Autonomous Vehicle Hybrid Routing for Active Trip Preferences
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Solution Overview
Problem
Current autonomous vehicle systems lack the ability to efficiently integrate user preferences and optimize routes that combine physical activity with autonomous vehicle travel, while also considering financial, environmental, and health costs, leading to suboptimal travel experiences.
Innovation Solution
A method implemented on an electronic computing device that receives user preferences and profiles to create hybrid routes combining physical activity with autonomous vehicle travel, calculating estimated times and costs, and determining suitable starting times to meet arrival deadlines, while considering factors like stress, environmental impact, and health benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional autonomous vehicle routing systems are used, then the vehicle can operate autonomously, but the system cannot integrate user preferences for physical activity and optimize routes combining multiple transportation modes
Solution Approach 1:
The routing system segments the trip into multiple segments, allowing different transportation modes (physical activity, public transportation, autonomous vehicle) to be combined in a hybrid route. Each segment can be independently optimized based on user preferences, destination, and arrival time requirements.
Solution Approach 2:
The routing system is designed to handle multiple transportation modes and user preferences universally. It can accommodate various physical activities (walking, running, cycling), public transportation options, and autonomous vehicle usage within a single integrated routing framework.
2Object-affected harmful factors
If the system provides only autonomous vehicle routes, then the routing is simple, but it does not provide health benefits or physical activity opportunities
Solution Approach 1:
The routing system dynamically adjusts route options based on user preferences, destination, and arrival time. It can flexibly incorporate physical activity segments, public transportation, and autonomous vehicle usage, adapting the route composition to maximize health benefits while meeting user constraints.
Solution Approach 2:
The system changes routing parameters by considering multiple transportation modes and physical activity levels. It optimizes routes based on varying parameters such as user fitness goals, time constraints, and preference for active versus passive transportation segments.
3Adaptability or versatility
If the system calculates multiple route options with different criteria, then user preferences are better satisfied, but the computational complexity increases
Solution Approach 1:
The system provides multiple route options with different levels of detail and optimization criteria. Users can select from partial route information (quick options) or more comprehensive optimized routes (detailed options), allowing them to balance between receiving thorough optimization and minimizing calculation time.
Data Source
AI summary
A method for using an autonomous vehicle includes receiving one or more user preferences for use of the autonomous vehicle. A destination is received for a trip using the autonomous vehicle. An arrival time is received for when the trip needs to be completed. A determination is made as to whether the user preferences includes a preference for physical activity for the trip. One or more routes are provided for the trip to the destination that permits the trip to be completed by the arrival time and that implements at least one of the user preferences. At least one of the routes comprises a hybrid route including one segment in which a physical activity selected by the user is suggested for traversing a distance of the one segment and another segment using the autonomous vehicle.