Study on Relative Accuracy and Verification Method of High-Definition Maps for Autonomous Driving
Abstract
:1. Introduction
2. High-Definition Maps and Accuracy
2.1. Accuracy and Precision in Mapping
2.2. Accuracy in HDMs for AD
2.3. Traditional Method for Accuracy
2.4. Limitations of Traditional Methods
2.4.1. Finding the Same Feature Point Pair
2.4.2. Differences between Lane Heading and Side Directions
2.5. Elemental Classification and Decomposition of HDMs
3. Materials and Methods
3.1. Case Study
3.1.1. Equipment and Environment
3.1.2. Data Acquisition
3.2. Methodology
- Calculate the corresponding closet point in the target point set for each point in the source point set.
- Compute the rigid transformation that minimizes the average distance of the above corresponding point pairs. Calculate the rotation and translation parameters.
- The new point set is obtained by using the rotation and translation parameters found in 2, for the source point set.
- Determines if the iterative computation stop condition is met. If it is, the calculation is stopped, if not, the new point set obtained in 3 is used as the new source point set and input into 1 to continue the iterative calculation.
3.2.1. Lane-Heading Direction
3.2.2. Lane-Side Direction
4. Results
4.1. Results for Lane-Heading Direction
4.2. Results for Collinear Direction
4.3. Results of Traditional Methods
5. Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Level | Name | Vehicle Lateral and Longitudinal Movement Control | Target and Incident Detection and Response | Dynamic Driving Task Takeover | Design Operating Conditions | Map Data Content |
---|---|---|---|---|---|---|
0 | Emergency assistance | Drivers | Drivers and systems | Drivers | Restrictions apply | Traditional maps |
1 | Partial driving assistance | Drivers and systems | Drivers and systems | Drivers | Restrictions apply | Traditional maps |
2 | Combined driving assistance | Systems | Drivers and systems | Drivers | Restrictions apply | Traditional maps + ADAS data |
3 | Conditional autopilot | Systems | Systems | Dynamic driving tasks take over the user | Restrictions apply | Static HDMs |
4 | Highly automated driving | Systems | Systems | Systems | Restrictions apply | Dynamic HDMs |
5 | Fully automated driving | Systems | Systems | Systems | No restrictions | Smart HDMs |
Lane Number | Median Deviation Error | Real Length of the Curve | Median Error per 100 m | Limit Error of the Section |
---|---|---|---|---|
Section 1 | 0.132 | 166.5 m | 0.080 | 0.159 |
Section 2 | 0.134 | 203.3 m | 0.066 | 0.132 |
Section 3 | 0.143 | 155.7 m | 0.092 | 0.185 |
Section 4 | 0.163 | 179.3 m | 0.091 | 0.181 |
Lane Number | Median Error | Limit Error |
---|---|---|
Section 1 | 0.132 | 0.159 |
Section 2 | 0.134 | 0.132 |
Section 3 | 0.143 | 0.185 |
Section 4 | 0.163 | 0.181 |
Lane Number | Relative Accuracy of the Vertical | Relative Accuracy of the Horizontal |
---|---|---|
Section 1 | 0.091 | 0.0025 |
Section 2 | 0.127 | 0.0031 |
Section 3 | 0.151 | 0.0032 |
Section 4 | 0.116 | 0.0028 |
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Yu, T.; Huang, H.; Jiang, N.; Acharya, T.D. Study on Relative Accuracy and Verification Method of High-Definition Maps for Autonomous Driving. ISPRS Int. J. Geo-Inf. 2021, 10, 761. https://doi.org/10.3390/ijgi10110761
Yu T, Huang H, Jiang N, Acharya TD. Study on Relative Accuracy and Verification Method of High-Definition Maps for Autonomous Driving. ISPRS International Journal of Geo-Information. 2021; 10(11):761. https://doi.org/10.3390/ijgi10110761
Chicago/Turabian StyleYu, Tengfei, He Huang, Nana Jiang, and Tri Dev Acharya. 2021. "Study on Relative Accuracy and Verification Method of High-Definition Maps for Autonomous Driving" ISPRS International Journal of Geo-Information 10, no. 11: 761. https://doi.org/10.3390/ijgi10110761