Ride-Sharing Route Search Balancing Safety and Pickup Probability
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Solution Overview
Problem
Ride-sharing services face challenges in increasing utilization rates while ensuring traveling safety, as existing route search techniques prioritize detour routes for better sensor recognition accuracy over high-pickup probability routes, leading to potential safety risks and reduced service efficiency.
Innovation Solution
A route search device and method that calculates standard, high-frequency, and low-frequency routes based on sensor recognition levels, pedestrian distribution, and weather conditions, selecting routes that balance safety and pickup probability by comparing recognition levels with reference thresholds and determining passenger safety conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a detour route is selected to improve sensor recognition accuracy and traveling safety, then traveling safety is improved, but pickup probability decreases
Solution Approach 1:
The route selection is made dynamic by adjusting the route type based on real-time recognition accuracy levels. When recognition accuracy is high, the system dynamically switches to high-frequency routes to maximize pickups. When recognition accuracy is low, it dynamically switches to low-frequency routes to ensure safety, thereby adaptively balancing safety and productivity based on current conditions
Solution Approach 2:
The system changes the parameter of route frequency selection based on the recognition accuracy parameter. By monitoring recognition accuracy as a key parameter and adjusting the route frequency parameter accordingly, the system resolves the contradiction between safety (low frequency) and productivity (high frequency) through parameter-based decision making
2Productivity
If a standard route with shortest requested time is selected, then productivity is improved, but traveling safety may be compromised due to lower sensor recognition accuracy
Solution Approach 1:
The system dynamically adjusts route selection based on real-time recognition accuracy conditions. When recognition accuracy is sufficient, it dynamically chooses standard routes for efficiency. When recognition accuracy deteriorates, it dynamically switches to safer low-frequency routes, making the safety-productivity balance adaptive rather than static
Solution Approach 2:
The system implements feedback by continuously monitoring recognition accuracy and using this information to adjust route selection. The recognition accuracy serves as feedback that informs the route choice, creating a closed-loop system where safety conditions directly influence productivity decisions
Data Source
AI summary
A route search device includes a memory and a processor. The processor performs search processing for a route from a current position to a destination of a ride-sharing vehicle based on data stored in the memory. A standard route with the shortest requested time from the current position to the destination is calculated in the search processing. A high-frequency route with a frequency of encountering a pedestrian between the current position and the destination that is higher than the standard route is also calculated in the search processing. A recognition level is compared with a reference level in the search processing. When the recognition level is equal to or less than the reference level, the standard route is selected as a final route. When the recognition level is higher than the reference level, the high-frequency route is selected as the final route.