Vehicle Detection via Shared RF Maps
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting other vehicles due to signal blocking or loss of radio-frequency (RF) signal reception, which can lead to safety hazards such as accidents, and there is a need for reliable pedestrian and object detection systems to address safety and legal liability concerns.
Innovation Solution
A vehicle detection system that uses RF signals and communication formats like V2V and V2X to share information about surrounding vehicles, allowing a vehicle to generate maps that indicate undetectable vehicles by receiving data from other vehicles, enabling safe maneuvering through traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a vehicle uses RF signals for direct detection of surrounding vehicles, then the detection range is limited by signal blocking and loss of RF signal reception, but the system complexity is reduced
Solution Approach 1:
The patent introduces a map data intermediary that mediates between detected vehicles and the ego vehicle. Instead of direct RF signal detection between all vehicle pairs, the system uses map data as an intermediary information carrier. Map data generated by one vehicle can be shared with other vehicles through communication infrastructure, enabling indirect detection of vehicles that are out of direct RF range or blocked by obstacles.
Solution Approach 2:
The patent transitions from a single-dimension direct RF signal detection approach to a multi-dimensional detection framework. By incorporating map data (spatial dimension) and communication infrastructure (network dimension), the system adds new dimensions to vehicle detection, allowing vehicles to detect surrounding traffic through multiple pathways: direct RF signals, shared map data, and infrastructure-mediated communication.
2Measurement precision
If a vehicle relies solely on direct RF signal reception for vehicle detection, then the system simplicity is maintained, but detection accuracy is reduced due to signal blocking and loss of reception
Solution Approach 1:
The patent merges multiple detection information sources: direct RF signal data, shared map data from other vehicles, and infrastructure-mediated communication data. By combining these diverse data sources, the system achieves more accurate and comprehensive vehicle detection, overcoming the limitations of relying on a single direct RF signal channel.
Solution Approach 2:
The system performs preliminary detection and map generation by vehicles in the vicinity before the ego vehicle needs the information. Other vehicles can detect and map surrounding vehicles in advance, and this pre-generated map data is then shared with the ego vehicle, enabling the ego vehicle to benefit from others' preliminary detection work without having to perform all detections itself.
3Area of stationary object
If the system uses map data sharing from other vehicles, then the detection coverage is improved, but the information processing complexity increases
Solution Approach 1:
The patent segments the detection task across multiple vehicles and information channels. Instead of one vehicle attempting to detect all surrounding vehicles directly, the detection task is segmented and distributed: each vehicle detects vehicles in its local vicinity and generates map data, which is then shared with other vehicles. The ego vehicle segments the information processing by receiving and integrating map data from multiple sources rather than performing all detections centrally.
Data Source
AI summary
Exemplary embodiments described in this disclosure are generally directed to vehicle detection systems and methods. In one exemplary embodiment, a vehicle detection system that is provided in a first vehicle receives a map generated by a vehicle detection system of a second vehicle. The map, which can be a cardinal map, for example, indicates a third vehicle that is detected by the vehicle detection system of the second vehicle and is undetectable by the first vehicle due to various reasons. For example, the first vehicle may fail to detect the third vehicle due to signal blocking caused by an intervening vehicle located between the first vehicle and the third vehicle, or due to the loss of radio-frequency (RF) signal reception by the vehicle detection system in the first vehicle. The second vehicle can detect the third vehicle by using radio-frequency (RF) signals and to convey the information to the first vehicle.