Autonomous Vehicle Zone Matching for Road-Suitable Dispatch
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Solution Overview
Problem
Existing transportation management systems face inefficiencies in matching autonomous transportation provider vehicles with transportation requests, leading to wasted resources, fluctuating availability, and increased transportation time due to the inability to determine the suitability of vehicles for specific geographic zones and conditions.
Innovation Solution
A system and method for matching autonomous transportation provider vehicles with transportation requests based on vehicle characteristics, road surface characteristics, and requestor characteristics, using geographic zones to optimize vehicle deployment and request fulfillment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous transportation provider vehicles are arbitrarily matched with pending transportation requests, then transportation requests can be fulfilled quickly, but transportation supply resources are wasted and vehicle availability fluctuates
Solution Approach 1:
The system performs preliminary actions by determining geographic zones where autonomous vehicles are suitable for providing transportation services before matching requests. This advance preparation ensures that when requests come in, vehicles can be quickly matched to appropriate zones, maintaining fast fulfillment speed while avoiding resource waste by pre-filtering incompatible vehicle-request pairings.
Solution Approach 2:
The system dynamically adjusts vehicle matching based on real-time conditions including vehicle characteristics, road surface conditions, and requestor characteristics. This dynamic approach allows the system to optimize matches continuously, improving fulfillment speed while reducing resource waste by adapting to changing conditions rather than using static arbitrary matching.
2Device complexity
If autonomous transportation provider vehicles are matched without considering geographic zone suitability, then matching process is simple, but service quality deteriorates and operational safety decreases
Solution Approach 1:
The system segments the geographic area into multiple zones based on road surface conditions and vehicle characteristics. This segmentation allows the matching process to consider zone suitability without becoming overly complex, as each zone has defined characteristics that guide vehicle assignment. The segmentation maintains service quality by ensuring vehicles are matched to appropriate zones while keeping the process manageable through structured zone definitions.
Solution Approach 2:
The system applies local quality by tailoring vehicle matching to specific geographic zones with different road surface conditions. Each zone has localized requirements that determine which vehicles are suitable, ensuring high service quality and safety in each area while maintaining overall system efficiency through standardized zone-based matching rules.
3Speed
If vehicle characteristics are not considered in matching, then matching speed increases, but fuel efficiency and operational performance decrease
Solution Approach 1:
The system changes parameters by considering vehicle characteristics such as driving maneuver capabilities when determining geographic zone suitability. This parameter-based matching ensures that vehicles are assigned to zones where they can operate efficiently, improving fuel efficiency and operational performance while maintaining matching speed through automated parameter comparison and zone-based filtering.
Data Source
AI summary
The disclosed computer-implemented method may determine one or more characteristics of an autonomous vehicle, determine one or more characteristics of one or more road segments of a geographic area, determine at least one geographic zone for the autonomous vehicle within the geographic area based at least on the characteristics of the autonomous vehicle and the characteristics of the one or more road segments of the at least one geographic area, and match a request with the autonomous vehicle within the at least one geographic zone based at least in part on a request location and a destination location of the request being associated with the at least one geographic zone. Other methods, systems, and computer-readable media are disclosed.