Remote Vehicle Takeover for Predicted Autonomous Driving Hazards
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face limitations in responding to critical events due to rapid analysis and potential misinterpretations of environmental data, restricting effective piloting actions and safety during unforeseen situations.
Innovation Solution
A method that involves predictive detection of critical events by a remote control center using data on traffic, meteorological conditions, and sensor data from upstream locations, allowing a human operator to temporarily take control of the vehicle via a wireless communication network to implement optimal piloting actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the automatic driving device performs rapid analysis of environmental data to detect critical events, then the response speed is improved, but misinterpretations occur and piloting actions become limited
Solution Approach 1:
The system performs preliminary detection of critical events upstream of the vehicle's geographical position before the vehicle reaches the hazard. This advance detection allows the remote control center to analyze data from multiple sources (traffic conditions, meteorological conditions, sensor data) and prepare appropriate piloting actions without the time pressure that causes misinterpretations in rapid onboard analysis.
Solution Approach 2:
A remote control center acts as an intermediary between the autonomous vehicle and the critical event. The center receives data from the vehicle's sensors and external sources, performs comprehensive analysis, and sends back piloting commands. This intermediary structure allows for more thorough analysis than the vehicle's onboard system can achieve in real-time, reducing misinterpretations while maintaining rapid response through pre-positioned analysis upstream of the hazard.
2Device complexity
If the vehicle relies solely on onboard sensors and rapid analysis, then the system complexity is reduced, but the ability to anticipate and properly respond to critical events is limited
Solution Approach 1:
The remote control center serves multiple functions: it receives sensor data from the autonomous vehicle, gathers external data (traffic conditions, meteorological conditions), performs comprehensive analysis, determines critical events upstream of the vehicle, and sends piloting commands. This multi-functional center enhances the system's ability to respond to various critical events without requiring each vehicle to have complex onboard prediction capabilities.
Solution Approach 2:
The system performs preliminary detection and analysis of critical events upstream of the vehicle's position before the vehicle encounters the hazard. This advance preparation allows the simplified onboard system to receive ready-analyzed information and pre-planned piloting commands, enhancing responsiveness without increasing vehicle complexity.
3Measurement precision
If piloting actions are delayed until the vehicle reaches the critical event location, then the response is based on complete information, but the time available for effective action is reduced
Solution Approach 1:
The system detects and analyzes critical events upstream of the vehicle's geographical position in advance, before the vehicle reaches the hazard location. This preliminary action allows the remote control center to complete its analysis with complete information from multiple data sources and prepare appropriate piloting commands ahead of time, so that when the vehicle approaches the critical event, ready-to-execute commands are already available, eliminating the time loss between detection and action.
Data Source
AI summary
A method for assisting an autonomous motor vehicle includes using an autonomous motor vehicle equipped with an automatic driving device which is adapted to decide driving actions to be carried out in order to autonomously circulate on a route, connecting the automatic driving device to a computer server of a remote control center through a wireless communication network, determining the geographical position of the vehicle. The method also includes predictive detection of a critical event on the route upstream of the position of the vehicle, which results in said operator takes control of the remote vehicle and decides driving actions, predictive detection of the critical event resulting from the combined analysis of data that includes, data on the state of the traffic lanes taken on the route upstream, the road conditions, the meteorological conditions, data coming from sensors installed on the vehicle.