Rear-Zone Vehicle Control for Vulnerable Road User Collision Avoidance
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Solution Overview
Problem
Vulnerable road users, such as pedestrians, cyclists, and motorcyclists, are at high risk of rear-end collisions due to limited visibility and protection, especially in city traffic, where they may not have early realization of traffic situations and are often obstructed by larger vehicles.
Innovation Solution
A computer-implemented method for reducing rear-end collisions by obtaining data on the position and vulnerability of road users, providing control instructions to vehicles to adjust their route, speed, or notify road users to avoid collisions, using autonomous or semi-autonomous vehicle systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle maintains its current trajectory and speed, then the vehicle's productivity and efficiency are improved, but the risk of rear-end collision with vulnerable road users increases
Solution Approach 1:
The system performs preliminary detection of vulnerable road users in the rear zone using sensors before the collision risk materializes. By identifying cyclists, pedestrians, or motorcyclists early and predicting their potential trajectories, the system can prepare preventive actions (trajectory adjustment, speed modification) in advance, allowing the vehicle to maintain higher productivity while preemptively eliminating collision hazards.
Solution Approach 2:
The control system acts as an intermediary between the vehicle's driving objectives and the vulnerable road users. It processes sensor data about road users and translates this information into appropriate control instructions (trajectory adjustments, speed modifications) that mediate between maintaining vehicle efficiency and ensuring road user safety, thereby resolving the contradiction between productivity and collision risk.
2Object-affected harmful factors
If the vehicle adjusts its trajectory or speed to avoid vulnerable road users, then the collision risk is reduced, but the vehicle's productivity and travel time increase
Solution Approach 1:
The system dynamically adjusts the vehicle's trajectory and speed based on real-time detection of vulnerable road users and prediction of their movements. Rather than static avoidance zones, the system continuously adapts the safety margin and avoidance maneuvers according to the detected road user's position, speed, and predicted trajectory, allowing minimal deviations from the optimal path while maintaining collision avoidance.
Solution Approach 2:
The system changes operational parameters (trajectory coordinates, speed) only when necessary and by the minimum amount required to eliminate collision risk. By calculating the precise safety margin needed based on detected road user characteristics and vehicle dynamics, the system modifies parameters just enough to ensure safety while maximizing productivity, avoiding excessive deviations from the optimal route.
3Reliability
If the vehicle provides comprehensive detection and control instructions for all road users, then the safety coverage is improved, but the device complexity increases
Solution Approach 1:
The system applies different levels of detection and control based on the local characteristics of detected road users. Rather than treating all road users uniformly, it adjusts the safety margin and control instruction intensity according to each road user's vulnerability, position, and predicted trajectory. This localized approach ensures comprehensive safety coverage for vulnerable users while avoiding unnecessary complexity for situations with lower risk.
Solution Approach 2:
The sensor system and control unit are designed to handle multiple types of road users (cyclists, pedestrians, motorcyclists) and various traffic scenarios using a single integrated system. The universal detection and control architecture processes different road user types through common algorithms and actuators, achieving comprehensive safety coverage without proportionally increasing system complexity through multiple specialized subsystems.
Data Source
AI summary
A computer-implemented method for reducing a risk of a collision of a road user with a rear-end of a vehicle. The method includes obtaining first data indicative of a position of the road user in a zone behind the rear-end of the vehicle, obtaining second data indicative of the road user being a vulnerable road user, and providing a control instruction for controlling the vehicle for reducing the risk of the rear-end collision based on the first data and the second data.