000119604 001__ 119604
000119604 005__ 20240319081005.0
000119604 0247_ $$2doi$$a10.1016/j.trf.2022.10.005
000119604 0248_ $$2sideral$$a130409
000119604 037__ $$aART-2022-130409
000119604 041__ $$aeng
000119604 100__ $$0(orcid)0000-0003-3793-669X$$aHernando Mazón, A.$$uUniversidad de Zaragoza
000119604 245__ $$aEffect of design factors on drivers’ understanding of variable message signs locating traffic events
000119604 260__ $$c2022
000119604 5060_ $$aAccess copy available to the general public$$fUnrestricted
000119604 5203_ $$aBackground: This article addresses how to combine three elements (a pictogram, an arrow, a city) in a variable message sign (VMS) to locate temporary events (e.g., “congestion before Milan”). We adopted the G1c stack model as a design template, an Advanced Directional Sign (ADS) recommended by the 1968 Convention to locate cities, which can be easily adapted to modern VMS. However, as most of the VMS in operation are not full-matrix, we have also adapted this design to more restrictive display conditions. This adaptation critically concerned the arrow function on the message that either points up broadly (generically, as in G1c) or connects with the city more specifically (explicit). Although G1c reads top-down like a verbal text, previous studies indicated drivers’ preference for bottom-up landmark order in VMS, so both ordering criteria were compared in the present study. Methods: The experiment involved 99 people (70 drivers and 29 drivers in training). Participants were informed that they would see various VMS reporting certain events (e.g., congestion) related to one of four cities along the road. Their task was to identify the event location (before, after the city) after seeing blocks of two consecutive messages (first a complementary message, then the target message), limiting their response to the content of the second message. Three design-focused factors were tested: typographical alignment (left or centre), landmark order (bottom-up or top-down), and arrow function (explicit or generic). The rate of correct location answers was the dependent variable. Results: Results revealed that comprehension varied greatly depending on the arrow’s function and the placing of elements. In the explicit-arrow messages, comprehension was good both in the Top-down and Bottom-up conditions, but in the generic-arrow messages, only in the Bottom-up condition was comprehension good. Likewise, understanding was better in the Before condition than in the After condition in all combinations of Landmark order and Arrow function conditions. In general, left alignment of the central column elements of the VMS improved comprehension respective to centred alignment. Finally, the complementary message factor had an effect under certain circumstances. Practical implications: The messages displaying a generic arrow (following the G1c model) were better understood when the landmarks were ordered bottom-up, not top-down. In addition, explicit-arrow messages were better understood per se (in the absence of a complementary message) than generic-arrow messages. Overall, this work suggests that improving our understanding of how thought processes and design features relate to each other can contribute to safer driving nationally and internationally.
000119604 536__ $$9info:eu-repo/grantAgreement/ES/MIR/SPIP2015-01761
000119604 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000119604 590__ $$a4.1$$b2022
000119604 592__ $$a1.352$$b2022
000119604 591__ $$aTRANSPORTATION$$b18 / 37 = 0.486$$c2022$$dQ2$$eT2
000119604 593__ $$aApplied Psychology$$c2022$$dQ1
000119604 591__ $$aPSYCHOLOGY, APPLIED$$b26 / 83 = 0.313$$c2022$$dQ2$$eT1
000119604 593__ $$aTransportation$$c2022$$dQ1
000119604 593__ $$aCivil and Structural Engineering$$c2022$$dQ1
000119604 593__ $$aAutomotive Engineering$$c2022$$dQ1
000119604 594__ $$a8.4$$b2022
000119604 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000119604 700__ $$0(orcid)0000-0002-6596-2978$$aLucas Alba, A.$$uUniversidad de Zaragoza
000119604 700__ $$0(orcid)0000-0003-2160-7509$$aBlanch Micó, M.T.
000119604 700__ $$0(orcid)0000-0003-3492-7544$$aLombas, A.S.$$uUniversidad de Zaragoza
000119604 7102_ $$14009$$2620$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Metod.Ciencias Comportam.
000119604 7102_ $$14009$$2730$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicología Básica
000119604 773__ $$g91 (2022), 223-235$$pTransp. res., Part F Traffic psychol. behav.$$tTransportation research. Part F, Traffic psychology and behaviour$$x1369-8478
000119604 8564_ $$s2202191$$uhttps://zaguan.unizar.es/record/119604/files/texto_completo.pdf$$yVersión publicada
000119604 8564_ $$s1934724$$uhttps://zaguan.unizar.es/record/119604/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000119604 909CO $$ooai:zaguan.unizar.es:119604$$particulos$$pdriver
000119604 951__ $$a2024-03-18-14:31:33
000119604 980__ $$aARTICLE