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Driver’s gaze behavior when approached by an emergency vehicle – The effects of in-car warnings and system introduction
Linköping University, Department of Computer and Information Science, Human-Centered Systems. Linköping University, Faculty of Arts and Sciences. Swedish National Road and Transport Research Institute, Linköping, Linköping, Sweden.ORCID iD: 0000-0001-9724-8456
Swedish National Road and Transport Research Institute, Linköping, Linköping, Sweden.
Linköping University, Department of Computer and Information Science, Human-Centered Systems. Linköping University, Faculty of Arts and Sciences. Region Östergötland, Regionledningskontoret, Center for Disaster Medicine and Traumatology.ORCID iD: 0000-0001-5943-0679
2025 (English)In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 109, p. 137-146Article in journal (Refereed) Published
Abstract [en]

This study investigates drivers’ eye gaze behavior in response to Emergency Vehicle Approaching (EVA) warnings. EVA warnings, delivered through in-car alerts, provide advance notice of approaching EVs, enabling drivers to move over in time. Previous research indicates that EVA warnings influence driver behavior positively, promoting safer interactions. This study expands further by exploring the role of system introduction to make drivers benefit from EVA warnings. A simulator experiment with 73 participants was conducted. Before driving, half of the participants were introduced to the EVA system. The participants were driving on a highway and were overtaken by EVs twice during a 20-minute drive. During the drive, half of participants received EVA warnings. Gaze distribution was analyzed in three areas of interest (Forward, Mirrors, Dashboards). Analysis of driving simulator data did not reveal any differences in driving behaviors. However, the analysis of drivers’ gaze distribution suggests that EVA warnings contribute to increased mirror usage, indicating early scanning for approaching EVs. Furthermore, drivers who were introduced to the EVA system before driving but never received an EVA warning in the simulator looked through the front windshield less than drivers who were introduced and received an EVA warning. This study contributes to understanding the driver gaze behavior when receiving an in-car warning for emergency vehicles and supports previous findings regarding EVA warnings positive impact of driver behavior.

Place, publisher, year, edition, pages
Elsevier, 2025. Vol. 109, p. 137-146
Keywords [en]
Emergency vehicle, In-car warning, Emergency vehicle approaching, Eye tracking, Driving simulator, Intelligent transport system
National Category
Vehicle and Aerospace Engineering
Identifiers
URN: urn:nbn:se:liu:diva-210398DOI: 10.1016/j.trf.2024.12.010ISI: 001385342000001Scopus ID: 2-s2.0-85211442307OAI: oai:DiVA.org:liu-210398DiVA, id: diva2:1920427
Note

Funding: This research was supported by the Swedish Transport Administration (TRV 2020/25755), Nordic Way 3 (2018- EU-TM-0026-S) and SAFER (FP18).

Available from: 2024-12-11 Created: 2024-12-11 Last updated: 2025-02-14Bibliographically approved
In thesis
1. Emergency Vehicle Approaching: Warning Drivers Using Cooperative Intelligent Transport Systems
Open this publication in new window or tab >>Emergency Vehicle Approaching: Warning Drivers Using Cooperative Intelligent Transport Systems
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Emergency Vehicle Approaching : Att varna förare genom det Samverkande Intelligenta Transportsystemet
Abstract [en]

Driving an emergency vehicle can be difficult. The driver of the emergency vehicle must navigate, communicate with emergency services, often drive at high speeds, and take surrounding traffic into account. Civilian drivers are required by law to give way to emergency vehicles with lights and sirens activated. Despite this, they sometimes fail to move over. One reason is not noticing the emergency vehicle in time.   

This dissertation aims to understand how technology can support civilian drivers in their interactions with emergency vehicles. One form of technology used to make drivers move over is emergency vehicle lighting. The results of this dissertation show that alternative designs of emergency vehicle lighting can affect driver behavior and that the current designs are not always suited to promote the most desirable driver behavior.   

Another technological approach to supporting drivers in their interactions with emergency vehicles is the use of Cooperative Intelligent Transport Systems (C-ITS). One C-ITS service is the Emergency Vehicle Approaching (EVA) warning. An EVA warning is an early in-car warning sent out to the driver before being overtaken by an emergency vehicle, providing more time to move over. Three driving simulator studies with EVA warnings were conducted in this dissertation. The results indicate that EVA warnings make drivers move over more quickly and thereby decrease delay time for emergency vehicles. Furthermore, there is a learning effect when receiving multiple EVA warnings, implying that drivers move over more quickly once they are familiar with the system. One of the simulator studies used eye tracking and showed that EVA warnings make drivers scan mirrors earlier, compared to when not receiving an EVA warning.   

An EVA warning is distributed based on the most probable path of the emergency vehicle. If the driver of the emergency vehicle decides on another route, there is a risk of false EVA warnings. Therefore, this dissertation explored how false alarms, and false expectations of EVA warnings, affect drivers. Receiving false alarms makes drivers move over more slowly in future interactions and negatively affects attitudes toward the EVA system. Furthermore, wrongly expecting an EVA warning makes drivers less attentive to the road ahead.    

In conclusion, both emergency vehicle lighting and EVA warnings can support civilian drivers in their interactions with emergency vehicles. It can decrease the risks of both collisions and delays. However, to implement a large-scale deployment of C-ITS, Sweden needs digital infrastructure to support secure data exchange  

Abstract [sv]

Att framföra ett utryckningsfordon är utmanande. Utryckningsföraren förväntas navigera, kommunicera med larmcentralen, framföra utryckningsfordonet i inte sällan höga hastigheter och samtidigt ta hänsyn till omgivande trafik. Bilister är enligt lag tvungna att lämna fri väg för utryckningsfordon med blåljus och sirener. Trots det misslyckas ibland förare med att lämna fri väg. En anledning är att de inte hinner uppfatta utryckningsfordonet i tid.

Syftet med denna avhandling är att förstå hur teknik kan stödja förare vid interaktioner med utryckningsfordon. En form av teknik som används för att få förare att lämna fri väg är blåljus. Resultaten av denna avhandling visar att alternativa designlösningar för blåljus kan påverka förarnas beteende och att de nu-varande utformningarna inte alltid är optimala för att främja det mest önskvärda förarbeteendet.   

En annan metod för att stötta förare i deras interaktion med utryckningsfordon är uppkopplad fordonsteknik, så kallat Cooperative Intelligent Transport Systems (C-ITS). En typ av C-ITS-tjänst är Emergency Vehicle Approaching (EVA)-varningar. En EVA-varning är en tidig varning som skickas ut till bilisten innan utryckningsfordonet kör ikapp, vilket ger föraren mer tid att lämna fri väg. Tre förarsimulatorstudier med EVA-varningar genomfördes inom ramen för avhandlingen. Resultaten visar på att EVA-varningar kan få förare att lämna fri väg snabbare och därmed minska förseningar för utryckningsfordon. Dessutom finns det en inlärningseffekt med EVA varningar som innebär att förare lämnar fri väg snabbare när de är bekanta med EVA systemet. I en av simulatorstudierna användes ögonrörelsemätning som visade att EVA-varningar får förare att skanna av speglarna i bilen tidigare, jämfört med när de inte får någon EVA-varning.   

En EVA-varning distribueras baserat på den mest sannolika vägen för utryckningsfordonet. Om föraren av utryckningsfordonet väljer en annan väg finns det risk för falska EVA-varningar. I den här avhandlingen undersöktes därför hur falska larm och en falsk förväntan om EVA-varningar påverkar förare. Att ta emot falska larm påverkade förarnas framtida interaktioner och inställning till EVA-systemet. Dessutom gjorde en felaktig förväntan på en EVA-varning till att förarna var mindre uppmärksamma på vägen framför dem.   

Sammanfattningsvis kan både blåljus och EVA-varningar stödja civila förare i interaktionen med utryckningsfordon. Varningssystemen kan minska riskerna för både kollisioner och förseningar. För att genomföra en storskalig utbyggnad av C-ITS behöver Sverige dock en digital infrastruktur för att stödja säkert datautbyte. 

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2024. p. 84
Series
Linköping Studies in Arts and Sciences, ISSN 0282-9800 ; 891
Keywords
Emergency Vehicles, Intelligent Transport System, Warning, Emergency Vehicle Approaching, Geofencing, Utryckningsfordon, Intelligenta Transportsystem, Varning, Emergency Vehicle Approaching, Geostaket
National Category
Vehicle and Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-208609 (URN)10.3384/9789180758055 (DOI)9789180758048 (ISBN)9789180758055 (ISBN)
Public defence
2024-11-22, Ada Lovelace, B-building, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Note

Funding: The PhD project has been financially supported by the Swedish Transport Administration (TRV 2020/25755) and the European Union. The majority of my included papers (II – V) were written in the context of the European Union project Nordic Way 3 (2018- EU-TM-0026-S). In addition, from the support from the Swedish Transport Administration and European Union, my second study received financial support from Vinnova (2018-01523), and the fourth study from SAFER (FP18). The first study in this dissertation was supported by the company Standby which provided the technical equipment for the experiment.  

Available from: 2024-10-17 Created: 2024-10-17 Last updated: 2025-02-14Bibliographically approved

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Weibull, KajsaPrytz, Erik

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