Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

• Main Authors: Minjin Baek, Donggi Jeong, Dongho Choi, Sangsun Lee
• Format: Article
• Language: English
• Published: MDPI AG 2020-01-01
• Series: Sensors
• Subjects: advanced driver assistance system; trajectory prediction; risk assessment; collision warning; connected vehicles; vehicular communications; vulnerable road users
• Online Access: https://www.mdpi.com/1424-8220/20/1/288

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle−vehicle collision scenario and a vehicle−pedestrian collision scenario.