Autonomous Vehicle Route Planning for Emergency Vehicle Avoidance
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Solution Overview
Problem
Existing autonomous vehicles face disruptions in their operation schedules when encountering emergency vehicles, leading to complications in control processing and increased power consumption, especially in congested or adverse weather conditions.
Innovation Solution
An operation support device that predicts the number of emergency vehicle appearances along a route and adjusts the vehicle's operation plan by selecting alternative lanes or extending travel times to minimize encounters, using appearance history data and environmental conditions to optimize the route.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle gives priority to emergency vehicles by changing lanes or stopping, then the emergency vehicle can pass safely, but the operation schedule of the vehicle is disrupted
Solution Approach 1:
The operation support device performs preliminary actions by predicting emergency vehicle appearances and pre-adjusting the operation plan before encounters occur. It acquires appearance data, predicts number of appearances for each link, and adjusts the operation plan in advance, allowing the vehicle to maintain its schedule while still prioritizing emergency vehicles when necessary
Solution Approach 2:
The system dynamically adjusts the operation plan based on real-time predictions and actual encounters. It flexibly modifies lane selection, travel time, and route based on predicted emergency vehicle appearances, balancing schedule maintenance with emergency vehicle priority requirements
2Reliability
If the vehicle performs complex processing to detect and avoid emergency vehicles in real-time, then safety is improved, but power consumption increases
Solution Approach 1:
The system performs preliminary detection and prediction of emergency vehicle appearances before the vehicle encounters them. By acquiring appearance data and predicting numbers of appearances in advance, the system reduces the need for complex real-time processing during actual encounters, thereby lowering power consumption while maintaining safety
Solution Approach 2:
The operation support device acts as an intermediary between raw sensor data and vehicle control decisions. It processes appearance data, predicts emergency vehicle appearances, and generates adjusted operation plans, reducing the computational burden on the vehicle's real-time systems and lowering overall power consumption
3Productivity
If the vehicle maintains strict adherence to operation schedule without adjustments, then productivity is improved, but the ability to respond to emergency vehicles deteriorates
Solution Approach 1:
The system dynamically adjusts the operation plan based on predicted emergency vehicle appearances while striving to maintain schedule adherence. It flexibly modifies lane selection and travel time estimates for links with high predicted appearances, allowing the vehicle to respond to emergencies without significantly disrupting the overall operation schedule
Solution Approach 2:
The system uses feedback from appearance data and prediction results to continuously adjust the operation plan. By monitoring predicted numbers of appearances and actual encounters, the system optimizes lane selection and timing to balance schedule adherence with emergency vehicle response capability
Data Source
AI summary
An operation support device operates a vehicle by autonomous driving. The operation support device includes a control unit that acquires appearance data indicating an appearance history of emergency vehicles for each of a plurality of links forming a route through which the vehicle is expected to pass, predicts, for each of the links, the number of appearances of emergency vehicles while the vehicle is traveling, based on the acquired appearance data, and adjusts an operation plan of the vehicle according to the predicted number of appearances for each of the links.