Identifying crashes potentially affected by conditionally automated vehicles in Finland

Fanny Malin (Corresponding Author), Anne Silla, Johannes Mesimäki, Satu Innamaa, Harri Peltola

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
83 Downloads (Pure)

Abstract

The objective of the study was to identify the number and national fraction of crashes that could be affected by universal adoption of conditionally automated vehicles (SAE3) based on the expected number of injury crashes, fatalities, and serious injuries in Finland. The study considered passenger cars with automated driving systems (ADS) for motorways and urban areas. The results show that of the national annual average, the motorway ADS has the potential to affect at maximum 3.3% of injury crashes, 3.1% of fatalities, and 3.2% of serious injuries. The corresponding fractions for urban ADS in the four largest Finnish cities were: 2.2%, 1.1% and 2.5%. Of the cities’ annual average, urban ADS has the potential to affect at the most 17.4% of injury crashes, 17.1% of fatalities, and 26.8% of serious injuries. Although the market introduction of these ADS is on the horizon, deployment can be expected to be slow, indicating a need for additional measures to reach the traffic safety goals.
Original languageEnglish
Pages (from-to)665-676
Number of pages12
JournalJournal of Intelligent Transportation Systems: Technology, Planning, and Operations
Volume27
Issue number5
DOIs
Publication statusPublished - 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Automated driving
  • Empirical Bayes method
  • killed and seriously injured

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