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The impact of travelinformation onmotorists’ choicepatterns: opportunitiesand limitationsTravel information and travel recommendations aregenerally regarded as key opportunities for influencingmotorists. As recent research shows, however, it isimportant not to set our expectations too high, asingrained behavioural patterns are hard to change.

Harry Timmermans

Car mobility has increasedsignificantly over the past fewdecades and is expected to increasefurther, particularly once the currenteconomic recession is over. Besidesthe general growth in car mobility,there will always continue to be localtraffic problems as a result of thereduced capacity at specific hubs,changes in speed, and the capacity ofthe local network. Both professionalsand academics have concluded that

building more infrastructure in and ofitself will never fully solve congestionissues and that the optimum use ofthe available capacity must becomplementary to an increase incapacity.The Dutch government has introduceda number of measures over the yearsto take maximum advantage of theexisting infrastructure, with free buslanes, traffic management systems,road charges, peak avoidance and

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carpooling being just severalexamples of the measuresimplemented. By and large, theeffectiveness of these measures hasproved to have been very limited,particularly in relation to theexpectations beforehand, whichtended to be very high.The emergence of modern ITresources, including smartphoneapps, could potentially provide newopportunities for influencingmotorists’ transport behaviour. Thistime around, expectations are highonce again. The idea is to providecurrent travel information in order tokeep motorists up­to­date of currentroad network conditions, therebypotentially avoiding congestion.Travel information may also involvealerting users to options (e.g. routesand travel alternatives) of which theywere previously unaware. Analternative option to this type ofdescriptive travel information isprescriptive travel information, whichentails providing specific, personalisedadvice to motorists. This type ofinformation is similar to routesuggestions made by navigationsystems, the difference being that theinformation is dynamic rather thanstatic and that the advice can beprovided in such a variety of ways asto allow the information users toaccess the full potential of the systemThe system can also take into accountpersonal preferences and limitations.The number of apps based on theseprinciples has grown rapidly of late.

The DBR research programmeTRISTAM (Traveller Response andInformation Service Technology:Analysis and Modelling) was designedto gain a greater understanding of theimpact of travel information ontravellers’ behaviour. The sub­projects, for their part, were designed(i) to determine whether passengerswould select a different route, (ii) todetermine what the effects are onday­to­day activity patterns (i.e. notonly the route, but also the time ofdeparture, choice of destination, etc.)and, by extension, what the spatialeffects are, (iii) to develop a broaddefinition of the term “accessibility”,also factoring in travel information,and (iv) to investigate the impact ofteleworking on transport behaviour.The various projects have producedsome interesting results, which areoutlined in this article.

Old habits are hard tochangeThe main conclusion of the DBR studyinto travel information was once againthat expectations of influencing travelbehaviour through travel informationor travel advice should not be toohigh. Due to a variety of factors, theimpact of travel information onbehaviour is less significant than isoften assumed. Commutes andtransport for other purposes are theresult of travellers’ experiences over aperiod of in some cases many years

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and based on their experience theyhave found the most optimal route –or at least one that is acceptable.Transport is characterised by a highlevel of routine behaviour (patterns).This routine behaviour may or maynot be context­dependent (e.g. theday of the week, or activities whichmust be completed), but within thatcontext there is relatively littlevariability. In addition, it is alsoimportant to realise that transport isnot a purpose in and of itself: Theconvenience with which individualsand households organise their day­to­day lives in terms of time and spaceis most important. Any minor timegains do not weigh up against theeffort required to achieve those timegains.Furthermore, if travellers alreadyhave access to real­time information,they tend to study this informationonly when they are already en routeor right before they embark on theirjourney. Passengers do not typicallychoose the perfect departure time,one with minimum delays, and the“routine departure time” is neveradjusted. It appears as thoughpassengers gather real­timeinformation mainly to be notified ofthe expected travel time and arrivaltime. The process of gathering real­time travel information may eliminatesome of the uncertainty regardingarrival time, with passengers beingable to communicate estimatedarrival times to their partner or

colleagues. However, this does notautomatically bring about changes inbehaviour.Passengers tend to only change theirplanned travel­activity pattern (basedon travel information) if they stand tobenefit significantly by doing so; theyare not inclined to change their routesto arrive several minutes earlier orlater, for example. Travel informationbecomes more valuable if the userhas the option to work from home: Inthat case, passengers use theinformation to make a strategicdecision to either go to the office orwork from home. The importance oftravel information also increaseswhen the information corresponds toimportant personal values, such asvalues related to sustainability.In a general sense, we note thatadaptive behaviour is characterisedby as little mental effort as possible.Passengers first change the durationof the journey and the activities theyintend to undertake and only selectan alternative route if the detourwould not be too great and the delayhas turned out to be significantlylonger than usual. They are less likelyto consider other aspects of activitytravel patterns, including a change indestination. It should be noted thatthis is not only a matter ofpassengers being unwilling;interviews with passengers have, infact, taught us that even if apassenger had seriously consideredthe travel advice received, they

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ultimately did not select that routebecause the differences between theregular route and the suggested routewere too small, or because they hadlimited options in terms of changingtheir plans in view of othercommitments. The majority ofpassengers did, as expected, driveout of their residential area and ontoa motorway, and would then exit itagain to get to their final destination.If there were any other possibleroutes in the first place, they onlyinvolved minor changes in the routeto and from the motorway.Another problem is that general travelinformation does not take intoaccount people’s individual schedules,which means there is a significantlikelihood that the travel advicereceived does not constitute animprovement, is difficult toincorporate, or turns out to beirrelevant. In addition, we also sawthat most people’s diaries andschedules are relativelystraightforward and fairly flexible. Aslightly longer travel time does notreally make much of an impact; evenfor business travel, traffic­relateddelays would appear to be sociallyacceptable and make for a simpleexcuse. Mobile phones have made iteasy to inform others of any delayswe may incur. Personal travel advice(i.e. factoring in people’sdiaries/schedules and flexibility) maybe (slightly) more effective.The fact that this does not concern astrategic decision is further

highlighted by the fact that real­timetravel information (e.g. TomTom HDtravel information), provided it isavailable, is the most frequentlyconsulted source of information.Travel information on the radio is onealternative; roadside information isconsulted far less frequently. Thissuggests that investments in digitalservices are more effective thaninvestments in hardware.Beware of “secondary and tertiaryeffects”Whereas the focus used to be mainlyon the positive effects of travelinformation and more effective use ofthe existing capacity, we must notclose our eyes to the possiblenegative long­term effects. Based oneconomic theory, it is to be expectedthat reduced congestion will result inpeople spending more time at home.This can potentially result insuburbanisation and, by extension, toan increase in the number ofkilometres travelled.IT is not just an essential conditionfor travel information: it is alsorequired to enable people to workfrom home. The option of telework isoften regarded as a key factor inreducing mobility, but we have beenaware for some time that this issomewhat simplified reasoning. Notbeing required to travel during peaktimes could mean that people willstart travelling by car to otheractivities or that another familymember will now use vehicle for allmanner of activities, for which they

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would normally use the bike. TheDDR study into travel information alsorevealed that teleworking for only apart of the day in order to avoidpeak­hour traffic can result inmarginal economic loss, Since, ifmore passengers travel at a laterhour, this could lead to seriouscongestion later in the day. In thatcase, passengers are not distributedover time and the traffic peak merelyshifts, without significantly reducingtravel costs.

Impact of travel informationdepends on large number ofvariablesIt is not possible, them, to draw easyblanket conclusions regarding thecontribution of travel information tosustainable mobility. The effects ofthis policy vary depending on thesituation and the intended usergroup. The extent to whichpassengers will be able to adapt theirbehaviour in the shorter or longerterm depends on the specific localsituation, their schedule, and thelevel of flexibility of the time pressurethey experience, along with theextent to which the travel advicereceived matches passengers’personal preferences and the physicalpossibilities and limitations of theirjourney. The margins, in this context,are small and expectations of theimpact of policy and trafficmanagement should not beexcessively high.

Harry Timmermans(H.J.P.Timmermans@tue.nl) is aProfessor of Urban Planning in theDepartment of the Built Environmentat Eindhoven University ofTechnology.

The TRISTRAM study, which formspart of the Sustainable Accessibility ofthe Randstad Conurbation (SARC)programme, was conducted by Gisellede Moraes Ramos(g.m.ramos@tudelft.nl), Ruihua ZackLu (R.Lu@tudelft.nl), Zahra Parvaneh(Z.Parvaneh@tue.nl), Sergejs Gubins(s.gubins@vu.nl), Anna Kononova andtheir supervisors Harry Timmermans(h.j.p.timmermans@tue.nl), SergeHoogendoorn(s.p.hoogendoorn@tud.nl), CasparChorus (c.g.chorus@tud.nl) and ErikVerhoef (everhoef@feweb.vu.nl)

BibliographyGubins, Sergejs & Erik T. Verhoef (2011)Teleworking and Congestion: A DynamicBottleneck Analysis, Tinbergen InstituteDiscussion Paper TI 2011­096/3Gubins, Sergejs & Erik T. Verhoef (2013)Dynamic Congestion and UrbanEquilibrium, Tinbergen Institute DiscussionPaper TI 2012­137/VIIIGubins, Sergejs, Erik T. Verhoef & Thomasde Graaff (2012) Welfare effects of roadpricing and traffic information underalternative ownership regimes,Transportation Research Part A: Policy andPractice 46(8): 1304­1317Lu , Ruihua, Caspar G. Chorus & Bert vanWee (2012) The effects of different formsof ICT on accessibility – a behaviouralmodel and numerical examples,

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Transportmetrica,DOI:10.1080/18128602.2012.742171Parvaneh, Zahra, Theo Arentze, HarryTimmermans (2012) UnderstandingTravelers’ Behavior in Provision of TravelInformation: A Bayesian Belief Approach,Proceedings of 15th meeting of the EUROWorking Group on TransportationRamos, GM, Daamen, W & Hoogendoorn,SP (2011) Expected utility theory,prospect theory, and regret theorycompared for prediction of route choicebehavior, Transportation Research Record,Vol. 2230, pp. 19­28.Ramos, GM, Daamen, W & Hoogendoorn,SP (2013) Modelling travellers’heterogeneous route choice behaviour asprospect maximizers, The Journal ofChoice Modelling 6 (2013) 17–33.http://dx.doi.org/10.1016/j.jocm.2013.04.002Ramos, GM, Frejinger, E, Daamen, W &Hoogendoorn, SP (2012) A revealedpreference study on route choices in acongested network with real­timeinformation, Presented at the 13thInternational Conference on TravelBehaviour Research. July 15th ­ 20th,2012 ­ Toronto ­ Canada.