Autonomous Route Planning Based on Vehicle Sensor Capabilities
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current automatic driving technologies face challenges in navigating non-typical environments due to limitations in sensor accuracy, particularly in adverse weather conditions, leading to potential safety issues and unnecessary detours, as they do not adequately consider the specific sensor capabilities of individual vehicles.
Innovation Solution
An information processing apparatus and method that acquires traveling possibility or impossibility information based on sensor categories and determines the most appropriate route for a vehicle by classifying areas according to the sensor categories of the vehicle, allowing for real-time route planning to avoid critical states and ensure safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a vehicle uses sensors with limited accuracy (such as radar in rain or fog), then the vehicle can maintain basic autonomous traveling in typical environments, but detection accuracy of road shoulders and obstacles decreases in adverse weather conditions
Solution Approach 1:
The system dynamically changes the determined route based on current weather conditions and sensor capabilities. When adverse weather is detected, the route is automatically adjusted to avoid areas where detection accuracy is insufficient, transforming the static route planning into a dynamic adaptation process that responds to environmental changes.
Solution Approach 2:
The invention changes the operational parameters of the sensing system by selecting different routes based on sensor performance thresholds. When detection accuracy falls below required levels due to weather conditions, the system parameter changes the route to maintain safe operation margins.
2Reliability
If a vehicle avoids all areas with potential detection limitations, then safety in adverse weather is improved, but unnecessary detours increase and route efficiency decreases
Solution Approach 1:
The system applies local quality by making route decisions specific to the vehicle's sensor capabilities and the local environmental conditions. Rather than avoiding all potentially problematic areas universally, the route is adjusted only for specific segments where the vehicle's sensors would be insufficient, allowing efficient passage through areas where the vehicle's sensors are adequate.
Solution Approach 2:
The invention uses partial action by applying route adjustments only when and where necessary based on the conjunction of weather conditions and sensor capabilities. The system does not over-avoid areas, but instead makes targeted route modifications only for segments where detection accuracy would be insufficient.
3Adaptability or versatility
If a vehicle includes additional sensors to handle narrow roads and oncoming traffic, then the ability to move backward and yield is improved, but device complexity and cost increase
Solution Approach 1:
The system achieves universality by creating a route determination function that serves multiple purposes: it plans routes for various vehicle types, adapts to different weather conditions, and ensures safety for diverse sensor configurations. This single multi-functional system replaces the need for vehicle-specific hardware modifications.
Solution Approach 2:
The invention introduces an intermediary route determination system that mediates between the vehicle's existing sensors and the road environment. Rather than requiring every vehicle to have comprehensive sensors for all situations, the intermediary system processes sensor data and selects routes that match the vehicle's actual capabilities.
4Adaptability or versatility
If a vehicle operates in environments beyond its sensor capabilities, then route flexibility is improved, but the risk of critical states and accidents increases
Solution Approach 1:
The system applies preliminary anti-action by proactively preventing the vehicle from entering critical states. The route determination function anticipates potential detection failures by analyzing weather conditions and sensor capabilities beforehand, and selects routes that prevent the vehicle from operating in environments where its sensors would be insufficient.
Data Source
AI summary
An information processing method, and a program that allow travelable areas to be appropriately selected according to performances, functions, and types of sensors that a vehicle includes, to realize appropriate automatic driving while avoiding critical states. Traveling possibility or impossibility information of every sensor category set according to types and performances of sensors with which vehicles are equipped, of a path of every area is acquired, and it is determined whether or not a route to a destination is most appropriate, on the basis of the sensor category of an own car, and the traveling possibility or impossibility information. If the route is not most appropriate, replanning is performed.