Vehicle Collision Prediction Using Time-Space Overlap Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional collision avoidance systems in vehicles often cause unnecessary yielding, leading to traffic delays by incorrectly assessing collision risks with pedestrians and other agents, particularly in situations where the pedestrian is slowing down or the crosswalk is in a non-crossable state.
Innovation Solution
A vehicle computing system that determines regions of potential collision by analyzing probable paths and velocities of agents and contextual data, using time-space overlap and probability density functions to assess collision likelihood and decide on appropriate actions such as yielding or navigating through the region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional collision avoidance systems simply identify surfaces and adjust vehicle velocity to avoid collision, then collision avoidance is achieved, but unnecessary yielding occurs causing traffic delays
Solution Approach 1:
The system changes parameters by transitioning from simple surface detection to multi-dimensional analysis including agent classification (pedestrian, cyclist, vehicle), behavior prediction (crossing intent, speed changes), and contextual factors (crosswalk state, traffic signals). This enables more accurate collision risk assessment that distinguishes between genuine threats and situations requiring normal yielding, thereby reducing unnecessary traffic delays while maintaining collision avoidance reliability
Solution Approach 2:
The system implements dynamic assessment by continuously monitoring agent velocity changes, acceleration patterns, and trajectory modifications. By detecting when pedestrians slow down or change behavior (e.g., stopping at crosswalks), the system dynamically adjusts collision risk evaluation in real-time, allowing vehicles to proceed without unnecessary yielding when agents are not maintaining collision courses
2Reliability
If traditional systems yield to all detected agents to ensure safety, then collision avoidance is improved, but traffic flow efficiency deteriorates
Solution Approach 1:
The system applies local quality by treating different agent types and situations differently rather than applying uniform yielding rules. It classifies agents into categories (pedestrians, cyclists, vehicles) and applies context-specific assessment criteria, such as evaluating crossing intent for pedestrians at crosswalks versus continuous monitoring for vehicles in adjacent lanes. This differentiated approach maintains safety for genuine threats while improving traffic flow by avoiding unnecessary yielding to agents that pose no collision risk
Solution Approach 2:
The system performs preliminary action by predicting agent future positions and collision likelihood before making yielding decisions. By using probability density functions to forecast agent trajectories and assessing collision risk in advance, the system can identify situations where yielding is unnecessary (e.g., pedestrians clearly not intending to cross) and maintain traffic flow efficiency while still preparing appropriate safety responses for genuine collision threats
Data Source
AI summary
Techniques and methods for providing additional safety for interactions with pedestrians. For instance, a vehicle may identify a region through which the vehicle and agent (such as a pedestrian) pass. The vehicle may determine a time buffer value and/or a distance buffer value based on the vehicle and the agent passing through the region. The vehicle may determine a time threshold and/or a distance threshold for passing through the region in the presence of the agent. The time threshold and/or the distance threshold may be based on a velocity of the vehicle, a safety factor, a hysteresis factor, a comfort factor, and/or an assertiveness factor. If the time buffer value is below the time threshold and/or the distance buffer value is below the distance threshold, the vehicle may yield to the agent. Otherwise, the vehicle may not yield to the agent within the region.