Construction Zone Mapping for Active-Inactive Driving Mode Decisions
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating construction zones due to rapidly changing environments, leading to inaccuracies in pre-stored map data, which can result in unnecessary transitions from autonomous to manual driving modes, affecting safety and efficiency.
Innovation Solution
A method involving the identification and classification of construction zones using detailed map information, where vehicles detect construction objects, map the area, classify the zone as active or inactive based on changes, and adjust driving modes accordingly, with the ability to reclassify and update map data in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles rely on pre-stored map data for navigation, then the system can operate autonomously in normal conditions, but the map data becomes inaccurate or obsolete in construction zones
Solution Approach 1:
The system dynamically updates map data by detecting construction zones in real-time and classifying their activity status. Instead of relying solely on static pre-stored map data, the vehicle adapts its navigation by incorporating real-time construction zone information, allowing the map data to evolve from static to dynamic and maintain accuracy in changing environments.
Solution Approach 2:
The system implements feedback by detecting construction zones, classifying their activity status, and using this information to update map data and adjust driving mode decisions. This closed-loop feedback mechanism ensures that map data reflects current conditions, resolving the contradiction between relying on pre-stored data and adapting to construction zones.
2Reliability
If the vehicle automatically transfers control to the driver upon identifying a construction zone, then safety is ensured, but driver frustration increases for long-term construction projects that don't present actual challenges
Solution Approach 1:
The system applies local quality by classifying construction zones based on their specific characteristics and activity status. Instead of treating all construction zones uniformly and transferring control, the system selectively determines when manual intervention is needed based on the actual challenge level of each zone, allowing autonomous operation in low-risk areas while maintaining safety in high-risk areas.
Solution Approach 2:
The system changes the parameter of driving mode selection based on construction zone classification. By introducing activity status classification (active vs. inactive construction zones), the system dynamically adjusts the driving mode parameter, transferring to manual control only when necessary, thereby maintaining safety while improving driver convenience.
3Reliability
If the vehicle always operates in manual mode in construction zones, then safety is maintained, but productivity and efficiency decrease due to unnecessary driver intervention
Solution Approach 1:
The system applies local quality by differentiating between active and inactive construction zones and applying different driving mode strategies to each. Inactive construction zones with no actual challenges allow autonomous operation, maintaining productivity, while active zones require manual control for safety, optimizing the balance between safety and efficiency.
Solution Approach 2:
The system changes the driving mode parameter dynamically based on construction zone activity classification. By introducing this conditional parameter change, the system avoids unnecessary manual intervention in low-risk zones, maintaining high productivity, while ensuring manual control in high-risk zones, maintaining safety.
Data Source
AI summary
Aspects of the present disclosure relate to differentiating between active and inactive construction zones. In one example, this may include identifying a construction object associated with a construction zone. The identified construction object may be used to map the area of the construction zone. Detailed map information may then be used to classify the activity of the construction zone. The area of the construction zone and the classification may be added to the detailed map information. Subsequent to adding the construction zone and the classification to the detailed map information, the construction object (or another construction object) may be identified. The location of the construction object may be used to identify the construction zone and classification from the detailed map information. The classification of the classification may be used to operate a vehicle having an autonomous mode.