Predicting Individual Trip Destinations With Artificial Potential Fields.

A. Zonta, S.K. Smit, Evert Haasdijk

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper presents a method to model the intended destination of a subject in real time, based on a trace of position information and prior knowledge of possible destinations. In contrast to most work in this field, it does so without the need for prior analysis of habitual travel patterns. The method models the certainty of each POI by means of a virtual charge, resulting in an artificial potential field that reflects the current estimate of the subject’s intentions. The virtual charges are updated as new information about the subject’s position arrives. We experimentally compare a number of update rules with various parameter settings, showing that it is important to take the distance to a potential destination into account when updating the charge.
LanguageEnglish
Title of host publicationSmart Cities
Subtitle of host publicationSecond International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings
PublisherSpringer/Verlag
Pages118-127
DOIs
Publication statusPublished - 26 May 2017
EventInternational Conference on Smart Cities - Malaga, Spain
Duration: 14 Jun 201716 Jun 2017
http://smart-ct2017.lcc.uma.es/index.html

Conference

ConferenceInternational Conference on Smart Cities
Abbreviated titleSmart-CT 2017
CountrySpain
CityMalaga
Period14/06/1716/06/17
Internet address

Keywords

  • Human behavior
  • Intention analysis
  • Destination Prediction
  • GPS
  • Trajectory Database

Cite this

Zonta, A., Smit, S. K., & Haasdijk, E. (2017). Predicting Individual Trip Destinations With Artificial Potential Fields. In Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings (pp. 118-127). Springer/Verlag. https://doi.org/10.1007/978-3-319-59513-9_12
Zonta, A. ; Smit, S.K. ; Haasdijk, Evert. / Predicting Individual Trip Destinations With Artificial Potential Fields. Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings. Springer/Verlag, 2017. pp. 118-127
@inproceedings{9d74c68bafa4453c95789b3b4c769ecd,
title = "Predicting Individual Trip Destinations With Artificial Potential Fields.",
abstract = "This paper presents a method to model the intended destination of a subject in real time, based on a trace of position information and prior knowledge of possible destinations. In contrast to most work in this field, it does so without the need for prior analysis of habitual travel patterns. The method models the certainty of each POI by means of a virtual charge, resulting in an artificial potential field that reflects the current estimate of the subject’s intentions. The virtual charges are updated as new information about the subject’s position arrives. We experimentally compare a number of update rules with various parameter settings, showing that it is important to take the distance to a potential destination into account when updating the charge.",
keywords = "Human behavior, Intention analysis, Destination Prediction, GPS, Trajectory Database",
author = "A. Zonta and S.K. Smit and Evert Haasdijk",
year = "2017",
month = "5",
day = "26",
doi = "10.1007/978-3-319-59513-9_12",
language = "English",
pages = "118--127",
booktitle = "Smart Cities",
publisher = "Springer/Verlag",

}

Zonta, A, Smit, SK & Haasdijk, E 2017, Predicting Individual Trip Destinations With Artificial Potential Fields. in Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings. Springer/Verlag, pp. 118-127, International Conference on Smart Cities, Malaga, Spain, 14/06/17. https://doi.org/10.1007/978-3-319-59513-9_12

Predicting Individual Trip Destinations With Artificial Potential Fields. / Zonta, A.; Smit, S.K.; Haasdijk, Evert.

Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings. Springer/Verlag, 2017. p. 118-127.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Predicting Individual Trip Destinations With Artificial Potential Fields.

AU - Zonta, A.

AU - Smit, S.K.

AU - Haasdijk, Evert

PY - 2017/5/26

Y1 - 2017/5/26

N2 - This paper presents a method to model the intended destination of a subject in real time, based on a trace of position information and prior knowledge of possible destinations. In contrast to most work in this field, it does so without the need for prior analysis of habitual travel patterns. The method models the certainty of each POI by means of a virtual charge, resulting in an artificial potential field that reflects the current estimate of the subject’s intentions. The virtual charges are updated as new information about the subject’s position arrives. We experimentally compare a number of update rules with various parameter settings, showing that it is important to take the distance to a potential destination into account when updating the charge.

AB - This paper presents a method to model the intended destination of a subject in real time, based on a trace of position information and prior knowledge of possible destinations. In contrast to most work in this field, it does so without the need for prior analysis of habitual travel patterns. The method models the certainty of each POI by means of a virtual charge, resulting in an artificial potential field that reflects the current estimate of the subject’s intentions. The virtual charges are updated as new information about the subject’s position arrives. We experimentally compare a number of update rules with various parameter settings, showing that it is important to take the distance to a potential destination into account when updating the charge.

KW - Human behavior

KW - Intention analysis

KW - Destination Prediction

KW - GPS

KW - Trajectory Database

U2 - 10.1007/978-3-319-59513-9_12

DO - 10.1007/978-3-319-59513-9_12

M3 - Conference contribution

SP - 118

EP - 127

BT - Smart Cities

PB - Springer/Verlag

ER -

Zonta A, Smit SK, Haasdijk E. Predicting Individual Trip Destinations With Artificial Potential Fields. In Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings. Springer/Verlag. 2017. p. 118-127 https://doi.org/10.1007/978-3-319-59513-9_12