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Road Trauma in Regional and Remote Australia and New Zealand in Preparedness for ADAS Technologies and Autonomous Vehicles

Author

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  • Sujanie Peiris

    (Accident Research Centre, Monash University, 21 Alliance Ln, Clayton VIC, 3800 Melbourne, Australia)

  • Janneke Berecki-Gisolf

    (Accident Research Centre, Monash University, 21 Alliance Ln, Clayton VIC, 3800 Melbourne, Australia)

  • Bernard Chen

    (Department of Mechanical and Aerospace Eng., Monash University, 17 College Walk, Clayton VIC, 3800 Melbourne, Australia)

  • Brian Fildes

    (Accident Research Centre, Monash University, 21 Alliance Ln, Clayton VIC, 3800 Melbourne, Australia)

Abstract

Achieving remote and rural road safety is a global challenge, exacerbated in Australia and New Zealand by expansive geographical variations and inconsistent population density. Consequently, there exists a rural-urban differential in road crash involvement in Australasia. New vehicle technologies are expected to minimise road trauma globally by performing optimally on high quality roads with predictable infrastructure. Anecdotally, however, Australasia’s regional and remote areas do not fit this profile. The aim of this study was to determine if new vehicle technologies are likely to reduce road trauma, particularly in regional and remote Australia and New Zealand. An extensive review was performed using publicly available data. Road trauma in regional and remote Australasia was found to be double that of urban regions, despite the population being approximately one third of that in urban areas. Fatalities in 100 km/h + speed zones were overrepresented, suggestive of poor speed limit settings. Despite new vehicle ownership in regional and remote Australasia being comparable to major cities, road infrastructure supportive of new vehicle technologies appear lacking, with only 1.3–42% of all Australian roads, and 67% of all New Zealand roads being fully sealed. With road quality in regional and remote areas being poorly mapped, the benefits of Advanced Driver-Assistance Systems (ADAS) technologies cannot be realised despite the fact new vehicles with these technologies are penetrating the fleet. Investments should be made into sealing and separating roads but more importantly, for mapping the road network to create a unified tracking system which quantifies readiness at a national level.

Suggested Citation

  • Sujanie Peiris & Janneke Berecki-Gisolf & Bernard Chen & Brian Fildes, 2020. "Road Trauma in Regional and Remote Australia and New Zealand in Preparedness for ADAS Technologies and Autonomous Vehicles," Sustainability, MDPI, vol. 12(11), pages 1-26, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4347-:d:362903
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    References listed on IDEAS

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    1. Woldeamanuel, Mintesnot & Nguyen, Dang, 2018. "Perceived benefits and concerns of autonomous vehicles: An exploratory study of millennials’ sentiments of an emerging market," Research in Transportation Economics, Elsevier, vol. 71(C), pages 44-53.
    2. Itf, 2015. "Automated and Autonomous Driving: Regulation under Uncertainty," International Transport Forum Policy Papers 7, OECD Publishing.
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    Cited by:

    1. Matúš Šucha & Ralf Risser & Kristýna Honzíčková, 2021. "Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    2. Sujanie Peiris & Stuart Newstead & Janneke Berecki-Gisolf & Bernard Chen & Brian Fildes, 2022. "Quantifying the Lost Safety Benefits of ADAS Technologies Due to Inadequate Supporting Road Infrastructure," Sustainability, MDPI, vol. 14(4), pages 1-23, February.
    3. Sujanie Peiris & Janneke Berecki-Gisolf & Stuart Newstead & Bernard Chen & Brian Fildes, 2021. "Development of a Methodology for Estimating the Availability of ADAS-Dependent Road Infrastructure," Sustainability, MDPI, vol. 13(17), pages 1-18, August.
    4. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2023. "Implications of automated vehicles for physical road environment: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    5. Qian Cheng & Xiaobei Jiang & Haodong Zhang & Wuhong Wang & Chunwen Sun, 2020. "Data-Driven Detection Methods on Driver’s Pedal Action Intensity Using Triboelectric Nano-Generators," Sustainability, MDPI, vol. 12(21), pages 1-17, October.
    6. Bruce Corben & Sujanie Peiris & Suryaprakash Mishra, 2022. "The Importance of Adopting a Safe System Approach—Translation of Principles into Practical Solutions," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    7. Jaeheon Choi & Kyuil Lee & Hyunmyung Kim & Sunghi An & Daisik Nam, 2020. "Classification of Inter-Urban Highway Drivers’ Resting Behavior for Advanced Driver-Assistance System Technologies using Vehicle Trajectory Data from Car Navigation Systems," Sustainability, MDPI, vol. 12(15), pages 1-20, July.

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