Autonomous Vehicle Wait-Time Allocation for Multi-Stop Trips
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Solution Overview
Problem
Autonomous vehicles face inefficiencies in managing waiting time at intermediate destinations during multi-destination trips, leading to unproductive vehicle idle time and reduced trip servicing capacity.
Innovation Solution
A fleet management system determines the waiting time at intermediate destinations based on passenger input and various factors, including historical data, passenger characteristics, and third-party data, then optimizes vehicle activities such as maintenance, short or long duration trips, and parking strategies to minimize idle time and maximize trip servicing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the autonomous vehicle waits at the intermediate destination for the passenger to return, then the passenger can complete their errand or activity, but the vehicle experiences unproductive idle time reducing fleet efficiency
Solution Approach 1:
The system performs preliminary actions by determining the optimal activity for the vehicle before the passenger returns. The fleet management system calculates waiting time and pre-determines whether the vehicle should perform maintenance, accept short trips, or park, thereby preparing the vehicle for productive use during the passenger's absence rather than simply idling
Solution Approach 2:
The vehicle is assigned to perform maintenance activities or other trips during waiting time, making the waiting period productive. The system enables the vehicle to service itself through maintenance or contribute to fleet productivity through additional trips, transforming unproductive idle time into valuable service time
2Reliability
If the vehicle performs maintenance during waiting time, then vehicle reliability improves, but the time available for trip servicing is reduced
Solution Approach 1:
The system changes the time parameter by utilizing previously idle waiting time for maintenance activities. By calculating the optimal waiting time and assigning maintenance during this period, the system transforms lost time into productive maintenance time, improving reliability without extending the overall trip duration
Solution Approach 2:
The system converts the harmful effect of idle waiting time into a beneficial opportunity for maintenance. What was previously unproductive downtime is now transformed into valuable maintenance time, improving vehicle reliability while maintaining the same trip servicing schedule
3Productivity
If the vehicle accepts short trips during waiting time, then fleet productivity increases, but the risk of missing the passenger's return increases
Solution Approach 1:
The system continuously monitors the passenger's expected return time and adjusts vehicle assignments accordingly. By establishing a buffer period between the vehicle's return from short trips and the passenger's expected arrival, the system provides feedback control that ensures reliable passenger pickup while maximizing productivity
Solution Approach 2:
The system accepts that the vehicle may arrive slightly earlier than the passenger's exact return time by building in a buffer period. This partial action approach ensures the vehicle is ready to pick up the passenger reliably while still utilizing the majority of waiting time for productive short trips
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.