Mind the map! The impact of transit maps on path choice in public transit

https://doi.org/10.1016/j.tra.2011.04.001Get rights and content

Abstract

This paper investigates the impact of schematic transit maps on passengers’ travel decisions. It does two things: First, it proposes an analysis framework that defines four types of information delivered from a transit map: distortion, restoration, codification, and cognition. It then considers the potential impact of this information on three types of travel decisions: location, mode, and path choices.1 Second, it conducts an empirical analysis to explore the impact of the famous London tube map on passengers’ path choice in the London Underground (LUL). Using data collected by LUL from 1998 to 2005, the paper develops a path choice model and compares the influence between the distorted tube map (map distance) and reality (travel time) on passengers’ path choice behavior. Results show that the elasticity of the map distance is twice that of the travel time, which suggests that passengers often trust the tube map more than their own travel experience on deciding the “best” travel path. This is true even for the most experienced passengers using the system. The codification of transfer connections on the tube map, either as a simple dot or as an extended link, could affect passengers’ transfer decisions. The implications to transit operation and planning, such as trip assignments, overcrowding mitigation, and the deployment of Advanced Transit Information System (ATIS), are also discussed.

Research highlights

► Schematic transit maps offer important but geographically inaccurate information. ► Such map information could affect passengers’ location, mode, or path choices. ► A path choice model is developed for 18,894 passengers in the London Underground. ► Passengers trust the map (map distance) more than their own experience (travel time). ► Codification of transfer stations on a map affects passengers’ transfer decisions.

Introduction

Traveling in a transit system often involves a greater degree of uncertainty than traveling on a road network due to the complexity of transit systems and the stochastic nature of services (Hickman and Wilson, 1995). Transit users often need more information in planning travel than road travelers, such as operating hours, fare and fare media, waiting and travel times, access and egress, transfers, station locations, and seat availability (Abdel-Aty et al., 1996, Cluett et al., 2003). Such information is critical to passengers’ travel decisions (Khattak et al., 2003, Chorus et al., 2007), and the provision of information could be a powerful planning tool to guide individual decisions and to enhance the overall efficiency of the system (Polak and Jones, 1993, Ben-Elia and Shiftan, 2010).

While most studies in this field have focused on Advanced Traveler Information Systems (ATIS), this paper considers an alternative perspective and targets traditional information media. In particular, it focuses on the effect of schematic transit maps on travel decisions in public transit. The central argument is that a transit map has a tremendous impact on a passenger’s perceptions and his or her usage of the transit system. If implemented appropriately, a transit map can be a valuable tool to solve planning and operation problems in a cost-effective way.

This paper first develops a conceptual framework of the impact of the map on transit travel and then focuses on a specific travel decision: path choice in public transit. The case study of the London Underground indicates that passengers often (mis)trust a transit map more than their actual experience; they often take a path that looks shorter on the system map but is longer in reality compared with alternative paths. They also try to avoid transfer stations when the coded connection on a map looks less convenient than it actually is. The implications of the map on transit planning and operations are also discussed.

Section snippets

Literature

The importance of maps to spatial behavior has been well documented (Woods, 1992, Hutchins, 1995, MacEachren, 2004). However, in the field of transportation, maps have attracted little attention. Little is known about the travel information delivered by a map to a traveler and the effect of a map on travel decisions. There have been few efforts to incorporate the map as an analytical tool for transportation planning (Jankowski et al., 2001). The author identifies only a few related studies.

Transit map and travel information

A transit map is a schematic diagram that depicts the locations, directions, and connections of stations and lines in a public transit system. It normally does not include service information, such as travel time or crowding.2 A transit map can deliver four types of travel

London Underground and the tube map

London has the world’s oldest underground railway system with services operating since 1863. The system had only one line at the beginning, so the map was simple and fully geographic. When the system grew bigger and became more complex, geographical details began to impair the legibility of the map, and many stations in outer London were cut off from the map (Garland, 1994). Many experiments were performed in the early 1900s, which mainly focused on Central London and gradually teased out the

Modeling the map effect on path choices

To test the transit map effect on passengers’ path choices, a reference is defined as the reality. If a transit map presents a distorted reality, then the key research question is what passengers trust more: the schematic map or their own experience.

In this paper, the map effect is operationalized into two ways: map distance and transfer connection. The former is the distance of a path measured from a transit map. A passenger is often able to infer this distance by reading the transit map and

Results and analysis

Most variables in both models were significant at the 5% level with expected signs. In the Base Model, the more a path had in terms of entry, exit, in-vehicle, initial waiting time, transfer walking or waiting time, the less likely that path was chosen by a passenger. In-vehicle time was perceived as more onerous than the initial waiting time (−0.55 vs. −0.36) probably due to the high frequency of service. Transfer walking was more onerous than entry and exit walking (−0.32 vs. −0.29) while

Discussion and conclusion

This paper investigates the effect of schematic transit maps on travel decisions in public transit systems. The relationship might have significant implications for public transit operation and planning, but so far it has been largely overlooked by both academics and practitioners. The paper first defines four types of information delivered from a transit map: distortion, restoration, codification, and cognition, and then discusses their potential influence on travel location, mode, and path

Acknowledgements

The author wishes to thank Professor Nigel H.M. Wilson from MIT for his insight that made this study possible. He is also grateful for the valuable comments from Anthony Shorris, Rae Zimmerman, John Attanucci, Andrew Mondschein, and Amy Faust. The path choice model described in this paper was developed by the author with funding support from Transport for London (TfL) through the MIT-TfL Research Initiative.

References (83)

  • S. Raveau et al.

    A topological route choice model for metro

    Transportation Research, Part A

    (2011)
  • P.W. Thorndyke et al.

    Differences in spatial knowledge acquired from maps and navigation

    Cognitive Psychology

    (1982)
  • B. Tversky

    Distortions in memory for maps

    Cognitive Psychology

    (1981)
  • M.A. Abdel-Aty et al.

    The impact of advanced transit information on commuters mode changing

    Journal of Intelligent Transportation Systems

    (1996)
  • T.A. Arentze et al.

    Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics

    Transportation

    (2005)
  • E. Avineri et al.

    The impact of travel time information on travelers’ learning under uncertainty

    Transportation

    (2006)
  • J.N. Bailenson et al.

    The initial segment strategy: a heuristic for route selection

    Memory and Cognition

    (2000)
  • S. Bekhor et al.

    Evaluation of choice set generation algorithms for route choice models

    Annals of Operations Research

    (2006)
  • Ben-Akiva, M.E., Bergman, M.J., Daly, A.J., Ramaswamy, R., 1984. Modelling Inter Urban Route Choice Behavior....
  • E. Ben-Elia et al.

    The combined effect of information and experience on drivers’ route-choice behavior

    Transportation

    (2008)
  • B. Berendt et al.

    Spatial representation with aspect maps

  • P. Bovy et al.

    Route Choice: Wayfinding in Transport Networks

    (1990)
  • C.G. Chorus et al.

    Information impact on quality of multimodal travel choices: Conceptualizations and empirical analyses

    Transportation

    (2007)
  • C.G. Chorus et al.

    Determinants of stated and revealed mental map quality: an empirical study

    Journal of Urban Design

    (2010)
  • Cluett, C., Bregman, S., Richman, J., 2003. Customer preferences for Transit ATIS: Research report. Report No....
  • R.C. Dalton

    The secret is to follow your nose: route path selection and angularity

    Environment and Behavior

    (2003)
  • E.W. Dijkstra

    A note on two problems in connection with graphs

    Numerical Mathematics

    (1959)
  • Dziekan, L., 2008. The transit experience of newcomers to a city – learning phases, system difficulties, and...
  • S.I. Fabrikant et al.

    Cognitively inspired and perceptually salient graphic displays for efficient spatial inference making

    Annals of the Association of American Geographers

    (2010)
  • Fiorenzo-Catalano, S., 2005. Route Set Generation for Multi-modal Networks. PhD Dissertation, UT Delft, the...
  • Freksa, C., 1999. Spatial aspects of task-specific wayfinding maps. In: Gero, J.S., Tversky, B. (Eds.), A...
  • S. Fujii et al.

    Changes in drivers’ perceptions and use of public transport during a freeway closure

    Environment and Behaviour

    (2001)
  • G. Gallo et al.

    Shortest path algorithms

    Annals of Operations Research

    (1988)
  • H.C. Garland et al.

    Transit map color coding and street detail effects on trip planning performance

    Environment and Behavior

    (1979)
  • Garland, K., 1994. Mr. Beck’s Underground Map: A History by Ken Garland. Middlesex: Capital Transport...
  • Golledge, R.G., 1995. Path selection and route preference in human navigation: a progress report. In: Frank, A.U.,...
  • R.G. Golledge

    Wayfinding behavior: cognitive mapping and other spatial process

    (1999)
  • R.G. Golledge et al.

    Changes in drivers’ perceptions and use of public transport during a freeway closure

    Environment and Behavior

    (2001)
  • Golledge, R.G., Garling, T., 2004. Cognitive maps and urban travel. In: Hensher, D.A., Button, K.J., Haynes, K.E.,...
  • R.G. Golledge et al.

    Applications of behavioral research on spatial problems I: cognition

    Progress in Human Geography

    (1990)
  • Cited by (90)

    • Understanding the route choice behaviour of metro-bikeshare users

      2022, Transportation Research Part A: Policy and Practice
    • Advanced Travelers Information Systems (ATIS)

      2021, International Encyclopedia of Transportation: Volume 1-7
    View all citing articles on Scopus
    1

    Path refers to a unique sequence of entry, transfer, and exit stations/stops in the public transit network. The author differentiates between path and route choices because the latter could refer to a situation among different service routes that follow the same physical path, which is not the purpose of this analysis.

    View full text