Skip to main content
Log in

Modeling Travel Time Under ATIS Using Mixed Linear Models

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

The objective of this paper is to model travel time when drivers are equipped with pre-trip and/or en-route real-time traffic information/advice. A travel simulator with a realistic network and real historical congestion levels was used as a data collection tool. The network included 40 links and 25 nodes. This paper presents models of the origin-to-destination travel time and en-route short-term route (link) travel time under five different types and levels of advanced traveler information systems (ATIS). Mixed linear models with the repeated observation's technique were used in both models. Different covariance structures (including the independent case) were developed and compared. The effect of correlation was found significant in both models. The trip travel time analysis showed that as the level of information increases (adding en-route to the pre-trip and advice to the advice-free information), the average travel time decreases. The model estimates show that providing pre-trip and en-route traffic information with advice could result in significant savings in the overall travel time. The en-route short-term (link) travel time analysis showed that the en-route short-term (link) information has a good chance of being used and followed. The short-term qualitative information is more likely to be used than quantitative information. Learning and being familiar with the system that provides the information decreases en-route short-term delay.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Abdalla M (2003) Modeling Multiple Route Choice Paradigms Under Different Types and Levels of ATIS Using Correlated Data, Ph.D. dissertation, University of Central Florida

  • M Abdel-Aty F Abdalla (2002) Design and development of a computer simulation tool to collect data that support hybrid travel models under ATIS Proceedings of the Annual Conference of the Canadian Society for Civil Engineering Montreal, Quebec, Canada

    Google Scholar 

  • M Abdel-Aty R Kitamura P Jovanis (1997) ArticleTitleUsing stated preference data for studying the effect of advanced traffic information on driver's route choice Transportation Research Part C 5 IssueID1 39–50

    Google Scholar 

  • M Abdel-Aty R Kitamura P Jovanis (1995) ArticleTitleInvestigating effect of travel time variability on route choice using repeated measurement stated preference data Transportation Research Record 1493 39–45

    Google Scholar 

  • Abdel-Aty M, Vaughn K, Jovanis P, Kitamura R, & Mannering F (1994a) Impact of traffic information on commuters' behavior: empirical results from Southern California and their implications for ATIS. The Proceedings of the 1994 Annual Meeting of IVHS America, pp. 823–830

  • M Abdel-Aty R Kitamura P Jovanis K Vaughn (1994b) Investigation of Criteria Influencing Route Choice: Initial Analysis Using Revealed and Stated Preference Data California University Davis

    Google Scholar 

  • R Arnott A De-Palma R Lindsey (1990) ArticleTitleDeparture time and route choice for the morning commute Transportation Research Part B 24 209–228

    Google Scholar 

  • P Bonsall T Parry (1991) ArticleTitleUsing an interactive route-choice simulator to investigate driver's compliance with route guidance advice Transportation Research Record 1306 59–68

    Google Scholar 

  • P Chen K Srinivasan H Mahmassani (1999) ArticleTitleEffect of information quality on compliance behavior of commuters under real-time traffic information Transportation Research Record 1676 53–60

    Google Scholar 

  • W. Chen P Jovanis (2003) Analysis of Driver En-Route Guidance Compliance and Driver with ATIS using a Travel Simulation Experiment presented in the 81st Transportation Research Meeting Washington, DC

    Google Scholar 

  • Delvert K (1997) Heterogeneous Agents Facing Route Choice: Experienced versus Inexperienced Tripmakers. Presented at IATBR `97, Austin, TX

  • R Garrido H Mahmassani (2000) ArticleTitleForecasting freight transportation demand with the space-time multinomial probit model Transportation Research Part B 34 IssueID5 403–418

    Google Scholar 

  • Gopinath D (1995) Modeling Heterogeneity in Discrete Choice Processes: Application to Travel Demand Ph.D. Thesis, MIT

  • L Guerin W Stroup (2000) A simulation study of evaluation PROC MIXED analysis of repeated measures data Proceedings of the 12th Annual Conference on Applied Statistics in Agriculture Manhattan, KS: Kansas State University

    Google Scholar 

  • R Jou H Mahmassani (1998) Day-To-Day Dynamics of Urban Commuter Departure Time and Route Switching Decisions: Joint Model Estimation Elsevier New York

    Google Scholar 

  • A Khattak J Schofer F Koppelman (1995) ArticleTitleEffect of traffic information on commuters' propensity to change route and departure time Journal of Advanced Transportation 29 193–212 Occurrence Handle10.1002/atr.5670290205

    Article  Google Scholar 

  • R Kitamura D Bunch (1990) Heterogeneity and State Dependence in Household Car Ownership: A panel Analysis Using Ordered-Response Probit Models with Error Components Transportation and Traffic Theory Elsevier Oxford 477–496

    Google Scholar 

  • K Koutsopoulos Y Duse-Anthony D Fisher S Duffy (2000) ArticleTitleThe framing of drivers' route choice when travel time information provided under varying degrees of cognitive load Human Factors 42 IssueID3 470–481

    Google Scholar 

  • R Littell W Stroup R Freund (1996a) SAS for Linear Models, Fourth edition SAS Institute Inc., USA Cary, NC ISBN0-387-95027-3

    Google Scholar 

  • Y Liu H Mahmassani (1998) ArticleTitleDynamic aspects of departure time and route decision behavior under advanced traveler information systems (ATIS): modeling framework and experimental results Transportation Research Record 1645 111–119

    Google Scholar 

  • J Louviere G Woodworth (1983) ArticleTitleDesign and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data Journal of Marketing Research XX 350–367

    Google Scholar 

  • H Mahmassani Y Liu (1999) ArticleTitleDynamics of commuting decision behavior under advanced traveler information systems Transportation Research Part C 7 IssueID2 91–107

    Google Scholar 

  • H Mahmassani T Hu (1997) ArticleTitleDay-to-day evolution of network flows under real-time information and reactive signal control Transportation Research Part C 5 51–69

    Google Scholar 

  • F Mannering S Kim W Barfield L Ng (1994) ArticleTitleStatistical analysis of commuters' route, mode, and departure time flexibility Transportation Record C 2 IssueID1 35–47

    Google Scholar 

  • F Mannering (1987) ArticleTitleAnalysis of the impact of interest rates on automobile demand Transportation Research Record 1116 10–14

    Google Scholar 

  • Morikawa T (1994) Correcting state dependence and serial correlation in the RP/SP combined estimation method. Transportation Journal 21(2)

  • Pallottino S & Grazia M (1988) Shortest Path Algorithms in Transportation Models: Classical and Innovative Aspects. In Marcotte P and Nguyen S (eds) Equilibrium and Advanced Transportation Modeling (pp. 245–28)

  • R Reiss N Gartner S. Cohen (1991) ArticleTitleDynamic control and traffic performance in a freeway corridor: a simulation study Transportation Research Part A, 25 IssueID5 267–276 Occurrence Handle10.1016/0191-2607(91)90143-E

    Article  Google Scholar 

  • SAS/STAT (2003), Technical Support Resources, Version 8.2

  • S Searle G Casella C McCulloch (1992) Variance Components. John Wiley & Sons Inc New York

    Google Scholar 

  • S Searle (1971) Linear Models John Wiley & Sons Inc. New York

    Google Scholar 

  • R Sengupta B Hongola (1998) Estimating ATIS benefits for the Smart Corridor Partners for Advanced Transit and Highways Institute of Transportation Studies University of California Berkeley

    Google Scholar 

  • M Stokes C Davis G Koch (2000) Categorical data analysis using the SAS system EditionNumbersecond edition, SAS Institute Cary, NC

    Google Scholar 

  • K Vaughn R Kitamura P Jovanis (1995a) ArticleTitleExperimental analysis and modeling of advice compliance: results from advanced traveler information system simulation experiments Transportation Research Record 1485 18–26

    Google Scholar 

  • K Vaughn P Reddy M Abdel-Aty R Kitamura P Jovanis (1995b) ArticleTitleRoute choice and information use: initial results simulation experiment Transportation Research Record 1516 61–91

    Google Scholar 

  • Verbeke G, & Molenberghs G (2000) Linear Mixed Models for Longitudinal Data. In: Springer series in Statistics, ISBN 0-387-95027-3, Springer-Verlag New York, Inc

  • R Wolfinger M Chang (1996) Comparing the SAS® GLM and MIXED Procedures for repeated observations SAS institute INC Cary, NC

    Google Scholar 

  • Wunderlich K (1996) An assessment of pre-trip and en route ATIS benefits in a simulated regional urban network. Proceedings of the third world congress on Intelligent Transport Systems at Orlando

  • T Yamamoto S Fujii R Kitamura H Yoshida (2000) ArticleTitleAn analysis of time allocation, departure time and route choice behavior under congestion pricing Transportation Research Record 1725 95–101

    Google Scholar 

  • S Zhao N Harata K Ohta (1996) Assessing driver benefits from information provision: a logit model incorporating perception band of information Proceedings of the 24th annual Passenger Transport Research Conference London, England

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Abdel-Aty.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Abdalla, M.F., Abdel-Aty, M. Modeling Travel Time Under ATIS Using Mixed Linear Models. Transportation 33, 63–82 (2006). https://doi.org/10.1007/s11116-005-5354-y

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-005-5354-y

Key words

Navigation