Autonomous Vehicle Pickup Wait Times for Congestion-Aware Stops
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing transportation services using autonomous vehicles lack a realistic wait time estimation for passenger pickups due to environmental factors like congestion, as fixed wait times are not applicable to autonomous vehicles without human drivers.
Innovation Solution
A method and system that determine a subset of potential pickup locations by considering factors such as estimated time of arrival, walking distance, congestion impact scores, and location characteristics, and assign wait times based on these factors to provide users with informed choices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed wait time is provided for autonomous vehicle pickups, then the system is simple to operate, but the wait time estimation is not realistic due to environmental factors like congestion
Solution Approach 1:
The system segments the pickup location analysis into multiple candidate locations, each with its own wait time estimation. Instead of providing a single fixed wait time, the system divides the pickup area into several potential spots and calculates individual wait times for each, allowing users to choose based on their preferences.
Solution Approach 2:
The wait time estimation is made dynamic by adjusting it based on environmental factors such as traffic congestion, location characteristics, and historical data. Each candidate pickup location receives a dynamically calculated wait time that reflects current and predicted conditions, rather than using a static fixed value.
2Reliability
If multiple potential pickup locations are provided with different wait times, then the reliability of wait time estimation is improved, but the device complexity increases
Solution Approach 1:
The system provides a subset of candidate pickup locations (e.g., top 3-5 options) rather than analyzing every possible location. This partial action approach delivers sufficient reliability for user decision-making while limiting the complexity increase to a manageable number of options.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically analyzes multiple factors (congestion, location characteristics, historical data) and translates them into simplified wait time estimates for each candidate location. This intermediary handles the complexity internally while presenting simplified information to users.
3Productivity
If wait times are assigned based on congestion impact scores, then the productivity of the transportation system is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring actual wait times, congestion levels, and pickup success rates at different locations. This feedback is used to refine and update the congestion impact scores over time, improving the accuracy of productivity optimization while using historical data to reduce measurement complexity.
Solution Approach 2:
The system performs preliminary analysis of congestion patterns and location characteristics in advance, building predictive models that estimate congestion impact scores before actual pickups occur. This preliminary action reduces the need for complex real-time measurements during critical dispatching moments.
Data Source
AI summary
Aspects of the disclosure provide for wait times for pickups of passengers involving autonomous vehicles. For instance, a request for a trip identifying a pickup location may be received from a client computing device. A plurality of potential pickup locations may be identified. A subset of the plurality of potential pickup locations may be determined. A wait time may be assigned to each of the potential pickup locations of the subset. Each wait time may correspond to an estimated amount of time an autonomous vehicle can wait for the user at a respective one of the potential pickup locations of the subset. The potential pickup locations of the subset and the assigned wait times may be sent to the client computing device for display to a user.