Autonomous Vehicle Route Scoring for Personalized Trip Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing autonomous passenger vehicle (APV) systems lack the ability to account for diverse customer preferences, leading to suboptimal trip planning and reduced customer satisfaction.
Innovation Solution
An automated ordering system that receives customer preferences, determines route scores based on these preferences, and selects a planned route using a scoring system, while also providing comparison routes to enhance customer choice and satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single fixed route is used for all customers, then the routing system is simple and fast, but customer satisfaction decreases due to inability to accommodate individual preferences
Solution Approach 1:
The routing system segments the route selection process into multiple independent components: preference extraction module, route scoring module, and route selection module. Each component handles a specific aspect of route customization, allowing the system to accommodate individual preferences without becoming unmanageably complex.
Solution Approach 2:
The system dynamically adjusts route selection based on customer preferences, vehicle type, weather conditions, and traffic patterns. Rather than using a fixed route for all customers, the system generates customized routes in real-time by weighting different route attributes according to individual customer preferences.
2Ease of operation
If multiple route options and preference scoring are implemented, then customer satisfaction increases through personalized service, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating multiple potential routes and their associated scores before final route selection. Route attributes such as distance, time, tolls, and scenic value are pre-computed and stored, allowing rapid final route determination when customer preferences are provided.
Solution Approach 2:
The system incorporates feedback mechanisms where customer preferences, historical data, and route performance metrics continuously refine the scoring algorithm. This feedback loop improves route determination accuracy over time while maintaining efficient processing through learned patterns and optimized weighting schemes.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A first device includes one or more processors configured to receive, from a second device associated with a customer, a service request for a trip from a first location to a second location via an autonomous vehicle. The one or more processors are configured to access preferences for the trip, where one or more of the preferences include one or more preference scores. The one or more processors are configured to determine a route score associated with each of one or more potential routes for the trip based at least in part on the one or more preference scores. The one or more processors are configured to select a planned route from the one or more potential routes based on the route scores. The one or more processors are also configured to provide information associated with the planned route to the second device.