Improving A Priori Demand Estimates Transport Models using Mobile Phone Data
A Rotterdam-Region Case
Bibliographic Data
| ID | 15318506 |
|---|---|
| Authors | Luc Johannes Josephus Wismans (0000-0002-5262-8735, University of Twente, corresponding author), K Friso (DAT.Mobility, Deventer, Netherlands), J Rijsdijk (Municipality of Rotterdam, Rotterdam, Netherlands), S W de Graaf (Goudappel Coffeng, Deventer, Netherlands), Jan F Keij, J Keij (Mezuro, Weesp, Netherlands) |
| Year | 2018 |
| Volume | 25 |
| Issue | 2 |
| Pages | 63-83 |
| Publication date | 2018-04-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Urban Technology (JOURNAL) |
| Journal identifiers | ISSN: 1063-0732 • E-ISSN: 1466-1853 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/10630732.2018.1442075 |
| OpenAlex | W2795867444 |
| Language | EN |
| Citations received | 3 |
| References cited | 14 |
Mobile phone data are a rich source to infer all kinds of mobility- related information. In this research, we present an approach where mobile phone data are used and analyzed for enriching the transport model of the region of Rotterdam. In this research Call Detail Records (CDR) are used from a mobile phone provider in the Netherlands that serves between 30 and 40 percent of Dutch mobile phones. Accessing these data provides travel information of about one-third of the Dutch population. No other data source is known that gives travel information at a national scale at this high level. The raw data of one month is processed into basic information which is subsequently translated into OD-information (Origin-Destination) based on several decision rules. This OD information is compared with the traditionally estimated a priori OD matrix of the Rotterdam transport model and the Dutch yearly national household travel survey. Based on the analysis and assignment results, an approach is developed to combine the mobile phone OD-information and an a priori OD matrix using the best of both worlds. Results show a better match of the assignment results of this matrix with the counts indicating a better quality of the matrix
A priori and a posteriori · Geography · Mobile phone · Phone · Population · Raw data · Telecommunications · Transport engineering · Travel behavior · Travel survey · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Transportation Planning and Optimization · Urban Transport and Accessibility
| Citations per year | 0.6 |
|---|---|
| Citation span | 2021 - 2024 (4) |
| Highly cited | No |