HD Map Speed Limit Adjustment Using IMU Road Feedback
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Solution Overview
Problem
Speed limits in maps used for autonomous driving vehicles do not get updated frequently enough to account for changes in road conditions, such as new speed bumps or uneven road surfaces, which can affect the comfort and safety of passengers.
Innovation Solution
Dynamic vehicle parameters like pitch angle changing rate, z-axis acceleration, and z-axis jerk are measured using an inertial measurement unit, and if these parameters meet specific criteria, the speed limit is adjusted within a predetermined range, allowing for real-time updates to the speed limit based on the vehicle's experience of the road conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If speed limits in the map are updated frequently to reflect road condition changes, then passenger comfort and safety are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system uses IMU sensor feedback to continuously monitor vehicle dynamics (acceleration, jerk) and automatically adjusts speed limits when abnormal patterns are detected. This closed-loop feedback mechanism enables automatic adaptation to road condition changes without manual intervention, improving reliability while managing complexity through automated decision-making algorithms
Solution Approach 2:
The autonomous vehicle performs self-diagnosis of road conditions by analyzing its own motion data from IMU sensors. The vehicle independently determines when road conditions have changed and adjusts its speed limits accordingly, eliminating the need for external map updating systems and reducing overall system complexity
2Adaptability or versatility
If speed limits are updated in real-time based on road conditions, then adaptability to changing environments is improved, but measurement precision requirements increase
Solution Approach 1:
The system pre-establishes threshold criteria for IMU parameter patterns that indicate specific road conditions (e.g., speed bumps, uneven surfaces). By having predetermined decision rules ready, the system can quickly adapt to new conditions without requiring ultra-precise real-time measurements, as the thresholds provide built-in tolerance ranges
Solution Approach 2:
The system monitors changes in IMU parameters (acceleration, jerk, velocity) over time and detects road condition changes through parameter patterns rather than absolute precision requirements. By focusing on parameter changes and trends rather than exact values, the system achieves adaptability with moderate measurement precision
3Reliability
If the vehicle operates at lower speed limits to accommodate uncertain road conditions, then safety is improved, but productivity decreases
Solution Approach 1:
The system dynamically adjusts speed limits based on real-time detection of actual road conditions rather than using static conservative limits. When road conditions are good, the vehicle operates at higher speeds for improved productivity. When conditions deteriorate (detected through IMU patterns), speed limits are reduced for safety. This dynamic adjustment resolves the contradiction by making speed adaptive to actual conditions
Solution Approach 2:
The system periodically re-evaluates road conditions by continuing to monitor IMU sensor data and adjusts speed limits in periodic cycles. This allows the vehicle to maintain higher speeds during safe periods while periodically checking for condition changes, balancing productivity with safety through time-based reassessment rather than continuous conservative limiting
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables the speed limits to be dynamically adjusted based on real-time data from the vehicle's sensors, improving passenger comfort and safety by ensuring the vehicle operates within optimal speed limits even when road conditions change.
Implementation Method 1
a set of dynamic vehicle parameters of an autonomous driving vehicle (ADV) associated with a road location are determined based on outputs of an inertial measurement unit (IMU) of the ADV measured when the ADV is traveling through the road location
Data Source
AI summary
In one embodiment, a set of dynamic vehicle parameters of an ADV associated with a road location are determined based on outputs of an IMU of the ADV measured when the ADV is traveling through the road location. Whether the set of dynamic vehicle parameters satisfy one of a first set of criteria and a second set of criteria is determined. In response to the dynamic vehicle parameters satisfying the first set of criteria for a first predetermined quantity of times or satisfying the second set of criteria for a second predetermined quantity of times, the speed limit associated with the road location is adjusted within a limited range spanning from a minimum speed limit to a maximum speed limit. Operations of the ADV when the ADV subsequently travels through the road location are controlled based at least in part on the adjusted speed limit.