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The operational safety of automated driving system (ADS)-equipped vehicles (AVs) must be quantified using well-defined metrics in order to gain an unambiguous understanding of the level of risk associated with AV deployment on public roads. In this research, efforts to evaluate the operational safety assessment (OSA) metrics introduced in prior work by the Institute of Automated Mobility (IAM) are described. An initial validation of the proposed set of OSA metrics involved using the open-source simulation software Car Learning to Act (CARLA) and Scenario Runner, which are used to place a subject vehicle in selected scenarios and obtain measurements for the various relevant OSA metrics. Car following scenarios were selected from the list of 37 pre-crash scenarios identified by the National Highway Traffic Safety Administration (NHTSA) as the most common driving situations that lead to crash events involving two light vehicles.

As the deployment of automated vehicles (AVs) on public roadways expands, there is growing interest in establishing metrics that can be used to evaluate vehicle operational safety. The set of Operational Safety Assessment (OSA) metrics, that include several safety envelope-type metrics, previously proposed by the Institute of Automated Mobility (IAM) are a step towards this goal. The safety envelope OSA metrics can be computed using kinematics derived from video data captured by infrastructure-based cameras and thus do not require on-board sensor data or vehicle-to-infrastructure (V2I) connectivity, though either of the latter data sources could enhance kinematic data accuracy. However, the calculation of some metrics includes certain vehicle-specific parameters that must be assumed or estimated if they are not known a priori or communicated directly by the vehicle.

The operational safety of automated driving system (ADS)-equipped vehicles (AVs) needs to be quantified for an understanding of risk, requiring the measurement of parameters as they relate to AVs and human driven vehicles alike. In prior work by the Institute of Automated Mobility (IAM), operational safety metrics were introduced as part of an operational safety assessment (OSA) methodology that provide quantification of behavioral safety of AVs and human-driven vehicles as they interact with each other and other road users. To calculate OSA metrics, the data capture system must accurately and precisely determine position, velocity, acceleration, and geometrical relationships between various safety-critical traffic participants. The design of an infrastructure-based system that is intended to capture the data required for calculation of OSA metrics is addressed in this paper.

A significant number of vehicle-to-vehicle collisions involve front-to-rear impacts at low- to moderate-speeds. While a variety of studies have been conducted since the 1990s involving fore-aft collisions, those discussing the response of late model passenger vehicles during progressively more severe impacts are limited. In this study, four inline, front-rear tests were conducted using two midsize sedans of the same make, model, and year. An instrumented Hybrid III 50th percentile-male Anthropomorphic Test Device (ATD) was located in the driver seat of each sedan and was restrained using the standard three-point seat belt system. Instrumentation on the vehicles included tri-axis accelerometers and seat belt load cells. For each test, the centerlines of the vehicles were aligned, and the striking vehicle impacted the stationary target vehicle at closing speeds of 4.6, 7.9, 13.5, and 20.9 mph (7.4, 12.7, 21.7, and 33.6 kph).