Electric Ridesharing Fleet Routing With Charging Stop Optimization
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Solution Overview
Problem
Existing ridesharing systems do not effectively manage fleets of electrically-powered vehicles, particularly in optimizing routes and battery charging, leading to inefficiencies and potential range anxiety.
Innovation Solution
A system that includes GPS data for vehicle location and battery charge management, selecting non-closest charging stations, and optimizing routes to ensure vehicles are charged efficiently while accommodating multiple passengers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the system directs electrically-powered ridesharing vehicles to the closest charging station, then the charging time is reduced, but the overall fleet efficiency deteriorates due to suboptimal route planning and inadequate consideration of passenger pickup/dropoff requirements
Solution Approach 1:
The system segments the fleet management problem into multiple optimization objectives: individual vehicle charging needs, overall fleet productivity, passenger pickup/dropoff requirements, and energy consumption. By evaluating multiple candidate charging stations and selecting based on a composite score that balances these segmented objectives, the system resolves the contradiction between minimizing charging time and maximizing fleet efficiency.
Solution Approach 2:
The system changes the decision parameter from a simple distance-based selection to a multi-parameter evaluation that includes charging time, fleet productivity impact, passenger service requirements, and energy consumption. This parameter transformation allows the system to optimize for overall efficiency rather than just charging speed.
2Productivity
If the system optimizes routes to accommodate multiple passengers and charging stops, then the vehicle utilization rate is improved, but the route complexity increases leading to longer travel distances and time
Solution Approach 1:
The system performs preliminary route optimization by pre-calculating optimal routes that integrate multiple passenger pickups, dropoffs, and charging stops before the vehicle departs. By planning the entire multi-stop route in advance rather than making sequential decisions, the system reduces actual route complexity while maintaining high vehicle utilization.
Solution Approach 2:
The system implements dynamic route adjustment capabilities that allow real-time modifications to the optimized route based on changing conditions such as new ride requests, traffic conditions, or battery status. This dynamic adaptation maintains route efficiency while accommodating the complexity of multiple stops.
3Speed
If the system selects charging stations based solely on proximity, then the charging speed is maximized, but the energy consumption increases due to inefficient routing and lack of charging station optimization
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor battery status, charging station availability, and route efficiency. This feedback allows the system to adjust charging station selection to balance charging speed with energy consumption, choosing stations that provide optimal charging rates while minimizing detour distances and overall energy use.
Data Source
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AI summary
The present disclosure relates to systems and methods for managing a fleet of ridesharing vehicles. In some implementations, the fleet of ridesharing vehicles may include electrically-powered ridesharing vehicles. The systems and methods may manage a charging schedule for multiple charging stations for a fleet of electrically-powered ridesharing vehicles, plan a route for an electrically-powered ridesharing vehicle to account for a current battery charge of the electrically-powered ridesharing vehicle, plan a route for an electrically-powered ridesharing vehicle to account for battery charging stops, and making vehicle or passenger assignments based on a proximity of an electrically-powered ridesharing vehicle to a charging station. Additionally, the systems and methods may provide different levels of service for ridesharing.