Autonomous Vehicle Route Control Using Reliable Shared Environment Data
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Solution Overview
Problem
Existing vehicle control systems face challenges in maintaining the reliability of traveling environment information over time, which is crucial for accurate autonomous driving, especially as the environment changes dynamically.
Innovation Solution
A system that utilizes a communication interface to receive driving environment information from other autonomous vehicles and servers, determining navigation routes based on reliability, and controlling the vehicle's driving system accordingly, while also identifying and transmitting differences in detected environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If traveling environment information is generated and stored over time, then the coverage area and duration of navigation data increases, but the reliability of the information decreases as time passes
Solution Approach 1:
The system performs preliminary actions by having preceding vehicles collect and transmit traveling environment information to subsequent vehicles before those vehicles encounter the same environments. This allows following vehicles to receive pre-collected data about obstacles, road conditions, and traffic patterns ahead of time, extending the effective duration of reliable information without waiting for real-time collection.
Solution Approach 2:
The communication interface acts as an intermediary that transfers traveling environment information from preceding vehicles to following vehicles. This mediator mechanism enables information to be passed along the vehicle platoon, allowing each vehicle to benefit from the observations of others and maintain high reliability over extended durations through continuous information refreshment.
2Area of stationary object
If a road network enabling automatic driving in a wide area is deployed, then the coverage area increases, but the complexity of generating and maintaining information increases
Solution Approach 1:
The system segments the information collection task by assigning it to individual vehicles that encounter different road sections. Each vehicle independently collects and transmits information about its local environment, dividing the overall task of mapping and monitoring a wide area into manageable segments that can be processed and transmitted in parallel across multiple vehicles.
Solution Approach 2:
Each vehicle serves itself by collecting, processing, and transmitting its own traveling environment information. This self-service approach eliminates the need for centralized data collection infrastructure, allowing the road network to expand coverage area without proportionally increasing system complexity. Vehicles autonomously contribute to the collective knowledge base.
3Measurement precision
If real-time traveling environment information is used for navigation, then the accuracy of navigation control improves, but the time delay in information availability increases
Solution Approach 1:
The system performs preliminary information collection by preceding vehicles that travel ahead and gather data about future traveling environments. This advance collection reduces the time delay for following vehicles, as they receive pre-collected information about obstacles and conditions before actually encountering them, maintaining high accuracy while minimizing latency.
Solution Approach 2:
The communication interface provides continuous feedback loops where vehicles transmit their detected environment information to others in real-time or near real-time. This feedback mechanism ensures that navigation systems have access to current and accurate traveling environment data, allowing dynamic adjustment of navigation control based on the latest information from the platoon.
Data Source
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AI summary
A system for an autonomous vehicle that receives driving environment information corresponding to a driving environment provided by another autonomous vehicle, and determines a navigation route based on a degree of reliability of the driving environment information provided by the another autonomous vehicle.