Ray Tracing for Hidden Obstacle Detection in Vehicles
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Solution Overview
Problem
Existing vehicle sensor systems struggle to detect hidden obstacles effectively, as they often cannot distinguish between the absence of a return signal due to no obstacle within range and the presence of a hidden obstacle, leading to potential safety hazards.
Innovation Solution
The method and system utilize ray tracing to transmit outbound sensor signals and determine if an obstacle is present along the projected path by analyzing the lack of return signals in conjunction with maps, such as terrain and static obstacle maps, to implement appropriate driving maneuvers to avoid hidden obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor systems are used to detect obstacles, then the system complexity remains low, but the detection precision deteriorates due to inability to distinguish hidden obstacles from absence of objects
Solution Approach 1:
The patent introduces map data as an intermediary element to assist in obstacle detection. By comparing sensor signals with pre-stored map information about static obstacles and terrain, the system can infer the presence of hidden obstacles that block sensor signals, thereby improving detection precision without requiring additional physical sensors
Solution Approach 2:
The patent replaces purely physical/mechanical detection methods with a computational approach. Instead of relying solely on sensor signal presence/absence, the system uses processing circuits to perform logical operations comparing sensor data with map data, substituting mechanical detection limitations with computational analysis to detect hidden obstacles
2Reliability
If sensor signals are transmitted to detect obstacles, then the detection range increases, but the reliability deteriorates due to false negatives from hidden obstacles
Solution Approach 1:
The patent performs preliminary action by pre-storing map data about static obstacles and terrain features before the detection process. This advance preparation enables the system to compare incoming sensor signals against known environmental information, allowing it to infer the presence of hidden obstacles that would otherwise cause false negatives
Solution Approach 2:
The system implements feedback by continuously comparing sensor signals with map data and using this comparison to infer the presence of hidden obstacles. The processing circuits analyze discrepancies between expected sensor returns (based on map data) and actual sensor readings, generating information about hidden obstacles that compensates for the original information loss
Data Source
AI summary
Ray tracing can be used to detect hidden obstacles in an external environment of a vehicle. An outbound sensor signal can be transmitted into an external environment of the vehicle. The outbound sensor signal can be a LIDAR sensor signal. If a return sensor signal is not received for the outbound sensor signal, it can be determined whether an obstacle is located along a projected path of the outbound sensor signal. Such a determination can be made using one or more maps, such as a terrain map and/or a static obstacle map. Responsive to determining that an obstacle is located along the projected path of the outbound sensor signal, a driving maneuver for the vehicle relative to the obstacle can be determined. The vehicle can be caused to implement the determined driving maneuver.