CHAMP: Crowdsourced, History-Based Advisory of Mapped Pedestrians for Safer Driver Assistance Systems

Understand

Vehicles are constantly approaching and sharing the road with pedestrians, and as a result it is critical for vehicles to prevent any collisions with pedestrians.

• Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Automatic Emergency Braking (AEB) systems which can trigger warnings and apply brakes as a pedestrian enters a vehicle's path.
• Unfortunately, pedestrian-detection-based systems can be hindered in certain situations such as nighttime or when pedestrians are occluded.
• Our system, CHAMP (Crowdsourced, History-based Advisories of Mapped Pedestrians), addresses such issues using an online, map-based pedestrian detection system where pedestrian locations are aggregated into a dataset after repeated passes of locations.