Autonomous Vehicle Routing With User-Selected Route Adherence
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Solution Overview
Problem
Autonomous vehicles lack the ability to enforce user-selected routes while allowing necessary deviations, which can lead to passenger dissatisfaction and reduced future ridership, as they rely solely on their own routing systems that may recalibrate and deviate from the chosen route.
Innovation Solution
A method and system that allow users to select routes for autonomous vehicles, which include trip plans with specific geographic locations, enabling the vehicle to enforce the chosen route while allowing deviations by recalculating the optimal route in real-time using additional costs or penalties for routes that do not adhere to the selected path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the autonomous vehicle relies solely on its own routing system to determine the route, then the vehicle can operate autonomously without user intervention, but the vehicle may recalibrate and deviate from the user-selected route, leading to passenger dissatisfaction
Solution Approach 1:
The system receives and stores user-selected route information before the vehicle begins its journey. The routing system is provided with the user-selected route as preliminary input, establishing a predetermined path that the vehicle should follow. This preliminary action ensures that the user's route preference is established before any autonomous recalibration can occur.
Solution Approach 2:
The routing system periodically determines whether to use the user-selected route or a newly generated route by comparing route costs. This feedback mechanism allows the system to continuously monitor route adherence and make adjustments based on real-time conditions while respecting the user's original route selection, thereby maintaining both automation and adaptability.
2Productivity
If the autonomous vehicle allows real-time route recalibration, then the vehicle can optimize for current conditions, but the vehicle may deviate from the user-selected route, reducing passenger satisfaction
Solution Approach 1:
The system dynamically adjusts routing behavior by periodically evaluating whether to follow the user-selected route or switch to a newly generated route based on current conditions. The routing system can adapt its path in real-time while maintaining a bias toward the user-selected route, achieving both optimization efficiency and route adherence through dynamic decision-making.
Solution Approach 2:
The system changes the cost parameters of route evaluation by adding additional costs to routes that do not pass through key geographic locations of the user-selected route. This parameter modification ensures that the optimization process inherently favors routes that adhere to the user's selected path, maintaining reliability while allowing for necessary deviations.
3Reliability
If the autonomous vehicle strictly follows the user-selected route, then passenger satisfaction is improved, but the vehicle cannot deviate when necessary, reducing operational reliability
Solution Approach 1:
The system applies partial deviation from the user-selected route by allowing deviations only when the newly generated route demonstrates significantly lower cost. The additional cost parameter ensures that minor deviations are prevented, while substantial optimizations are permitted. This partial action maintains route adherence while enabling necessary real-time adjustments.
Solution Approach 2:
The cost comparison mechanism acts as an intermediary between the user-selected route and real-time route generation. By introducing additional costs for routes that deviate from key geographic locations, the system mediates between strict route adherence and necessary flexibility, allowing deviations only when they provide significant operational benefits.
4Reliability
If the system adds additional costs to routes that do not pass through selected geographic locations, then route adherence is enforced, but the route planning complexity increases
Solution Approach 1:
The system modifies the cost parameters of the routing algorithm by adding additional costs to routes that do not pass through key geographic locations of the user-selected route. This parameter change transforms the routing problem into one that naturally favors route adherence without requiring complex constraint enforcement mechanisms, maintaining simplicity while achieving reliable route following.
Data Source
AI summary
Aspects of the disclosure relate to controlling an autonomous vehicle. For instance, dispatching instructions including a destination location and a trip plan identifying a selected route may be received. The route was selected by a user from a set of two or more routes. The trip plan may be used to determine whether to user the selected route or a new route. The autonomous vehicle may be controlled to the destination location based on the determination.