Enriched travel demand estimation by including zonal and traveler characteristics and their relationships

J. P. Van Der Vliet; A. J. Pel; J. W.C. Van Lint

doi:10.1109/MTITS.2017.8005696

Enriched travel demand estimation by including zonal and traveler characteristics and their relationships

J. P. Van Der Vliet, A. J. Pel, J. W.C. Van Lint

Transport and Planning

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

77 Downloads (Pure)

Abstract

Current procedure in travel demand estimation models is to separately deal with attraction, production and trip distribution, where the latter typically assumes inverse distance proportionality. We show that this procedure leads to errors in the demand estimation, particularly when dealing with very specific zones and heterogeneous travel behavior. We argue that this traditional procedure is rooted in traditional ways of data collection, while new (big) data sources allow direct observation of travel demand patterns. Using such data, we propose an enriched travel demand estimation method in which zonal and traveler characteristics and their relationships are consistently carried over from the empirical data into the demand model. This can improve both the validity and richness of demand estimations.

Original language	English
Title of host publication	5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
Publisher	IEEE
Pages	351-355
Number of pages	5
ISBN (Electronic)	9781509064847
DOIs	https://doi.org/10.1109/MTITS.2017.8005696
Publication status	Published - 8 Aug 2017
Event	5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Naples, Italy Duration: 26 Jun 2017 → 28 Jun 2017

Conference

Conference	5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017
Abbreviated title	MT-ITS 2017
Country/Territory	Italy
City	Naples
Period	26/06/17 → 28/06/17

Keywords

big data
demand estimation
itravel demand

Access to Document

10.1109/MTITS.2017.8005696

20170602_paperv3_MT-ITSAccepted author manuscript, 1.85 MB

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Van Der Vliet, J. P., Pel, A. J., & Van Lint, J. W. C. (2017). Enriched travel demand estimation by including zonal and traveler characteristics and their relationships. In 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings (pp. 351-355). Article 8005696 IEEE. https://doi.org/10.1109/MTITS.2017.8005696

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abstract = "Current procedure in travel demand estimation models is to separately deal with attraction, production and trip distribution, where the latter typically assumes inverse distance proportionality. We show that this procedure leads to errors in the demand estimation, particularly when dealing with very specific zones and heterogeneous travel behavior. We argue that this traditional procedure is rooted in traditional ways of data collection, while new (big) data sources allow direct observation of travel demand patterns. Using such data, we propose an enriched travel demand estimation method in which zonal and traveler characteristics and their relationships are consistently carried over from the empirical data into the demand model. This can improve both the validity and richness of demand estimations.",

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Van Der Vliet, JP, Pel, AJ & Van Lint, JWC 2017, Enriched travel demand estimation by including zonal and traveler characteristics and their relationships. in 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings., 8005696, IEEE, pp. 351-355, 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017, Naples, Italy, 26/06/17. https://doi.org/10.1109/MTITS.2017.8005696

Enriched travel demand estimation by including zonal and traveler characteristics and their relationships. / Van Der Vliet, J. P.; Pel, A. J.; Van Lint, J. W.C.
5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings. IEEE, 2017. p. 351-355 8005696.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AB - Current procedure in travel demand estimation models is to separately deal with attraction, production and trip distribution, where the latter typically assumes inverse distance proportionality. We show that this procedure leads to errors in the demand estimation, particularly when dealing with very specific zones and heterogeneous travel behavior. We argue that this traditional procedure is rooted in traditional ways of data collection, while new (big) data sources allow direct observation of travel demand patterns. Using such data, we propose an enriched travel demand estimation method in which zonal and traveler characteristics and their relationships are consistently carried over from the empirical data into the demand model. This can improve both the validity and richness of demand estimations.

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Enriched travel demand estimation by including zonal and traveler characteristics and their relationships

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