Driverless Transport Vehicle Route Optimization
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Solution Overview
Problem
Existing driverless transport vehicles lack an efficient method to determine the quickest route to their destination, especially in dynamic environments where route passability and travel times can change, leading to suboptimal travel times.
Innovation Solution
A method that utilizes a graph-based strategy calculation, where nodes represent intermediate points and edges represent route sections with passability and travel time information, allowing the vehicle to automatically determine the fastest route by recalculating the strategy based on current conditions and updating information in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the driverless transport vehicle uses traditional route planning methods, then the route can be determined, but the travel time is not optimized and the vehicle cannot adapt to dynamic changes in route passability
Solution Approach 1:
The patent applies dynamics by making the route planning system adaptive to changing conditions. The graph structure and strategy calculation are updated in real-time based on current time and changing passability conditions of route sections, allowing the vehicle to dynamically adjust its path rather than following a static pre-planned route
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors the current time and passability status of route sections, then uses this information to recalculate the optimal strategy. The strategy calculation feeds back into the route selection, creating a closed-loop system that adapts to environmental changes
2Productivity
If the driverless transport vehicle recalculates strategy in real-time based on current conditions, then the travel time is optimized, but the computational complexity increases
Solution Approach 1:
The patent segments the environment into a graph structure with discrete nodes (intermediate points) and edges (route sections). This segmentation allows the complex continuous navigation problem to be broken down into manageable discrete calculations, where the strategy is determined by evaluating specific graph edges rather than continuous space
Solution Approach 2:
The patent performs preliminary action by pre-calculating and storing the graph structure with all possible routes, passability information, and travel times before the vehicle needs to navigate. This pre-processing of route information enables faster real-time decision-making during actual traversal, as the system only needs to evaluate pre-computed options rather than calculating from scratch
Data Source
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AI summary
The invention relates to a driverless transport vehicle (1), a system comprising a computer (10) and a driverless transport vehicle (1), and a method for operating a driverless transport vehicle (1). The driverless transport vehicle (1) is intended to travel automatically along route segments (41-47) from a starting point (SP) to a destination point (ZP).