Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security
Abstract
:1. Introduction
2. Potential Applications of the Lane-Level Map-Aiding Approach and the Project TransSec
2.1. Potential Applications of the Lane-Level Map-Aiding Approach
2.2. Project TransSec
3. Map-Supported Positioning
3.1. Digital Road Map
3.2. Basics of Map-Matching
3.3. Map-Matching Criteria and Total Weighting Score (TWS)
3.3.1. Map-Matching Criteria
3.3.2. Total Weighting Score (TWS)
4. Map-Supported Positioning
4.1. Data Availability and Quality Analysis
4.2. Map-Aiding Approach
- (1)
- step 1: search for road candidate based on a well-defined weighting-function according to Equation (5) in Section 3.3.2,
- (2)
- step 2: identification of the road link with the highest TWS (reference link),
- (3)
- step 3: computation of the lateral position deviation d from the vehicle position to the identified road link (reference link),
- (4)
- Step 4: on-/off-road detection including a comparison of probability estimation (see Section 4.3),
- (5)
- step 5: identification of the lane on which the vehicle is travelling; wrong-way driver detection including probability estimation (see Section 4.4),
- (6)
- step 6: provide all necessary results (e.g., speed limit and direction of traffic flow, link type and number of lanes) of the reference link to identify potential risks.
- (1)
- The identification on which lane the vehicle is actually traveling is added.
- (2)
- The probability estimation of the on-/off-road or the wrong-way driver is added.
- (3)
- Multiple road links are provided (if needed).
4.3. On-/Off-Road Detection including Probability Estimation
4.4. Wrong-Way Driver Detection including Probability Estimation
4.4.1. Road Link with Attribute “One-Way”
4.4.2. Road Link with Attribute “Two-Way”
Case: Even Number of Lanes
Case: Odd Number of Lanes
4.4.3. Wrong-Way Driver Alert
5. Evaluation
5.1. Test Scenario
5.1.1. Real Trajectories
5.1.2. Simulated Trajectories
5.2. Results
5.2.1. Results of Real Trajectories
5.2.2. Results of Simulated Trajectories
5.3. Analysis
6. Conclusions and Outlook
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Driving Maneuvers | Cases | Number of Positions | Number of Road Links |
---|---|---|---|
Regular drives | - | 160,261 | 3124 |
Off-road drives | - | 4173 | 42 |
Wrong-way driver drives | One-way road | 1237 | 41 |
Oncoming traffic | 1226 | 45 | |
Closed road | 382 | 22 |
Actual: Yes | Actual: No | |
---|---|---|
Predicted: Yes | - | 344 |
Predicted: No | - | 27,108 |
Actual: Yes | Actual: No | |
---|---|---|
Predicted: Yes | - | 95 |
Predicted: No | - | 27,357 |
Actual: Yes | Actual: No | Actual: Yes | Actual: No | Actual: Yes | Actual: No | |
---|---|---|---|---|---|---|
Predicted: Yes | 4168 | 1582 | 4165 | 1826 | 4158 | 1956 |
Predicted: No | 5 | 161,524 | 8 | 161,280 | 15 | 161,150 |
Actual: Yes | Actual: No | Actual: Yes | Actual: No | Actual: Yes | Actual: No | |
---|---|---|---|---|---|---|
Predicted: Yes | 2842 | 228 | 2834 | 465 | 2821 | 456 |
Predicted: No | 3 | 164,206 | 11 | 1,639,969 | 24 | 163,978 |
Off-road detection | False positive rate [%] | 0.970 | 1.120 | 1.199 |
Sensitivity [%] | 99.904 | 99.808 | 99.640 | |
Wrong-way driver detection | False positive rate [%] | 0.139 | 0.283 | 0.278 |
Sensitivity [%] | 99.894 | 99.613 | 99.156 |
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Luz, P.; Zhang, L.; Wang, J.; Schwieger, V. Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security. Sustainability 2021, 13, 9724. https://doi.org/10.3390/su13179724
Luz P, Zhang L, Wang J, Schwieger V. Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security. Sustainability. 2021; 13(17):9724. https://doi.org/10.3390/su13179724
Chicago/Turabian StyleLuz, Philipp, Li Zhang, Jinyue Wang, and Volker Schwieger. 2021. "Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security" Sustainability 13, no. 17: 9724. https://doi.org/10.3390/su13179724