Dynamic Transportation Matching System Route Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing on-demand transportation systems face challenges in determining the most convenient and efficient pick-up and drop-off points and routes, leading to suboptimal user experiences and increased driver idle time due to computational intensity and lack of flexibility in traditional matching systems.
Innovation Solution
The implementation of a dynamic transportation matching system that calculates and optimizes routes by incorporating pre-pickup and post-drop-off walks, accounting for side-of-street information, and generating alternate waypoints to minimize trip time and improve user convenience, while providing users with options for selecting optimal pick-up and drop-off locations through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional matching systems are used to determine pick-up and drop-off points, then the system complexity is reduced, but the user experience and route optimization are worsened due to computational intensity constraints
Solution Approach 1:
The system segments the route determination problem into multiple discrete components: generating candidate pick-up points, generating candidate drop-off points, calculating convenience scores for each candidate, and selecting the optimal combination. This segmentation allows the complex optimization problem to be broken down into manageable steps that can be processed efficiently while still providing comprehensive route optimization options.
Solution Approach 2:
The system performs preliminary actions by pre-generating multiple candidate pick-up and drop-off points along with their associated convenience scores before the final matching decision. This allows the system to have optimization options ready in advance, reducing computational intensity during the actual matching process while maintaining high-quality route recommendations.
2Use of energy by moving object
If traditional matching systems are used, then computational intensity is reduced, but driver idle time increases due to lack of route optimization
Solution Approach 1:
The system dynamically adjusts pick-up and drop-off locations based on real-time conditions such as traffic patterns, road closures, and driver availability. By making the route determination dynamic rather than static, the system can optimize routes adaptively to minimize driver idle time and improve efficiency without requiring excessive computational resources for every possible scenario.
Solution Approach 2:
The system changes key parameters such as pick-up location, drop-off location, and route characteristics to optimize the balance between computational intensity and driver idle time. By adjusting these parameters based on convenience scores and current conditions, the system achieves route optimization that reduces driver waiting time while maintaining manageable computational requirements.
3Adaptability or versatility
If flexible pick-up and drop-off locations are implemented, then user convenience is improved, but the computational problem becomes more intensive
Solution Approach 1:
The system segments the flexible location selection into discrete candidate points with pre-calculated convenience scores. Instead of evaluating every possible continuous location, the system divides the area into specific candidate pick-up and drop-off points, making the flexible selection computationally manageable while still providing users with multiple convenient options.
Solution Approach 2:
The system uses approximate convenience scores that are calculated efficiently for each candidate location rather than performing exhaustive optimization calculations. These scores serve as good-enough approximations that enable flexible pick-up and drop-off selection without requiring computationally intensive exact solutions for every scenario.
Data Source
AI summary
The disclosed computer-implemented method may include (i) receiving, by a dynamic transportation matching system, a request for transportation between initial waypoints, (ii) calculating, by the dynamic transportation matching system, a value metric for an initial driving route between the initial waypoints (iii) calculating a value metric for a walk-enabled driving route that comprises at least one alternate waypoint that is within a predetermined walking range of one of the initial waypoints, and (iv) improving, by the dynamic transportation matching system, a value of fulfilling the request for transportation by determining that a difference between the value metric of the walk-enabled driving route and the value metric of the initial driving route satisfies a walking-value threshold and selecting, based on the determination that the difference satisfies the walking-value threshold, the walk-enabled driving route for fulfilling the request for transportation. Various other methods, systems, and computer-readable media are also disclosed.