| ... | @@ -7,14 +7,22 @@ Map matching typically involves comparing the sensor data, such as GNSS or inert |
... | @@ -7,14 +7,22 @@ Map matching typically involves comparing the sensor data, such as GNSS or inert |
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**- Candidate generation:** This step involves generating a set of possible locations on the digital map that correspond to the sensor data.
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**- Candidate generation:** This step involves generating a set of possible locations on the digital map that correspond to the sensor data.
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_Here is an example of candidat generation :_
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[](https://www.mdpi.com/1424-8220/22/8/3057)
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**- Candidate ranking:** This step involves ranking the candidate locations based on a set of criteria, such as the quality of the sensor data, the similarity of the sensor data to the digital map data, and the expected movement of the vehicle or person.
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**- Candidate ranking:** This step involves ranking the candidate locations based on a set of criteria, such as the quality of the sensor data, the similarity of the sensor data to the digital map data, and the expected movement of the vehicle or person.
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**- Map matching:** This step involves selecting the best candidate location from the ranked set of candidates.
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**- Map matching:** This step involves selecting the best candidate location from the ranked set of candidates.
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Here is an example of map matching:
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_Here is an example of map matching:_
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[](https://www.gpsworld.com/lane-level-positioning-with-low-cost-map-aided-gnss-mems-imu-integration/)
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[](https://www.gpsworld.com/lane-level-positioning-with-low-cost-map-aided-gnss-mems-imu-integration/)
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Map matching algorithms can be divided into two main categories: geometric and topological map matching. Geometric map-matching algorithms use geometric features such as angles and distances to match the sensor data to the digital map data. Topological map-matching algorithms use topological features such as road networks and intersections to match the sensor data to the digital map data.
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Map matching algorithms can be divided into two main categories: geometric and topological map matching. Geometric map-matching algorithms use geometric features such as angles and distances to match the sensor data to the digital map data. Topological map-matching algorithms use topological features such as road networks and intersections to match the sensor data to the digital map data.
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Overall, Map matching is a process used in navigation and transportation systems to determine the location of a vehicle or a person on a map based on sensor data. It typically involves comparing the sensor data, such as GPS or inertial sensor data, with the digital map data, the process includes several steps such as data pre-processing, candidate generation, candidate ranking, and map matching.
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Overall, Map matching is a process used in navigation and transportation systems to determine the location of a vehicle or a person on a map based on sensor data. It typically involves comparing the sensor data, such as GPS or inertial sensor data, with the digital map data, the process includes several steps such as data pre-processing, candidate generation, candidate ranking, and map matching.
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Sources :
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- https://www.gpsworld.com/lane-level-positioning-with-low-cost-map-aided-gnss-mems-imu-integration/
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- W. Li, W. Zhang and C. Gao, (2022), A Historical-Trajectories-Based Map Matching Algorithm for Container Positioning and Tracking, Sensors 2022, 22(8), 3057; https://doi.org/10.3390/s22083057 |
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