Autonomous Vehicle Routing With Human Guide Vehicle Assistance
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating urban environments due to crowded conditions, which can lead to errors in sensor information interpretation and reduced confidence in safely progressing through unknown or challenging road conditions.
Innovation Solution
A system that pairs autonomous vehicles with human-driven vehicles to provide guide assistance, using human operators to collect sensor information and provide real-time instructions to help the autonomous vehicle navigate through uncertain conditions, thereby enhancing its ability to safely operate in complex urban settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles operate independently in crowded urban environments, then automation level is improved, but reliability deteriorates due to sensor interpretation errors
Solution Approach 1:
A human operator acts as an intermediary between the autonomous vehicle system and the complex urban environment. The human operator receives sensor data from the autonomous vehicle, interprets challenging scenarios that the autonomous system cannot reliably process, and provides guidance decisions to ensure safe passage through crowded conditions.
2Productivity
If autonomous vehicles navigate complex urban conditions independently, then productivity is improved, but measurement precision deteriorates in sensor interpretation
Solution Approach 1:
The human operator serves as an intermediary who receives raw sensor information from the autonomous vehicle's sensors, applies contextual understanding and judgment, and makes precise interpretations of complex urban scenarios that the autonomous system cannot reliably decode alone.
3Device complexity
If autonomous vehicles operate alone, then device complexity is reduced, but adaptability deteriorates in unknown road conditions
Solution Approach 1:
The human operator provides adaptive intelligence to bridge the autonomous vehicle system and unknown road conditions. When the autonomous system encounters unfamiliar or complex urban scenarios, the human operator interprets the situation and guides the vehicle appropriately, enhancing adaptability without requiring complex system redesign.
4Loss of information
If autonomous vehicles operate independently, then loss of information is reduced, but loss of time increases when human assistance is required
Solution Approach 1:
The human operator is pre-positioned and pre-alerted to potential challenges ahead. The system proactively identifies complex urban scenarios and prepares human intervention in advance, allowing the operator to be ready with guidance decisions before the autonomous vehicle encounters the challenging condition, thereby minimizing delay.
Solution Approach 2:
The system continuously monitors sensor data and autonomously identifies when human assistance is needed, providing real-time feedback to the human operator. This feedback loop ensures that human intervention is triggered only when necessary, maintaining information integrity while minimizing time loss through targeted rather than continuous human involvement.
Data Source
AI summary
A system can receive a transport request from a computing device of a requesting user, where the transport request indicates a service location. The system can determines a preliminary route for the transport request, and select an autonomous vehicle from a fleet of autonomous vehicles operating in the given area to service the transport request based on determining that the selected autonomous vehicle is capable of traversing the preliminary route without intervention.