Naturalistic Driving Study: Linking the Study Data to the Roadway Information Database (2015) / Chapter Skim
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4Research Approach Matching Process Methods The method used in the present effort was developed to accurately associate large numbers of GPS latitude/longitude pairs (approximately 3.7 billion) with roadway links using feasible computing demands.
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5 The dense patches of roads in the center of the state are the areas where most of the participant driving occurred, and indicate where the NAVTEQ links are fully included. Beyond these patches, NAVTEQ links representing smaller roads are not included in the RID (see Figure 2.3)
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6highway sections because the Link AF does not share a node with the east-west highway links. Trip Metadata At the same time that the matching processing was being done, participant data associated with each trip were being stored in SHRP 2 database tables as part of the SHRP 2 driver identification activities, and trips by unconsented drivers were being identified.
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7 example, when the vehicle was under dense foliage for a period of time. These periods of reduced accuracy later in a file were not omitted from consideration because the previous accuracy would often permit obtaining a good solution even during the period of reduced accuracy.
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8of the roadway network, the algorithm logic needs only to follow the feasible sequence of links to which the GPS points track closest. Further, only distances from the GPS points to the nodes need to be evaluated, which greatly reduces the computational demands compared with spatial joins and buffers.
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9 Manual Route Reduction First, data reductionists visually translated GPS point paths from files into a list of road names, similar to a set of turn-byturn directions defining the route. Reductionists were provided a list of files by consented drivers in a random order.
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10 would be a random number from 1 to 7. The researcher then checked this row for algorithm accuracy.
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11 Masking Personally Identifying Information The Matching Algorithm attempted to identify every link on which the vehicle traveled. Various approaches have been explored for removing or masking locations, such as where the participant lived or worked.
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