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Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

There is a strong evidence that the overrepresentation of teen drivers in motor vehicle crashes is mainly due to their poor hazard perception skills, i.e., they are unskilled at appropriately detecting and responding to roadway hazards. This study evaluates two cuing systems designed to help teens better understand their driving environment. Both systems use directional color-coding to represent different levels of proximity between one’s vehicle and outside agents. The first system provides an overview of the location of adjacent objects in a head-up display in front of the driver and relies on drivers’ focal vision (focal cuing system). The second system presents similar information, but in the drivers’ peripheral vision, by using ambient lights (peripheral cuing system). Both systems were retrofitted into a test vehicle (2014 Toyota Camry). A within-subject experiment was conducted at the University of Michigan Mcity test-track facility.

This paper provides an analysis of how communication performance between vehicles using Dedicated Short-range Communication (DSRC) devices varies by antenna mounting, vehicle relative positions and orientations, and between receiving devices. DSRC is a wireless technology developed especially for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. A frequency band near 5.9 GHz has been set aside in the US and other countries for exploring safety and other uses for road vehicles. DSRC devices installed onboard vehicles broadcast their location using global navigation space systems (GNSS), speed, heading, and other information. This can be used to study communication performance in many scenarios including: car-following situations, rear-end crash avoidance, oncoming traffic situations, left turn advisory, head-on crash avoidance and do-not-pass warnings.

Mcity at the University of Michigan in Ann Arbor provides a realistic off-roadway environment in which to test vehicles and drivers in complex traffic situations. It is intended for testing of various levels of vehicle automation, from advanced driver assistance systems (ADAS) to fully self-driving vehicles. In a recent human factors study of interfaces for teen drivers, we performed parallel experiments in a driving simulator and Mcity. We implemented driving scenarios of moderate complexity (e.g., passing a vehicle parked on the right side of the road just before a pedestrian crosswalk, with the parked vehicle partially blocking the view of the crosswalk) in both the simulator and at Mcity.

This paper explores the potential safety performance of “Future Generation” automated speed control crash avoidance systems for Commercial Vehicles. The technologies discussed in this paper include Adaptive Cruise Control (ACC), second and third generation Forward Collision Avoidance and Mitigation Systems (F-CAM) comprised of Forward Collision Warning (FCW) with Collision Mitigation Braking (CMB) technology as applied to heavy trucks, including single unit and tractor semitrailers. The research [1[ discussed in this paper is from a study conducted by UMTRI which estimated the safety benefits of current and future F-CAM systems and the comparative efficacy of adaptive cruise control. The future generation systems which are the focus of this paper were evaluated at two separate levels of product refinement, “second generation” and “third generation” systems.

This paper focuses on the safety performance of Commercial Vehicle Forward Collision Avoidance and Mitigation Systems (F-CAM) that include Forward Collision Warning (FCW) with Collision Mitigation Braking (CMB) technology as applied to heavy trucks, including single unit and tractor semitrailers. The study estimated the safety benefits of a commercially available F-CAM system considered to be representative of products currently in service. The functional characteristics were evaluated and its performance generically modeled to estimate safety benefits. This was accomplished through the following steps: (1) first characterize the actual performance of these systems in various pre-crash scenarios under controlled test track conditions, and then reverse engineering the algorithms that control warnings and automatic braking actions; (2) developing a comprehensive set of simulated crash events representative of actual truck striking rear-end crashes.