Dynamic Ridesharing Vehicle Assignment Based on ETA
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Solution Overview
Problem
Current vehicle ridesharing systems face challenges in efficiently managing large fleets and adapting to unanticipated events, such as traffic changes or rider cancellations, which can lead to delays and inefficiencies in route planning and vehicle allocation.
Innovation Solution
A system that uses a communications interface and processor to receive ride requests and location data from users and vehicles, allowing for real-time assignment of vehicles, re-routing, and re-assignment of riders to optimize pick-up and drop-off locations and times, even in the face of unanticipated events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a ridesharing vehicle is assigned to pick up multiple users at different locations, then vehicle utilization increases, but the complexity of route planning and vehicle allocation increases
Solution Approach 1:
The system dynamically adjusts vehicle assignments and routes in real-time based on unanticipated events. When a vehicle cannot pick up a user as scheduled, the system automatically reassigns the user to a different vehicle and recalculates routes, transforming a static assignment system into a dynamic one that adapts to changing conditions.
Solution Approach 2:
The system implements feedback loops where unanticipated events (such as traffic changes or rider cancellations) are detected and trigger automatic reassignment processes. The system monitors vehicle locations, user pick-up status, and event conditions, then feeds this information back into the assignment algorithm to optimize vehicle allocation and route planning.
2Reliability
If the system dynamically reassigns users to different vehicles due to unanticipated events, then service reliability improves, but the time required for reassignment and route recalculation increases
Solution Approach 1:
The system pre-calculates alternative routes and identifies backup vehicles before unanticipated events occur. By having pre-computed fallback options and maintaining a pool of available vehicles, the system can execute reassignments quickly when events occur, reducing the actual reassignment time while maintaining service reliability.
Solution Approach 2:
The system implements automated self-service reassignment where the algorithm automatically detects unanticipated events, identifies suitable alternative vehicles, and reassigns users without manual intervention. This automation eliminates delays associated with human decision-making and enables rapid response to changing conditions.
3Productivity
If pick-up locations are determined to be other than the starting point, then vehicle routing efficiency improves, but user convenience deteriorates
Solution Approach 1:
The system adds the dimension of spatial flexibility by allowing pick-up locations to be anywhere along the vehicle's route, not just at the user's starting point. This transforms the traditional one-to-one pickup model into a many-to-many model where multiple users can be picked up at optimized locations along the vehicle's path, improving routing efficiency while managing user convenience through notification and choice.
Data Source
AI summary
Systems and methods related to ridesharing may involve receiving a ride request from a user including a desired destination and information associated with a current location of the user, and receive location information of on-demand and of fixed-line ridesharing vehicles and based on the received location information, identify a fixed-line ridesharing vehicle available to pick from a first pick-up location identify an on-demand ridesharing vehicle available to pick from a second pick-up location, both locations other than the current location of the user, determine a first value and a second value indicative of a time duration for the fixed-line and one demand ridesharing vehicles to arrive at the first and second pick-up locations, respectively, and when the first value is less than the second value, inform the user that the fixed-line ridesharing vehicle is enroute and direct the user to the first pick-up location.