Injury mitigation estimates for an intersection driver assistance system in straight crossing path crashes in the United States

Abstract

Objective: Accounting for one fifth of all crashes and one sixth of all fatal crashes in the United States, intersection crashes are among the most frequent and fatal crash modes. Intersection advanced driver assistance systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (Maximum Abbreviated Injury Scale [MAIS] 3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS. Methods: This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of 5 separate activation timing thresholds, 3 separate computational latency times, and 2 different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-V. The results were then compiled across all crashes in order to estimate system effectiveness. Results: The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 to 0.5 s was found to reduce crash and injury prevention estimates by approximately one third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to changes in activation timing (warning delivered 1.0 to 3.0 s prior to impact). If autonomous braking was used, system effectiveness was found to largely plateau for activation timings greater than 1.5 s prior to impact. In general, the results of this study suggest that I-ADAS will be 2-3 times more effective if an autonomous braking system is utilized over a warning-based system. Conclusions: This study highlights the potential effectiveness of I-ADAS in the U.S. vehicle fleet, while also indicating the sensitivity of system effectiveness to design specifications. The results of this study should be considered by designers of I-ADAS and evaluators of this technology considering a future I-ADAS safety test.

Crash and injury prevention estimates for intersection driver assistance systems in left turn across path/opposite direction crashes in the United States

“…A diagram depicting an LTAP/OD crash is shown in Figure 1. Previous work investigated the crash and injury benefits of a hypothetical I-ADAS in straight crossing path (SCP) crashes (Scanlon et al 2017) using the same I-ADAS system. Sander (2017) computed intersection automatic emergency braking (AEB) benefits using a different system design with effectiveness estimates developed using the German In-Depth Accident Study crash data set.…”

Connected and autonomous vehicle injury loss events: Potential risk and actuarial considerations for primary insurers

“…These predictions have since tapered to ‘optimistic' scenarios describing a 50% adoption rate and 35% market share by 2040 (Forsgren, 2018), while research studies have suggested highly‐automated vehicles to have a market share between 24%‐87% by 2045 (Bansal & Kockelman, 2017). A higher market share of CAVs will result in higher collision reductions and fewer collisions being realized (Bareiss et al, 2019; Scanlon et al, 2017), which we expect in turn to change to the shifted loss distributions outlined in Section 2. Regardless, a rapid introduction of these vehicles requires a significant buy‐in from low‐ and middle‐income motorists, who would need to spend significantly beyond their typical vehicle purchase to secure a vehicle with self‐driving capabilities (Litman, 2015).…”

“…The scenarios we present in Section 2 do not envision that single-loss event models will drastically change with a gradual introduction of ADAS-enabled (Level 2) and partiallyautomated (Level 3) vehicles. Although it is difficult to determine the exact mixture of automated levels on the road, a greater level of safety afforded by ADAS-enabled vehicles will ensure that many incidents will be avoided or mitigated (Bareiss et al, 2019;Scanlon et al, 2015Scanlon et al, , 2017. In addition, initial forays in to CAV-sharing mobility services will increase the number of deadheading vehicles, decreasing occupancy rates on average.…”

“…Simulation studies have highlighted the effectiveness of Level 2 ADAS technologies (where two systems act concurrently to avoid or mitigate an oncoming hazard) in reducing collision and injury rates relative to vehicles with no intervention systems (Scanlon et al, 2017). A number of studies have also used collision data to retroactively assess the extent to which Level 1 and 2 ADAS mechanisms would have prevented collisions (Bareiss et al, 2019; Östling et al, 2019; Spicer et al, 2018).…”

Estimated benefit of automated emergency braking systems for vehicle–pedestrian crashes in the United States

“…Walking speed was estimated based on pedestrian age. Estimated walking speed ranged from 1.15 to 1.45 m/s (Gates et al 2006 The pedestrian AEB system braking peak magnitude was assumed to reach 0.8 g in dry road conditions, 0.4 g in wet road conditions, and 0.3 g in icy road conditions (Scanlon et al 2017). It was assumed that AEB would increase braking deceleration at a jerk of À30 m/s 3 (Lubbe and Kullgren 2015).…”