Blacklist Re-Navigation for Driverless Road Blockages
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driverless vehicle systems lack the ability to respond flexibly to temporary road blockages, as they cannot continue driving until the obstruction is cleared, leading to passive waiting and inability to adapt to changing road conditions.
Innovation Solution
A blacklist-based re-navigation method and apparatus that detects obstacles in the driverless vehicle's path, generates a blacklist with the affected road information, and reports it to the navigation system to re-plan a route, allowing the vehicle to bypass or avoid the blockage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the driverless vehicle follows the planned driving route strictly, then the driving path is predetermined and simple to execute, but the vehicle cannot respond to temporary road blockages and must passively wait
Solution Approach 1:
The system pre-generates multiple alternative driving routes in advance and stores them in the navigation system. When a road blockage is detected, the vehicle can immediately switch to a pre-prepared alternative route without requiring complex real-time recalculation, thus improving adaptability while keeping the system relatively simple
Solution Approach 2:
The system continuously monitors road conditions through sensing devices and provides feedback to the navigation system. When blockages are detected, this feedback triggers automatic route switching to alternative paths, enabling the vehicle to adapt dynamically to changing road conditions while maintaining systematic control
2Productivity
If the driverless vehicle waits for road congestion to clear, then the vehicle maintains safety by avoiding blocked roads, but driving time is extended and efficiency is reduced
Solution Approach 1:
Alternative routes are pre-calculated and stored before needed, allowing the vehicle to switch paths immediately upon detecting blockages. This eliminates waiting time while ensuring safety through pre-validated alternative paths that have been checked for feasibility
Solution Approach 2:
The navigation system dynamically adjusts the driving route based on real-time road conditions. The system transitions from static route following to dynamic route adaptation, automatically selecting the most appropriate path while maintaining safety standards and improving driving efficiency
3Adaptability or versatility
If the navigation system re-plans route in real-time based on blacklist feedback, then the vehicle can avoid blockages effectively, but the system complexity and computational load increase
Solution Approach 1:
Multiple alternative routes are pre-generated and stored in the navigation system before any blockage occurs. The blacklist mechanism simply provides feedback about which pre-existing routes to avoid, and the system switches to the next available alternative. This approach provides effective route re-planning without requiring complex real-time optimization algorithms
Solution Approach 2:
The system uses a blacklist copy mechanism where blockage information is copied and fed back to the navigation system. The navigation system then selects from pre-existing alternative route copies, avoiding the need for complex real-time route generation while maintaining adaptability through systematic selection from prepared options
Data Source
AI summary
A blacklist-based re-navigation method and apparatus, and a computer readable storage medium are provided. The blacklist-based re-navigation method includes: detecting whether an obstacle is in a front area of a driverless vehicle in a driving process of the driverless vehicle; if an obstacle is detected in the front area, generating a blacklist associated with the obstacle, wherein the blacklist includes a road on which the obstacle is located; and reporting the blacklist to a navigation system, wherein the navigation system re-plans a navigation route according to the road on which the obstacle is located.