Pedestrian Collision Avoidance with Dynamic TTC Thresholds
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Solution Overview
Problem
Current vehicle collision avoidance systems are inadequate in detecting pedestrians and providing timely warnings or interventions, especially in scenarios where pedestrians are likely to be present, such as near bus stops or schools, and do not adequately account for various environmental and driver parameters.
Innovation Solution
A collision avoidance system utilizing multiple cameras and an image processor to determine a baseline time to collision (TTC) based on vehicle, pedestrian, environmental, and driver parameters, adjusting sensitivity and alert timing to prevent collisions by providing earlier warnings and potentially applying the brakes, even in scenarios where pedestrians are moving towards the vehicle's path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system increases sensitivity and provides earlier warnings to prevent pedestrian collisions, then pedestrian safety is improved, but false alarms and unnecessary brake interventions increase
Solution Approach 1:
The system dynamically adjusts the TTC threshold parameter based on environmental conditions, vehicle speed, and location context. By changing the threshold parameter rather than using a fixed value, the system can increase sensitivity in high-risk areas while maintaining appropriate thresholds in low-risk areas, thus improving collision avoidance without generating excessive false alarms
Solution Approach 2:
The system transitions from static collision detection to dynamic assessment by continuously monitoring multiple parameters (vehicle speed, pedestrian motion vectors, environmental context, road conditions) and adjusting the warning threshold in real-time. This dynamic approach allows the system to adapt sensitivity levels to current conditions, reducing false alarms while maintaining high reliability when actual risks are present
2Measurement precision
If the system accounts for multiple parameters (vehicle traction, environmental conditions, driver attentiveness) to adjust TTC, then collision avoidance accuracy is improved, but system complexity increases
Solution Approach 1:
The system uses a multi-functional processor that handles multiple tasks: detecting pedestrians, tracking their motion, assessing environmental conditions, monitoring vehicle state, and calculating adjusted TTC. By consolidating these functions into a single processing unit rather than separate dedicated systems, the accuracy is improved while complexity is managed through functional integration
Solution Approach 2:
The system combines data from multiple sources (cameras, sensors, vehicle computer) and merges them into a unified collision risk assessment. By merging the evaluation of diverse parameters into a single integrated TTC calculation rather than separate independent systems, the patent achieves higher accuracy while reducing overall system complexity through consolidation
3Reliability
If the system provides earlier warnings and controlled braking, then pedestrian safety is improved, but driver control and vehicle operation complexity increase
Solution Approach 1:
The system applies preliminary warning actions (visual, auditory, haptic alerts) before potential collision, giving the driver advance notice and opportunity to respond. By providing preliminary warning rather than immediate emergency braking, the system protects pedestrians while maintaining driver control and avoiding unnecessary intervention in low-risk situations
Solution Approach 2:
The system performs preliminary assessment and warning before collision becomes inevitable, allowing the driver time to react. By acting preliminarily with warnings rather than waiting for critical moments, the system improves safety while preserving driver ease of operation through gradual, non-intrusive intervention
Data Source
AI summary
A vehicular collision avoidance system includes a sensor disposed at a vehicle for sensing exterior and forwardly of the vehicle. A processor processes sensor data captured by the sensor to determine the presence of a pedestrian ahead of the vehicle and outside a path of travel of the vehicle. The processor determines a projected path of travel of the pedestrian based on movement of the pedestrian. The processor determines where the forward path of travel of the vehicle intersects the projected path of travel of the pedestrian. The system, responsive at least in part to prediction that the pedestrian will be in the forward path of travel of the vehicle when the vehicle time to intersection elapses, adjusts the speed of the vehicle based at least in part on attentiveness of a driver of the vehicle and a driving condition of the vehicle.


