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Potential of Cooperative Intelligent Transport System Services to Mitigate Risk Factors Associated With Emergency Vehicle Accidents
Swedish National Road and Transport Research Institute, Traffic and road users, Driver and vehicle. Department of Computer and Information Science, Linköping University.ORCID iD: 0000-0001-9724-8456
Swedish National Road and Transport Research Institute, Traffic and road users, Driver and vehicle.ORCID iD: 0000-0002-0330-7695
Linköping University, Sweden.ORCID iD: 0000-0001-5943-0679
2023 (English)In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, Vol. 2677, no 3, p. 999-1015Article in journal (Refereed) Published
Abstract [en]

Emergency vehicles (EVs) are at high risk of accidents during emergency driving. To make use of countermeasures to mitigate these risks, it is important to understand under what circumstances EV-related accidents occur. The common risk factors for EV-related accidents were examined through a systematic literature review. A total of 22 articles were examined for risk factors associated with EV-related accidents. The most reported risk factors were, in order of frequency, intersections, daytime, dry roads, clear weather, urban roads, traffic signals, and angular collisions. The articles were also reviewed for suggested countermeasures to mitigate the risk factors. The most commonly suggested countermeasures were driver training for EV operators, educating the public, exercising caution at intersections, wearing a seatbelt, and intelligent vehicle technologies. Cooperative intelligent transport systems (C-ITSs) have the potential to mitigate the risks of EV-related accidents. Therefore, three C-ITS services were investigated: EV approaching, EV preemption, and geofencing. They could all be used to inform, warn, or control aspects of driving. Each suggested service has the potential to decrease risk factors for EV-related accidents. The current literature review provides guidance on under what circumstance and in what form C-ITSs could be beneficial to prevent EV-related accidents. Further research is needed to examine behavior when drivers are introduced to C-ITSs.

Place, publisher, year, edition, pages
Sage Publications, 2023. Vol. 2677, no 3, p. 999-1015
Keywords [en]
operations, traffic signal systems, signal priority, V2I, V2X, safety, safety performance and analysis, crash data, sustainability and resilience, transportation systems resilience, disaster response, recovery, and business continuity, emergency response, first responder
National Category
Vehicle and Aerospace Engineering
Identifiers
URN: urn:nbn:se:vti:diva-18961DOI: 10.1177/03611981221119459Scopus ID: 2-s2.0-85153381736OAI: oai:DiVA.org:vti-18961DiVA, id: diva2:1715730
Available from: 2022-12-02 Created: 2022-12-02 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)
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.   

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.   

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2024. p. 115
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 Applied Psychology
Identifiers
urn:nbn:se:vti:diva-21320 (URN)10.3384/9789180758055 (DOI)9789180758048 (ISBN)9789180758055 (ISBN)
Public defence
2024-11-22, Ada Lovelace, B-building, Campus Valla, 13:15 (English)
Opponent
Supervisors
Funder
Swedish Transport Administration, TRV 2020/25755Vinnova, 2018-01523
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: 2024-11-25 Created: 2024-11-25 Last updated: 2025-02-14Bibliographically approved

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