution of this paper is to develop a novel approach to assessing the risk of collision with a pedestrian based on the scenario and the behavior of the pedestrian. The risk assessment is based on extensive offline Monte Carlo simulations relying on a simple, yet representative, stochastic model of the pedestrian. The approach has been applied for the design of the Risk Assessment Unit of the PROTECTOR project dealing with pedestrian detection and classification funded by the European Commission.
Keywords :
Monte Carlo methods; collision avoidance; risk management; road safety; sensors; tracking; Monte Carlo simulations; PROTECTOR project; collision risk assessment; onboard sensor; pedestrian detection; pedestrian safety; pedestrian tracking; stochastic model; Alarm systems; Intelligent sensors; Intelligent systems; Laser radar; Protection; Risk management; Road accidents; Sensor systems; System testing; Vehicle safety; Collision avoidance; Monte Carlo simulation; pedestrian safety; random walk; risk assessment;
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2007.899209