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The visualization of the cost c 3 for the neighbor node nn 1 . The final cost is computed as the absolute value of the difference between the edge length (blue dashed line) and the length along the trace (red dotted line). We can see that both cost c 1 and cost c 2 (gray dashed lines) would mistakenly chose nn 1 as the match.

The visualization of the cost c 3 for the neighbor node nn 1 . The final cost is computed as the absolute value of the difference between the edge length (blue dashed line) and the length along the trace (red dotted line). We can see that both cost c 1 and cost c 2 (gray dashed lines) would mistakenly chose nn 1 as the match.

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Fig. 1. The measurement noise of a GPS record from Prague
Fig. 3. Initialization example. Green points represent the location...
Fig. 4. The visualization of the cost c 1 , depicted as blue dashed...
Fig. 5. The visualization of cost c 2 , depicted by the blue dashed...
+5 Fig. 6. The visualization of the cost c 3 for the neighbor node nn 1 ....
Map Matching Algorithm for Large-scale Datasets
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  • Sep 2019
GPS receivers embedded in cell phones and connected vehicles generate a series of location measurements that can be used for various analytical purposes. A common pre-processing step of this data is the so-called map matching. The goal of map matching is to infer the trajectory that the device followed in a road network from a potentially sparse se...
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Context 1
... we created another cost c 3 that is designed to cover the remaining cases by comparing the length of the edge and the length along the trace between the projection of the current node n c on the trace (which was fixed in the previous step of the algorithm) and the projection of the node n n . We can see the example where this metric is essential to correctly match the trace in Figure 6. ...
Context 2
... we created another cost c 3 that is designed to cover the remaining cases by comparing the length of the edge and the length along the trace between the projection of the current node n c on the trace (which was fixed in the previous step of the algorithm) and the projection of the node n n . We can see the example where this metric is essential to correctly match the trace in Figure 6. ...

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