| People | Locations | Statistics |
|---|---|---|
| Mouftah, Hussein T. |
| |
| Dugay, Fabrice |
| |
| Rettenmeier, Max |
| |
| Tomasch, Ernst | Graz |
|
| Cornaggia, Greta |
| |
| Palacios-Navarro, Guillermo |
| |
| Uspenskyi, Borys V. |
| |
| Khan, Baseem |
| |
| Fediai, Natalia |
| |
| Derakhshan, Shadi |
| |
| Somers, Bart | Eindhoven |
|
| Anvari, B. |
| |
| Kraushaar, Sabine | Vienna |
|
| Kehlbacher, Ariane |
| |
| Das, Raj |
| |
| Werbińska-Wojciechowska, Sylwia |
| |
| Brillinger, Markus |
| |
| Eskandari, Aref |
| |
| Gulliver, J. |
| |
| Loft, Shayne |
| |
| Kud, Bartosz |
| |
| Matijošius, Jonas | Vilnius |
|
| Piontek, Dennis |
| |
| Kene, Raymond O. |
| |
| Barbosa, Juliana |
|
Saramäki, Jari
Aalto University
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2023Estimating inter-regional mobility during disruption: Comparing and combining different data sourcescitations
- 2021Navigability assessment of large-scale redesigns in nine public transport networks: Open timetable data approachcitations
- 2019Assessment of large-scale transitions in public transport networks using open timetable data: case of Helsinki metro extensioncitations
- 2018A collection of public transport network data sets for 25 citiescitations
- 2016Estimation and monitoring of city-to-city travel times using call detail recordscitations
Places of action
| Organizations | Location | People |
|---|
document
Estimation and monitoring of city-to-city travel times using call detail records
Abstract
henever someone makes or receives a call on a mobile telephone, a Call Detail Record (CDR) is automatically generated by the operator for billing purposes. CDRs have a wide range of applications beyond billing, from social science to data-driven development. Recently, CDRs have been increasingly used to study human mobility, whose understanding is crucial e.g. for planning efficient transportation infrastructure. A major difficulty in analyzing human mobility using CDR data is that the location of a cell phone user is not recorded continuously but typically only when a call is initiated or a text message is sent. In this paper we address this problem, and develop a method for estimating travel times between cities based on CDRs that relies not on individual trajectories of people, but their collective statistical properties. We apply our method to data from Senegal, released by Sonatel and Orange for the 2014 Data for Development Challenge. We turn CDR mobility traces to estimates on travel times between Senegalese cities, filling an existing gap in knowledge. Moreover, the proposed method is shown to be highly valuable for monitoring travel conditions and their changes in near real-time, as demonstrated by measuring the decrease in travel times due to the opening of the Dakar-Diamniadio highway. Overall, our results indicate that it is possible to extract reliable de facto information on typical travel times that is useful for a variety of audiences ranging from casual travelers to transport infrastructure planners.
Topics
Search in FID move catalog