Journal of Intelligent Transportation Systems · 2022 · 13 citations · 19 references
Public HealthAutomotive EngineeringInjury PreventionAutonomous VehiclesTransportTransportationIntelligent Transportation SystemsMotor Vehicle Injury PreventionRoad SafetyTraffic Injury PreventionTraffic SafetyTransportation SafetyMotor Vehicle Crash PreventionRoad Traffic CrashesRoad Traffic Injury EpidemiologyRoad Traffic Injury RiskSafety GoalsTraffic Accident RiskTraffic Crash PreventionVehicle Safety
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.
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Examining accident reports involving autonomous vehicles in California
Francesca Favarò, Sky O. Eurich, Michelle Tripp et al. · PLoS ONE · 2017 · 397 citations · Full text