TY - GEN
T1 - Travel-Time Computation Based on GPS Data
AU - Torp, Kristian
AU - Andersen, Ove
AU - Thomsen, Christian
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - The volume of GPS data collected from moving vehicles has increased significantly over the last years. We have gone from GPS data being collected every few minutes to data being collected every second. With large quantities of GPS data available it is possible to analyze the traffic on most of the road network without installing road-side equipment. A very important key performance indicator (KPI) in traffic planning is travel time. For this reason, this paper describes how travel time can be computed from GPS data. Of particular interest is how the travel time is affected by the weather. The work presented here is an extension of previous work on computing accurate travel time from GPS data. In this paper, the logical data model is explained in more details and the result section showing weather’s impact on travel time has been significantly extended with previously unpublished material.
AB - The volume of GPS data collected from moving vehicles has increased significantly over the last years. We have gone from GPS data being collected every few minutes to data being collected every second. With large quantities of GPS data available it is possible to analyze the traffic on most of the road network without installing road-side equipment. A very important key performance indicator (KPI) in traffic planning is travel time. For this reason, this paper describes how travel time can be computed from GPS data. Of particular interest is how the travel time is affected by the weather. The work presented here is an extension of previous work on computing accurate travel time from GPS data. In this paper, the logical data model is explained in more details and the result section showing weather’s impact on travel time has been significantly extended with previously unpublished material.
UR - http://www.scopus.com/inward/record.url?scp=85096530376&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-61627-4_4
DO - 10.1007/978-3-030-61627-4_4
M3 - Article in proceeding
AN - SCOPUS:85096530376
SN - 9783030616267
T3 - Lecture Notes in Business Information Processing
SP - 70
EP - 92
BT - Big Data Management and Analytics - 9th European Summer School, eBISS 2019, Revised Selected Papers
A2 - Kutsche, Ralf-Detlef
A2 - Zimányi, Esteban
PB - Springer Science+Business Media
T2 - 9th European Business Intelligence and Big Data Summer School, eBISS 2019
Y2 - 30 June 2019 through 5 July 2019
ER -