Autonomous Vehicle Blind Spot Prediction for Speed Adjustment
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Solution Overview
Problem
Autonomous vehicles face challenges in providing a sense of safety for drivers and passengers by maneuvering around uncomfortable or unnerving blind spots, which are not solely defined by poor visibility but also by unnatural or unnerving positions relative to other vehicles, even when operating safely.
Innovation Solution
A method and device that utilize sensor data to detect objects, predict future locations, and determine blind spot areas based on object characteristics, with controlling factors input into speed algorithms to adjust vehicle speed and maneuvering to avoid prolonged exposure to these areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle uses sensors to identify and avoid vehicles ahead in the same lane, then safety is improved, but the vehicle may still enter blind spots of other vehicles causing discomfort to drivers and passengers
Solution Approach 1:
The system segments the detection space into multiple zones including blind spot areas adjacent to the vehicle. By dividing the monitoring environment into specific regions (ahead, adjacent, behind), the system can apply different detection and avoidance strategies to each segment, thereby avoiding uncomfortable positions while maintaining safety.
Solution Approach 2:
The system performs preliminary detection of blind spot areas using sensors before the vehicle enters them. By identifying potential blind spot positions in advance and predicting future locations, the autonomous vehicle can take preventive actions to avoid entering uncomfortable positions, thus maintaining both safety and driver comfort.
2Ease of operation
If the vehicle avoids all blind spot areas, then driver comfort is improved, but the complexity of the control system increases
Solution Approach 1:
The system merges blind spot detection with the existing sensor suite already used for safety monitoring. By combining blind spot area identification with standard obstacle detection functions, the system avoids uncomfortable positions without requiring entirely separate detection and control systems, thus limiting the increase in overall system complexity.
Solution Approach 2:
The sensor system serves multiple functions: detecting vehicles ahead for safety, identifying blind spot areas for comfort, and providing data for path planning. This multi-functionality allows the system to achieve comfort improvement without proportionally increasing system complexity, as the same hardware infrastructure supports multiple objectives.
3Ease of operation
If the vehicle spends more time monitoring and avoiding blind spots, then comfort is improved, but the time to reach destination decreases
Solution Approach 1:
The system allows the vehicle to quickly pass through blind spot areas when necessary, rather than spending excessive time avoiding them. By predicting future locations and determining whether the vehicle would drive in blind spot areas, the system can make rapid decisions to minimize time spent in uncomfortable positions while maintaining overall travel efficiency.
Solution Approach 2:
The system applies blind spot avoidance selectively rather than continuously. By determining whether the predicted future locations indicate the vehicle would drive in blind spot areas and applying control only when necessary, the system achieves comfort improvement without unnecessarily extending travel time for situations where avoidance is not required.
Data Source
AI summary
Aspects of the disclosure relate generally to detecting and avoiding blind spots of other vehicles when maneuvering an autonomous vehicle. Blind spots may include both areas adjacent to another vehicle in which the driver of that vehicle would be unable to identify another object as well as areas that a second driver in a second vehicle may be uncomfortable driving. In one example, a computer of the autonomous vehicle may identify objects that may be relevant for blind spot detecting and may determine the blind spots for these other vehicles. The computer may predict the future locations of the autonomous vehicle and the identified vehicles to determine whether the autonomous vehicle would drive in any of the determined blind spots. If so, the autonomous driving system may adjust its speed to avoid or limit the autonomous vehicle's time in any of the blind spots.