Rideshare Prescheduling with Unknown Pickup and Shared Route Assignment
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Solution Overview
Problem
Current ridesharing management systems face challenges in efficiently managing fleets of vehicles, including discrepancies in passenger counts, optimizing routes for electric vehicles, and directing vehicles to charging stations based on predicted demand, which can lead to inefficiencies and increased operational costs.
Innovation Solution
The implementation of a system that includes sensors in vehicles to accurately count passengers, processors to compare scheduled and actual passenger numbers, and a centralized management system that directs electric vehicles to charging stations based on historical demand data and current battery levels, optimizing routes to ensure vehicles are charged in time for peak demand periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are installed in vehicles to accurately count passengers, then passenger counting accuracy is improved, but device complexity increases
Solution Approach 1:
The patent uses sensors as intermediary devices installed in the vehicle to detect and count passengers automatically. These sensors act as mediators between the physical presence of passengers and the digital record of passenger count, eliminating the need for manual counting while improving accuracy.
Solution Approach 2:
The patent replaces manual passenger counting (mechanical/human operation) with automated sensor-based detection. This substitution eliminates human error and labor while providing continuous, accurate monitoring of passenger numbers throughout the vehicle.
2Productivity
If electric vehicles are directed to charging stations based on predicted demand rather than closest location, then operational efficiency is improved, but travel time increases
Solution Approach 1:
The patent applies preliminary action by directing electric vehicles to charging stations in advance of when they are absolutely needed. By using predicted demand data, the system schedules charging trips before peak demand periods, ensuring vehicles are ready for upcoming high-demand periods rather than reacting to immediate needs.
Solution Approach 2:
The system enables self-service by allowing the fleet management algorithm to autonomously schedule and route vehicles to charging stations based on predictive analytics. The system independently optimizes charging schedules without requiring manual intervention, balancing individual vehicle needs with overall fleet productivity.
3Reliability
If vehicles are charged during low-demand periods, then vehicle availability during peak demand is improved, but charging infrastructure load during low-demand periods increases
Solution Approach 1:
The patent uses preliminary action by scheduling vehicle charging during low-demand periods before peak demand occurs. This advance charging ensures vehicles are available and charged during high-demand periods, improving reliability without requiring infrastructure to handle peak loads simultaneously for all vehicles.
Solution Approach 2:
The system implements periodic action by distributing charging loads across different time periods rather than concentrating all charging at once. Vehicles are cycled through charging schedules that stagger their charging times, creating a periodic pattern that smooths infrastructure load while ensuring availability when needed.
Data Source
AI summary
A system for directing a ridesharing vehicle may include a communications interface for receiving requests for shared-rides. The system may also include at least one processor programmed to: receive during a first time period a first request from a first user; receive during a first time period a second request from a second user; during the third time period, receive current vehicle location data for ridesharing vehicles, process the first and second requests, and the vehicle location data to identify a specific ridesharing vehicle for transporting both the first and second users, and calculate a ridesharing route for picking up and dropping off the first and second users; and after the third time period and before the second time period, wireless transmit to the specific ridesharing vehicle, the calculated route for picking up the first and second users during the second time period.