Autonomous Vehicle Speed Control for Shadowed Detection Horizons
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating through environments where sensor detection horizons are reduced due to shadowing by other road users, potentially leading to inadequate braking distances and increased risk of accidents.
Innovation Solution
A method for operating vehicles that dynamically adjusts speed based on real-time sensor data from cameras, radar, or lidar sensors to maintain a safe detection horizon greater than the braking distance, anticipating and responding to reduced detection areas caused by other road users, thereby preventing emergency braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle maintains a constant speed, then the productivity is improved, but the safety deteriorates when the detection horizon is reduced due to shadowing
Solution Approach 1:
The vehicle speed is dynamically adjusted based on the detected shadowing conditions and calculation of the reduced detection horizon. The control unit continuously monitors sensor data, determines when shadowing occurs, calculates the reduced detection horizon, and adapts the vehicle speed accordingly to maintain safety while optimizing productivity.
Solution Approach 2:
The system uses sensor data feedback to continuously monitor the detection horizon and shadowing conditions. The control unit receives feedback from sensors about the current detection horizon, compares it with the required safety distance, and adjusts the vehicle speed in response to maintain the safety condition while preserving productivity when conditions allow.
2Reliability
If the vehicle reduces speed to maintain safe stopping distance, then the safety is improved, but the productivity deteriorates
Solution Approach 1:
The vehicle applies partial speed reduction only when and where shadowing occurs, rather than maintaining reduced speed universally. The control unit calculates the specific reduced detection horizon caused by shadowing and reduces speed only to the extent necessary to maintain safety in the shadowed region, allowing full speed to be maintained in unshadowed regions.
3Measurement precision
If the vehicle uses multiple sensors to trace road users, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system merges data from multiple sensors (lidar, cameras, radar) to comprehensively detect shadowing conditions and calculate the reduced detection horizon. By combining sensor inputs, the system achieves accurate detection of shadowing effects while using a integrated approach that manages the complexity of multiple sensors through unified processing.
Data Source
AI summary
Surroundings in front of a vehicle are detected and the vehicle speed is reduced when the surroundings are partially shaded so the vehicle can be brought to a safe stop, without emergency braking, in front of an object located in the region of the shadowing in the lane in which the vehicle is travelling. In the event of a static detection of a reduced detection horizon less than a braking distance dependent on a current speed, the vehicle is decelerated such that the reduced detection horizon is again greater than the braking distance. Other road users in the surroundings of the vehicle are traced with sensors and shadowing by them and a resulting expected reduced detection horizon are determined in advance of a future point in time so that the vehicle speed is reduced and the expected reduced detection horizon at the time is again greater than the braking distance.