Autonomous Taxi Dispatch via Proximity Matching
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Solution Overview
Problem
Current systems for operating autonomous vehicles as taxis lack efficient dispatching and scheduling mechanisms, particularly in managing real-time availability, traffic conditions, and user requests, which can lead to inefficiencies and delays in service delivery.
Innovation Solution
A networked system that utilizes a taxi service control system to manage a fleet of autonomous vehicles, where requests are processed through mobile devices, selecting available vehicles based on proximity and schedule conflicts, and optimizing routes using real-time traffic information, with features for route modifications and payment processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a taxi service control system manages real-time availability and schedules for multiple autonomous vehicles, then service reliability and user satisfaction improve, but system complexity and computational requirements increase
Solution Approach 1:
The system segments the fleet management into individual vehicle profiles, each with its own availability status, location, and schedule. The control system processes requests by dividing the fleet into available and unavailable segments, matching users with appropriate vehicles rather than managing the entire fleet as a single complex unit.
Solution Approach 2:
The taxi service control system acts as an intermediary between users and autonomous vehicles. It receives user requests, processes them against vehicle availability and schedule data, and dispatches appropriate vehicles. This intermediary layer simplifies the interaction complexity by centralizing the matching logic.
2Loss of time
If the system selects vehicles based on proximity and schedule conflicts in real-time, then pickup time accuracy improves, but processing speed and computational load worsen
Solution Approach 1:
The system performs preliminary actions by pre-calculating vehicle availability statuses and maintaining updated location data before requests arrive. When a user requests a taxi, the system already has pre-processed information about which vehicles are available, their locations, and their schedules, enabling rapid matching without complex real-time calculations.
Solution Approach 2:
The system uses feedback mechanisms where vehicles continuously report their status, location, and schedule compliance to the control system. This real-time feedback allows the system to maintain accurate vehicle availability information and make rapid dispatch decisions based on current conditions rather than calculating from scratch.
Data Source
AI summary
Technology is described for operating a fleet of autonomous vehicles. A request for a taxi service may be received from a mobile device. The request may include a current location of the mobile device. They request may indicate that the taxi service is to be performed at a current time. An autonomous vehicle may be selected from the fleet of autonomous vehicles to perform the taxi service based in part on an availability of the autonomous vehicle and a proximity between the autonomous vehicle and the current location of the mobile device. Instructions may be provided to the autonomous vehicle to perform the taxi service according to the request. The autonomous vehicle may be configured to provide commands to drive the autonomous vehicle to the current location of the mobile device in order to perform the taxi service.