Autonomous Vehicle Trip Scheduling for Intermediate Stop Wait Times
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Solution Overview
Problem
Autonomous vehicle fleets face inefficiencies in managing waiting times at intermediate destinations during trips with multiple stops, leading to unproductive vehicle downtime.
Innovation Solution
A method for managing autonomous vehicle fleets involves receiving information on intermediate and final destinations, determining waiting times based on historical data and passenger expectations, and optimizing vehicle activities during waiting periods to maximize trip servicing and reduce downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle waits at the intermediate destination for the passenger to return, then the passenger can complete their errands, but the vehicle experiences unproductive downtime reducing fleet efficiency
Solution Approach 1:
The system enables the vehicle to perform useful actions during waiting time by dispatching it on additional trips or tasks while it remains in the vicinity of the intermediate destination. This maintains continuous productive operation rather than idle waiting, thereby resolving the contradiction between passenger convenience and vehicle utilization efficiency
Solution Approach 2:
The system preliminarily determines the optimal waiting time for the vehicle at the intermediate destination based on historical data and trip patterns. By pre-calculating when the vehicle should return to pick up the passenger, the system minimizes idle waiting time while ensuring passenger convenience, thus improving overall fleet productivity
2Reliability
If the vehicle returns to the intermediate destination frequently to check for passenger return, then passenger pickup reliability improves, but energy consumption and operational time increase
Solution Approach 1:
Instead of continuous monitoring, the system implements periodic checks at optimized intervals. The vehicle returns to the intermediate destination at predetermined time points based on calculated waiting durations, maintaining reliable passenger pickup while minimizing unnecessary trips and time loss
Solution Approach 2:
The system uses feedback from historical waiting time data and real-time trip information to dynamically adjust the vehicle's return schedule. This feedback mechanism ensures the vehicle returns at optimal times to pick up passengers, balancing reliability with time efficiency by avoiding both excessive frequency and insufficient monitoring
3Productivity
If the fleet management system optimizes vehicle dispatching to minimize idle time, then overall fleet productivity improves, but system complexity increases
Solution Approach 1:
The system automatically determines optimal waiting times and vehicle dispatch schedules using historical data and algorithmic optimization without requiring complex manual intervention. The autonomous decision-making capability reduces the need for complex human oversight while maintaining high fleet efficiency, thus improving productivity without proportionally increasing system complexity
Data Source
AI summary
Aspects of the disclosure relate to a method of managing a fleet of autonomous vehicles providing trip services. The method includes receiving information identifying an intermediate destination and a final destination for a trip. In this example, the intermediate destination is a destination where an autonomous vehicle will drop off and wait for a passenger in order to continue the trip, and the final destination is a destination where the trip ends. The method also includes determining an amount of waiting time the vehicle is likely to be waiting for the passenger at the intermediate destination, determining how a vehicle of the fleet of autonomous vehicles should spend the amount of waiting time, and sending an instruction to the vehicle, based on the determination of how the vehicle should spend the amount of waiting time.