Autonomous Vehicle Route Pricing Using Comfort and Risk Scores
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Solution Overview
Problem
Current systems for pricing autonomous vehicle (AV) services do not adequately account for tangible and reputational costs, such as wear and tear, safety risks, and passenger comfort, leading to inefficient pricing and potential reputational damage.
Innovation Solution
A dynamic pricing system that assigns comfort, confidence, and risk scores to various routes based on data analysis, influencing user route selection to minimize costs and reputational risks by determining prices that reflect these factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional pricing methods are used for AV services, then pricing simplicity is maintained, but tangible costs (wear and tear, maintenance) and reputational risks are not adequately accounted for
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting pricing based on multiple variables including route characteristics, vehicle wear metrics, safety risks, and reputational factors. The system transforms static pricing into dynamic pricing by changing price parameters in response to varying operational conditions, thereby improving cost recovery reliability without requiring overly complex system architecture
Solution Approach 2:
The patent introduces a pricing module as an intermediary component that processes multiple input factors (route data, vehicle status, risk assessments) and translates them into adjusted service prices. This intermediary layer manages the complexity by centralizing the decision-making logic, allowing the system to account for tangible and reputational costs without making the entire AV service system overly complex
2Adaptability or versatility
If AVs traverse routes with difficult driving maneuvers or high traffic areas, then service coverage and accessibility are improved, but wear and tear, safety risks, and reputational costs increase
Solution Approach 1:
The patent applies dynamics by making route selection and pricing flexible rather than fixed. The system dynamically evaluates multiple potential routes for each service request, adjusting the recommended route based on real-time factors such as traffic conditions, vehicle wear patterns, safety risks, and reputational considerations. This dynamic approach allows the AV to adapt service delivery to minimize harmful factors while maintaining broad service coverage
Solution Approach 2:
The patent applies inversion by reversing the traditional approach where routes are selected solely for efficiency and coverage. Instead, the system first evaluates routes based on their impact on vehicle wear, safety risks, and reputational factors, then adjusts pricing or selects alternative routes to mitigate these harmful effects. This inverted prioritization ensures that service coverage is maintained while actively reducing wear and tear and safety risks
3Ease of operation
If AVs take routes with potholes or rough terrain, then service accessibility is improved, but maintenance costs and vehicle damage increase
Solution Approach 1:
The patent applies parameter changes by incorporating route surface quality metrics into the pricing and route selection parameters. The system adjusts prices based on the expected maintenance impact of different routes, and selectively routes AVs through rough terrain only when necessary, using price adjustments to compensate for the additional maintenance costs incurred
Solution Approach 2:
The patent applies feedback by using historical maintenance data and vehicle sensor information to continuously improve route selection and pricing decisions. The system monitors actual wear and maintenance costs from previous trips through difficult terrain, feeds this information back into the routing and pricing algorithms, and adjusts future route selections and price adjustments accordingly to minimize maintenance costs while preserving service accessibility
Data Source
AI summary
The present disclosure provides a method comprising receiving by an autonomous vehicle (“AV”) service provider a request for an AV service from a user, wherein the request identifies an origin and a destination for the AV service; identifying a plurality of possible routes between the origin and the destination; and, for each one of the plurality of possible routes assigning to the one of the possible routes at least one of a comfort score, a confidence score, and a risk an risk score based on data associated with the one of the possible routes determining a price for the one of the possible routes based on a combination of the at least one of the comfort score, the confidence score, and the risk score assigned to the one of the possible routes.