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  "author": "Zourlidou, S., Golze, J. and Sester, M.",
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  "author": "Zourlidou",
            
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  "author_email": "stefania.zourlidou@ikg.uni-hannover.de",
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  "author_email": "stefania.zourlidou@ikg.uni-hannover.de",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/0043786",
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  "doi": "10.25835/0043786",
            
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  "doi_date_published": "2020-09-14",
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  "doi_date_published": "2020-09-14",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
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  "domain": "https://data.uni-hannover.de",
            
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  "extra_authors": [
            
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    {
            
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      "extra_author": " S."
            
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    },
            
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    {
            
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      "extra_author": " Golze"
            
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    },
            
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    {
            
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      "extra_author": " J. and Sester"
            
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    },
            
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    {
            
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      "extra_author": " M."
            
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    }
            
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  ],
            
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  "groups": [],
            
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  "have_copyright": "Yes",
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  "have_copyright": "Yes",
            
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  "id": "1a97c0df-4659-43bd-99e9-d2573d31f5cd",
            
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  "isopen": false,
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  "license_id": "CC-BY-NC-3.0",
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  "license_id": "CC-BY-NC-3.0",
            
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  "license_title": "CC-BY-NC-3.0",
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  "license_title": "CC-BY-NC-3.0",
            
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  "maintainer": "Jens Golze",
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  "maintainer": "Jens Golze",
            
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  "maintainer_email": "jens.golze@ikg.uni-hannover.de",
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  "maintainer_email": "jens.golze@ikg.uni-hannover.de",
            
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  "metadata_created": "2021-10-14T10:16:09.218830",
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  "metadata_created": "2021-10-14T10:16:09.218830",
            
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  "metadata_modified": "2023-08-04T08:46:52.230229",
            
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  "name": 
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  "name": 
            
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trajectory-analysis-at-intersections-for-traffic-rule-identification",
35
trajectory-analysis-at-intersections-for-traffic-rule-identification",
            
22
  "notes": "This dataset is a subset of a much larger data collection 
36
  "notes": "This dataset is a subset of a much larger data collection 
            
23
and used for the analysis of speed- and time-profiles of trajectories 
37
and used for the analysis of speed- and time-profiles of trajectories 
            
24
crossing different selected intersections. Resulting findings can be 
38
crossing different selected intersections. Resulting findings can be 
            
25
used for the intersection categorization according to traffic 
39
used for the intersection categorization according to traffic 
            
26
regulation types.\r\n\r\nThe six selected intersections (A - F) and 
40
regulation types.\r\n\r\nThe six selected intersections (A - F) and 
            
27
the crossing trajectory samples (green) can be seen in the subsequent 
41
the crossing trajectory samples (green) can be seen in the subsequent 
            
28
71e0e3-19d6-4e45-9da5-6cb932a3d7d7/download/junctionall.png)\r\n\r\n## 
42
71e0e3-19d6-4e45-9da5-6cb932a3d7d7/download/junctionall.png)\r\n\r\n## 
            
29
Data Acquisition\r\nThe trajectory samples were recorded using an 
43
Data Acquisition\r\nThe trajectory samples were recorded using an 
            
30
android smartphone while driving a car in and around the city of 
44
android smartphone while driving a car in and around the city of 
            
31
Hannover, Germany. The acquisition period was from December 2017 to 
45
Hannover, Germany. The acquisition period was from December 2017 to 
            
32
March 2019 by only a single person. The recording of the trajectories 
46
March 2019 by only a single person. The recording of the trajectories 
            
33
has taken place without restrictions in order to reflect a normal 
47
has taken place without restrictions in order to reflect a normal 
            
34
behavior of everyday car journeys. The sampling rate is approximately 
48
behavior of everyday car journeys. The sampling rate is approximately 
            
35
1 sample per second.\r\n\r\n## Related Publications:\r\n* __Zourlidou, 
49
1 sample per second.\r\n\r\n## Related Publications:\r\n* __Zourlidou, 
            
36
S., Sester, M. and Hu, S. (2022):__ Recognition of Intersection 
50
S., Sester, M. and Hu, S. (2022):__ Recognition of Intersection 
            
37
Traffic Regulations From Crowdsourced Data. Preprints 2022, 
51
Traffic Regulations From Crowdsourced Data. Preprints 2022, 
            
38
2022070012. DOI: 10.20944/preprints202207.0012.v1\r\n\r\n* 
52
2022070012. DOI: 10.20944/preprints202207.0012.v1\r\n\r\n* 
            
39
__Zourlidou, S., Golze, J. and Sester, M. (2022):__ Traffic Regulation 
53
__Zourlidou, S., Golze, J. and Sester, M. (2022):__ Traffic Regulation 
            
40
Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach, 
54
Recognition using Crowd-Sensed GPS and Map Data: a Hybrid Approach, 
            
41
AGILE GIScience Ser., 3, 22, 2022. 
55
AGILE GIScience Ser., 3, 22, 2022. 
            
42
https://doi.org/10.5194/agile-giss-3-22-2022\r\n\r\n* __Cheng, H., 
56
https://doi.org/10.5194/agile-giss-3-22-2022\r\n\r\n* __Cheng, H., 
            
43
Lei, H., Zourlidou, S., Sester, M. (2022):__ Traffic Control 
57
Lei, H., Zourlidou, S., Sester, M. (2022):__ Traffic Control 
            
44
Recognition with an Attention Mechanism Using Speed-Profile and 
58
Recognition with an Attention Mechanism Using Speed-Profile and 
            
45
Satellite Imagery data. The International Archives of the 
59
Satellite Imagery data. The International Archives of the 
            
46
Photogrammetry, Remote Sensing and Spatial Information Sciences 
60
Photogrammetry, Remote Sensing and Spatial Information Sciences 
            
47
XLIII-B4-2022, S. 287\u201329. 
61
XLIII-B4-2022, S. 287\u201329. 
            
48
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-287-2022\r\n\r\n* 
62
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-287-2022\r\n\r\n* 
            
49
__Wang, C., Zourlidou, S., Golze, J. and Sester, M. (2020):__ 
63
__Wang, C., Zourlidou, S., Golze, J. and Sester, M. (2020):__ 
            
50
Trajectory analysis at intersections for traffic rule identification. 
64
Trajectory analysis at intersections for traffic rule identification. 
            
51
Geo-spatial Information Science, 11(4):1-10. 
65
Geo-spatial Information Science, 11(4):1-10. 
            
52
https://doi.org/10.1080/10095020.2020.1843374\r\n\r\n* __Cheng, H., 
66
https://doi.org/10.1080/10095020.2020.1843374\r\n\r\n* __Cheng, H., 
            
53
Zourlidou, S. and Sester, M. (2020):__ Traffic Control Recognition 
67
Zourlidou, S. and Sester, M. (2020):__ Traffic Control Recognition 
            
54
with Speed-Profiles: A Deep Learning Approach. ISPRS Int. J. Geo-Inf. 
68
with Speed-Profiles: A Deep Learning Approach. ISPRS Int. J. Geo-Inf. 
            
55
2020, 9, 652. https://doi.org/10.3390/ijgi9110652\r\n\r\n* __Golze, 
69
2020, 9, 652. https://doi.org/10.3390/ijgi9110652\r\n\r\n* __Golze, 
            
56
J., Zourlidou, S. and Sester, M. (2020):__ Traffic Regulator Detection 
70
J., Zourlidou, S. and Sester, M. (2020):__ Traffic Regulator Detection 
            
57
Using GPS Trajectories. KN J. Cartogr. Geogr. Inf. 
71
Using GPS Trajectories. KN J. Cartogr. Geogr. Inf. 
            
58
https://doi.org/10.1007/s42489-020-00048-x\r\n\r\n* __Zourlidou, S., 
72
https://doi.org/10.1007/s42489-020-00048-x\r\n\r\n* __Zourlidou, S., 
            
59
Fischer, C. and Sester, M. (2019):__  Classification of street 
73
Fischer, C. and Sester, M. (2019):__  Classification of street 
            
60
junctions according to traffic regulators. In: _Kyriakidis, P., 
74
junctions according to traffic regulators. In: _Kyriakidis, P., 
            
61
Hadjimitsis, D., Skarlatos, D. and Mansourian, A., (eds) 2019_. 
75
Hadjimitsis, D., Skarlatos, D. and Mansourian, A., (eds) 2019_. 
            
62
Accepted short papers and posters from the 22nd AGILE conference on 
76
Accepted short papers and posters from the 22nd AGILE conference on 
            
63
geo-information science. Cyprus University of Technology 17\u201320 
77
geo-information science. Cyprus University of Technology 17\u201320 
            
64
June 2019, Limassol, Cyprus.\r\n\r\n## Related Datasets:\r\n* 
78
June 2019, Limassol, Cyprus.\r\n\r\n## Related Datasets:\r\n* 
            
65
__Zourlidou, S., Golze, J. and Sester, M. (2022).__ Dataset: GPS 
79
__Zourlidou, S., Golze, J. and Sester, M. (2022).__ Dataset: GPS 
            
66
Trajectory Dataset of the Region of Hannover, Germany. 
80
Trajectory Dataset of the Region of Hannover, Germany. 
            
67
https://doi.org/10.25835/9bidqxvl\r\n\r\n* __Zourlidou, S., Golze, J. 
81
https://doi.org/10.25835/9bidqxvl\r\n\r\n* __Zourlidou, S., Golze, J. 
            
68
and Sester, M. (2022).__ Dataset: Traffic Regulator Ground-truth 
82
and Sester, M. (2022).__ Dataset: Traffic Regulator Ground-truth 
            
69
Information for the Chicago Trajectory Dataset. 
83
Information for the Chicago Trajectory Dataset. 
            
70
https://doi.org/10.25835/0vifyzqi\r\n\r\n* __Zourlidou, S., Golze, J. 
84
https://doi.org/10.25835/0vifyzqi\r\n\r\n* __Zourlidou, S., Golze, J. 
            
71
and Sester, M. (2022).__ Dataset: GPS Trajectory Dataset and Traffic 
85
and Sester, M. (2022).__ Dataset: GPS Trajectory Dataset and Traffic 
            
72
Regulation Information of the Region of Edessa, Greece. 
86
Regulation Information of the Region of Edessa, Greece. 
            
73
https://doi.org/10.25835/v0mzwob3\r\n\r\n* __Zourlidou, S., Golze, J. 
87
https://doi.org/10.25835/v0mzwob3\r\n\r\n* __Zourlidou, S., Golze, J. 
            
74
and Sester, M. (2022).__ Dataset: Traffic Regulator Ground-truth 
88
and Sester, M. (2022).__ Dataset: Traffic Regulator Ground-truth 
            
75
Information of the City of Hannover, Germany. 
89
Information of the City of Hannover, Germany. 
            
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      "description": "Intersection C with overlaid trajectory samples 
            
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      "description": "Intersection D with overlaid trajectory samples 
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      "description": "Intersection D with overlaid trajectory samples 
            
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and background image.",
            
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      "format": "PNG",
            
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      "description": "Intersection E with overlaid trajectory samples 
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      "description": "Intersection E with overlaid trajectory samples 
            
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and background image.",
            
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      "format": "PNG",
            
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      "description": "Intersection F with overlaid trajectory samples 
232
      "description": "Intersection F with overlaid trajectory samples 
            
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and background image.",
            
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      "format": "PNG",
            
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resource/d02b7f48-3669-4497-9fe0-5015fb74ead4/download/junctionf.png",
            
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      "created": "2020-09-14T09:28:06.901537",
            
241
      "description": "Contains all crossing trajectories of 
255
      "description": "Contains all crossing trajectories of 
            
242
__intersection A__ with the following structure:\r\n\r\n* gid\r\n* 
256
__intersection A__ with the following structure:\r\n\r\n* gid\r\n* 
            
243
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
257
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
            
244
northutm\r\n* eastutm\r\n* speed",
258
northutm\r\n* eastutm\r\n* speed",
            
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      "format": "CSV",
            
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      "hash": "",
            
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      "last_modified": "2020-09-14T09:30:13.084821",
            
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d31f5cd/resource/4be6c2d0-3f28-4945-9639-a53e8a5513a7/download/a.csv",
            
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      "url_type": ""
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      "created": "2020-09-14T09:28:41.054344",
            
266
      "description": "Contains all crossing trajectories of 
280
      "description": "Contains all crossing trajectories of 
            
267
__intersection B__ with the following structure:\r\n\r\n* gid\r\n* 
281
__intersection B__ with the following structure:\r\n\r\n* gid\r\n* 
            
268
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
282
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
            
269
northutm\r\n* eastutm\r\n* speed",
283
northutm\r\n* eastutm\r\n* speed",
            
270
      "format": "CSV",
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      "mimetype_inner": null,
            
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      "name": "JunctionB.csv",
291
      "name": "JunctionB.csv",
            
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      "package_id": "1a97c0df-4659-43bd-99e9-d2573d31f5cd",
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298
d31f5cd/resource/7d20ecb4-4e5d-4e00-a052-279a82d6098c/download/b.csv",
            
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      "url_type": ""
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      "url_type": ""
            
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304
      "created": "2020-09-14T09:30:38.269882",
            
291
      "description": "Contains all crossing trajectories of 
305
      "description": "Contains all crossing trajectories of 
            
292
__intersection C__ with the following structure:\r\n\r\n* gid\r\n* 
306
__intersection C__ with the following structure:\r\n\r\n* gid\r\n* 
            
293
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
307
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
            
294
northutm\r\n* eastutm\r\n* speed",
308
northutm\r\n* eastutm\r\n* speed",
            
295
      "format": "CSV",
309
      "format": "CSV",
            
296
      "hash": "",
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      "hash": "",
            
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      "id": "80fc1fbd-28d8-4e49-afa0-8a29dbc58840",
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      "id": "80fc1fbd-28d8-4e49-afa0-8a29dbc58840",
            
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312
      "last_modified": "2020-09-14T09:30:38.233091",
            
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      "metadata_modified": "2023-01-12T13:14:29.118191",
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      "metadata_modified": "2023-08-04T08:46:52.241874",
            
300
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314
      "mimetype": "text/csv",
            
301
      "mimetype_inner": null,
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      "mimetype_inner": null,
            
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      "name": "JunctionC.csv",
316
      "name": "JunctionC.csv",
            
303
      "package_id": "1a97c0df-4659-43bd-99e9-d2573d31f5cd",
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      "package_id": "1a97c0df-4659-43bd-99e9-d2573d31f5cd",
            
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      "size": 72674,
            
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      "state": "active",
321
      "state": "active",
            
308
      "url": 
322
      "url": 
            
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d31f5cd/resource/80fc1fbd-28d8-4e49-afa0-8a29dbc58840/download/c.csv",
323
d31f5cd/resource/80fc1fbd-28d8-4e49-afa0-8a29dbc58840/download/c.csv",
            
310
      "url_type": ""
324
      "url_type": ""
            
311
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325
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312
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326
    {
            
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      "cache_last_updated": null,
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      "cache_last_updated": null,
            
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      "cache_url": null,
            
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      "created": "2020-09-14T09:30:53.716147",
329
      "created": "2020-09-14T09:30:53.716147",
            
316
      "description": "Contains all crossing trajectories of 
330
      "description": "Contains all crossing trajectories of 
            
317
__intersection D__ with the following structure:\r\n\r\n* gid\r\n* 
331
__intersection D__ with the following structure:\r\n\r\n* gid\r\n* 
            
318
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
332
track_id\r\n* trip_id\r\n* date\r\n* timestamp\r\n* unixtime\r\n* 
            
319
northutm\r\n* eastutm\r\n* speed",
333
northutm\r\n* eastutm\r\n* speed",
            
320
      "format": "CSV",
334
      "format": "CSV",
            
321
      "hash": "",
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      "hash": "",
            
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      "id": "5eccd8be-3eea-493c-a0c8-ab8d9cc19824",
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  "title": "Speed profiles and GPS Trajectories for Traffic Rule 
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  "title": "Speed profiles and GPS Trajectories for Traffic Rule 
            
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Recognition (6 Junctions, Hannover, Germany)",
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