Navigation System Routing Parameter Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Navigational guidance systems face challenges in accurately updating routing parameters to account for user vehicle routing restrictions, particularly when switching between different modes of transport, leading to potential safety hazards and inefficient routes due to incorrect parameter settings.
Innovation Solution
A method that utilizes previously traveled route data to update routing parameters by analyzing road segment attributes, applying penalty functions, and employing machine learning algorithms to determine optimal routing parameters, ensuring accurate route generation based on user vehicle combinations and transport modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If routing parameters are manually configured by users, then users can specify their preferences, but the system cannot automatically adapt to user behavior and vehicle restrictions
Solution Approach 1:
The system automatically updates routing parameters by analyzing previously traveled route data without requiring user intervention. The navigation system serves itself by learning from historical route traces and road segment attributes to adapt to user preferences and vehicle restrictions, eliminating the need for manual parameter configuration.
Solution Approach 2:
The system uses feedback from previously traveled routes to continuously improve routing parameter accuracy. By analyzing historical route data and comparing actual user behavior with recommended routes, the system adjusts parameters to better match user preferences and vehicle capabilities over time.
2Measurement precision
If the system provides detailed routing parameters, then route accuracy can be improved, but the complexity of the system increases
Solution Approach 1:
The system automatically manages the complexity of routing parameters through self-learning from historical data. Instead of requiring users to understand or configure multiple parameters, the system autonomously analyzes route traces and updates parameters, hiding the complexity while maintaining high accuracy.
Solution Approach 2:
The system dynamically adjusts routing parameters based on analyzed route data and road segment attributes. By automatically modifying parameters such as route preferences and restrictions based on learned user behavior and vehicle characteristics, the system achieves high accuracy without exposing users to parameter complexity.
3Measurement precision
If routing parameters are not updated based on user behavior, then the system remains simple to operate, but route accuracy and safety deteriorate
Solution Approach 1:
The navigation system automatically updates routing parameters by analyzing its own historical route data without user intervention. This self-service approach maintains operational simplicity while continuously improving route accuracy and safety by learning from actual user behavior and vehicle performance.
Solution Approach 2:
The system performs preliminary analysis of previously traveled routes to pre-update routing parameters before generating new route recommendations. By proactively learning from historical data and preparing updated parameters in advance, the system ensures high route accuracy is ready when users need it, without requiring users to manually configure anything.
Data Source
Figure 1
Figure 2a~2b
Figure 3a
AI summary
There is provided a method (and corresponding systems) of navigational guidance for a navigational system, the method comprising the following steps. Obtaining one or more route traces of previously travelled routes of a user of the navigational system, each route comprising a plurality of road segments. Updating an initial set of routing parameters of the navigational system based on attributes of the road segments of the previously travelled routes; generating, based on the updated set of routing parameters, a route between an initial location and a requested destination location. Providing navigational guidance to the user for following the generated route, based on the generated route and a current location of the user.