Abstract:
With the rapid development of intelligent vehicles and Advanced Driver-Assistance Systems (ADAS), a new trend is that mixed levels of human driver engagements will be inv...Show MoreMetadata
Abstract:
With the rapid development of intelligent vehicles and Advanced Driver-Assistance Systems (ADAS), a new trend is that mixed levels of human driver engagements will be involved in the transportation system. Therefore, necessary visual guidance for drivers is vitally important under this situation to prevent potential risks. To advance the development of visual guidance systems, we introduce a novel vision-cloud data fusion methodology, integrating camera image and Digital Twin information from the cloud to help intelligent vehicles make better decisions. Target vehicle bounding box is drawn and matched with the help of the object detector (running on the ego-vehicle) and position information (received from the cloud). The best matching result, a 79.2% accuracy under 0.7 intersection over union threshold, is obtained with depth images served as an additional feature source. A case study on lane change prediction is conducted to show the effectiveness of the proposed data fusion methodology. In the case study, a multi-layer perceptron algorithm is proposed with modified lane change prediction approaches. Human-in-the-loop simulation results obtained from the Unity game engine reveal that the proposed model can improve highway driving performance significantly in terms of safety, comfort, and environmental sustainability.
Published in: IEEE Transactions on Intelligent Vehicles ( Volume: 7, Issue: 2, June 2022)
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- IEEE Keywords
- Index Terms
- Data Fusion ,
- Lane Change ,
- Advanced Driver Assistance Systems ,
- Lane Change Prediction ,
- Transport System ,
- Highway ,
- Environmental Sustainability ,
- Object Detection ,
- Intersection Over Union ,
- Multilayer Perceptron ,
- Bounding Box ,
- Depth Images ,
- Digital Information ,
- Digital Twin ,
- Visual Guidance ,
- Game Engine ,
- Intelligent Vehicles ,
- Target Vehicle ,
- Intersection Over Union Threshold ,
- Cloud Computing ,
- Global Navigation Satellite System ,
- RGB Camera ,
- Lane Change Maneuver ,
- Extrinsic Parameters ,
- Steering Angle ,
- Object Detection Model ,
- Aggressive Approach ,
- Coordinate Transformation ,
- Depth Camera ,
- Intrinsic Parameters
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Data Fusion ,
- Lane Change ,
- Advanced Driver Assistance Systems ,
- Lane Change Prediction ,
- Transport System ,
- Highway ,
- Environmental Sustainability ,
- Object Detection ,
- Intersection Over Union ,
- Multilayer Perceptron ,
- Bounding Box ,
- Depth Images ,
- Digital Information ,
- Digital Twin ,
- Visual Guidance ,
- Game Engine ,
- Intelligent Vehicles ,
- Target Vehicle ,
- Intersection Over Union Threshold ,
- Cloud Computing ,
- Global Navigation Satellite System ,
- RGB Camera ,
- Lane Change Maneuver ,
- Extrinsic Parameters ,
- Steering Angle ,
- Object Detection Model ,
- Aggressive Approach ,
- Coordinate Transformation ,
- Depth Camera ,
- Intrinsic Parameters
- Author Keywords