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

Abstract

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.

Sensors and Sensing for Intelligent Vehicles

“…Concerning the different topics and subtopics, we have identified up to seven main categories, and some sub-categories that are presented in the following list (the number of papers per each category/sub-category is enclosed in parentheses): Object detection and scene understanding (11) Vehicle detection and tracking (4): [ 13 , 14 , 15 , 16 ]. Scene segmentation and interpretation (7) Road segmentation (2): [ 17 , 18 ].…”

“…Object detection and scene understanding (11) Vehicle detection and tracking (4): [ 13 , 14 , 15 , 16 ]. Scene segmentation and interpretation (7) Road segmentation (2): [ 17 , 18 ].…”

“…In [ 16 ] a vehicle collision warning system is proposed based on a Kalman filter-based approach for high-level fusion of multiple sensors, including radar, LIDAR, camera and wireless communication. The trajectories of remote targets are predicted, and an appropriate warning to the driver is provided based on the TTC (Time-To-Collision) estimate and the risk assessment.…”

“… Vehicle–vehicle collision simulation results and snapshots of the experimental environment at two different time points (images obtained from [ 16 ]). …”

Effect of Multi-Frequency Beam Alignment on Non-Line-of-Site Vehicle to Infrastructure Communication using CI Model (CI-NLOS-V2I)

“…To achieve these objects, a more efficient use of the spectrum is required over the employed wireless communication frequency, thus leading to the concept of millimeter-wave (mmWave) [9][10][11].…”