Vehicle Map Update Control for Area-Based Road Change Detection
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Solution Overview
Problem
Conventional map updating technologies face challenges in maintaining accurate map data, particularly in areas with varying traffic conditions, where excessive data communication occurs in high-traffic areas and insufficient data is collected in low-traffic areas, leading to inefficiencies and inaccuracies in map updates.
Innovation Solution
An information processing apparatus that divides a map into multiple areas and determines the necessity of updates based on changes in road shape and vehicle activity, selectively requesting detection data from vehicles capable of high-accuracy sensing to improve data freshness and reduce unnecessary communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map updating is performed using data from all vehicles in all areas, then map data accuracy is improved, but communication load and processing complexity increase excessively
Solution Approach 1:
The map area is divided into multiple regions, and each region is evaluated independently for update necessity. This segmentation allows the system to process only specific areas that require updates rather than handling the entire map, thereby reducing communication load while maintaining accuracy in critical areas.
Solution Approach 2:
Different update strategies are applied to different regions based on their specific characteristics. High-traffic areas with frequent changes receive more frequent updates, while low-traffic areas use less frequent updates. This local differentiation optimizes resource allocation and reduces overall communication complexity.
2Loss of information
If map updating frequency is increased in high-traffic areas, then map data freshness is improved, but communication traffic and energy consumption increase
Solution Approach 1:
The update frequency is made dynamic and adaptive based on real-time traffic conditions and change detection. Areas with detected changes trigger updated requests, while stable areas maintain lower update frequencies. This dynamic adjustment ensures data freshness where needed while conserving communication energy in stable regions.
Solution Approach 2:
The system uses feedback from vehicle detection data and change amount calculations to adjust update frequencies. When changes exceed thresholds or vehicle activity indicates potential updates, the system increases update frequency for those specific areas, creating a feedback loop that optimizes data freshness versus energy consumption.
3Reliability
If update requests are sent to all vehicles, then data coverage is improved, but processing load and system complexity increase
Solution Approach 1:
The system extracts and identifies only the essential update requests based on change detection and area evaluation. Instead of sending requests to all vehicles universally, it selectively generates requests only for areas where changes are detected, thereby maintaining data coverage reliability while significantly reducing processing load.
Solution Approach 2:
The system changes parameters such as update thresholds and request frequencies based on area characteristics and detected changes. By adjusting these parameters dynamically, the system optimizes the balance between data coverage and processing efficiency, sending requests only when and where necessary.
Data Source
AI summary
An information processing apparatus is configured to distribute, to a vehicle, a map showing a road shape of a road on which the vehicle runs makes, for each of a plurality of areas and determine whether it is necessary to update the map of that area. The determination is based on at least either an amount of change from the road shape shown by the map to the road shape at a present time in each of the plurality of areas or the number of occurrences of a predetermined action of a vehicle having run through in each of the plurality of areas.