Autonomous Vehicle Threat Warning System
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Solution Overview
Problem
Current safety systems in autonomous vehicles primarily focus on protecting passengers after an adverse event occurs, failing to provide proactive warnings to operators about potential threats before they become hazardous.
Innovation Solution
An advanced threat warning system that generates risk indicators by analyzing vehicle route data and external object data, using sensors to determine proximity and state information, and communicating warnings to operators or remote monitoring systems to enable proactive action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current safety systems focus only on post-event protection, then device complexity is reduced, but passenger safety is compromised due to lack of proactive threat warnings
Solution Approach 1:
The system performs preliminary actions by continuously analyzing route data, object trajectories, and risk criteria before adverse events occur. It generates risk indicators in advance to enable proactive safety measures, transforming the safety approach from reactive to preventive while maintaining manageable system complexity through structured data processing
Solution Approach 2:
The safety system is segmented into distinct functional modules: route data acquisition, external object tracking, risk criterion evaluation, and indicator generation. This modular architecture improves reliability through specialized functions while controlling overall system complexity by making each component independently manageable
2Reliability
If proactive threat warning systems are implemented, then passenger safety is improved, but device complexity increases due to additional sensors and data processing requirements
Solution Approach 1:
The system uses multi-functional data processing that serves both proactive safety warnings and basic navigation functions. The same route data and object tracking infrastructure supports both threat detection and standard vehicle operation, reducing the need for separate dedicated components and thereby limiting complexity growth
Solution Approach 2:
Risk criteria and threat thresholds are pre-configured and established before operation. This preliminary setup allows the system to perform real-time safety assessments using predetermined parameters, reducing the computational complexity of real-time decision-making while maintaining high safety standards
Data Source
AI summary
Methods, apparatuses, systems, and non-transitory computer readable storage media for generating risk indicators are described. The disclosed technology includes determining a vehicle route of a vehicle and external object routes of external objects. The vehicle route is determined using vehicle route data including a vehicle location and a vehicle destination. The external object routes are determined using external object route data including external object locations and external object destinations. Based on a comparison of the vehicle route data and the external object route data, external object routes that satisfy a proximity criterion are determined. Risk data for the vehicle is generated based on a vehicle state of the vehicle and external object states of the external objects corresponding to the external object routes that satisfy the proximity criterion. In response to determining that the risk data satisfies a risk criterion, at least one risk indicator is generated.