Autonomous Vehicle Route Cost Feedback for Traffic Diversion
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Solution Overview
Problem
Autonomous vehicles often use the same routes, leading to road congestion and potential stranding when multiple vehicles are traveling to or from a common location, such as airports or events, due to a lack of effective route diversification.
Innovation Solution
A method and system that utilize a fleet management system to identify clusters of autonomous vehicles likely to use a road segment and adjust the cost of traversing that segment based on factors like passenger load and vehicle state to encourage route variation, using cost-based analysis to distribute traffic more evenly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles use cost-based analysis with common maps to determine routes, then route determination efficiency is improved, but road congestion increases due to vehicles clustering on the same routes
Solution Approach 1:
The system implements feedback by continuously monitoring the locations of autonomous vehicles in the fleet and using this information to dynamically adjust route costs. When vehicles are detected clustering on certain road segments, the system increases the cost of those segments, causing vehicles to select alternative routes. This closed-loop feedback mechanism resolves the contradiction by maintaining efficient route determination while preventing congestion through real-time adaptive cost adjustment.
Solution Approach 2:
The patent applies dynamics by making route costs variable rather than static. The cost of traversing a road segment changes dynamically based on the current distribution of vehicles in the fleet. This dynamic adjustment allows the routing system to adapt to changing traffic conditions and vehicle distributions, enabling efficient route determination that automatically avoids congested areas without requiring complex centralized control.
2Loss of time
If autonomous vehicles follow the same routes to or from common locations, then travel time efficiency is improved, but reliability decreases when vehicles become stranded causing greater congestion
Solution Approach 1:
The system changes the parameter of route cost dynamically based on fleet distribution. When vehicles are concentrated on certain routes, the cost parameter for those routes is increased, automatically dispersing vehicles across multiple routes. This parameter change maintains travel time efficiency by allowing vehicles to use optimal routes when conditions permit, while simultaneously improving reliability by preventing complete dependency on single routes that could cause system-wide failures if stranding occurs.
3Object-affected harmful factors
If fleet management system adjusts route costs in real-time to distribute traffic, then road congestion is reduced, but system complexity increases
Solution Approach 1:
The system applies self-service by enabling autonomous vehicles to independently adjust their route selection based on real-time cost information provided by the fleet management system. Each vehicle autonomously evaluates multiple routes using the updated cost parameters and selects the optimal route without requiring direct centralized control. This self-service approach reduces congestion through distributed decision-making while minimizing system complexity by avoiding the need for complex centralized coordination of individual vehicle movements.
Data Source
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AI summary
Aspects of the disclosure provide for route variation for autonomous vehicles. For example, a plurality of routes may be identified. Each route of the plurality may be a current route on which an autonomous vehicle of a fleet of autonomous vehicles is currently traveling. Each of the autonomous vehicles may use a cost-based analysis to determine routes. That there will be a cluster of autonomous vehicles of the fleet of autonomous vehicles on a road segment may be determined. A signal may be sent to one or more of the autonomous vehicles of the cluster of autonomous vehicles a signal to adjust a cost of traversing the road segment in order to increase a likelihood of the one or more of the autonomous vehicles of the cluster of autonomous vehicles avoiding the road segment.