Autonomous Robot Stop-Area Prioritization in Mixed Traffic Zones
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Solution Overview
Problem
Existing robot control systems fail to adequately consider the stop position of mobile objects in dynamic environments, particularly in areas where pedestrians and vehicles coexist, leading to potential interference and inefficiencies.
Innovation Solution
A control system that uses processors to recognize objects, identify candidate stop areas, and prioritize them based on information from external devices, such as past traffic flow, size, and distance, to determine optimal stop positions, ensuring minimal interference and efficient movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the mobile object stops at any candidate area, then the stopping flexibility is improved, but the interference with pedestrians and traffic flow worsens
Solution Approach 1:
The patent applies local quality by assigning different priority levels to different candidate stop areas based on their specific characteristics. Each area is evaluated individually using multiple criteria (traffic flow, pedestrian activity, distance to target, area size) to determine its suitability, rather than treating all areas uniformly. This allows the system to select stop positions that are locally optimal for minimizing interference while maintaining flexibility.
Solution Approach 2:
The system changes parameters by evaluating candidate areas based on multiple varying parameters including traffic flow volume, pedestrian activity levels, distance to target location, and relative area size. These parameters are dynamically weighted and combined to calculate priority scores, allowing the system to adapt to different environmental conditions and select appropriate stop positions.
2Measurement precision
If multiple candidate areas are evaluated with multiple criteria, then the stop position accuracy is improved, but the computational complexity worsens
Solution Approach 1:
The evaluation process is segmented into distinct sequential steps: first identifying candidate areas, then evaluating each against multiple independent criteria (traffic flow, pedestrian activity, distance, size), calculating priority scores, and finally selecting the optimal area. This segmentation allows complex multi-criteria evaluation to be broken down into manageable computational tasks that can be processed efficiently.
Solution Approach 2:
The system performs preliminary actions by pre-identifying and storing information about multiple candidate stop areas before making a selection decision. This includes pre-calculating area sizes, storing traffic flow data, and maintaining lists of candidate positions, which reduces the computational burden during real-time decision-making.
Data Source
AI summary
A control system is a control system that controls a mobile object moving autonomously in an area in which a pedestrian is able to move, and recognizes objects around the mobile object, identifies a candidate area that is an area in which the mobile object stops when a specific event occurs, refers to information on a plurality of candidate areas, identifies the candidate area that is the candidate area that is obtained by excluding the candidate area in which the object interferes from the plurality of candidate areas and that corresponds to a priority, and moves the mobile object to the identified candidate area.