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Journal ArticleDOI

Safety Benefits of Forward Collision Warning, Brake Assist, and Autonomous Braking Systems in Rear-End Collisions

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TLDR
The dramatic reductions in serious and fatal injuries that a PCS, which is one of the first intelligent vehicle technologies to be deployed in production cars, can bring to highway safety when available throughout the fleet is shown.
Abstract
This paper examines the potential effectiveness of the following three precollision system (PCS) algorithms: 1) forward collision warning only; 2) forward collision warning and precrash brake assist; and 3) forward collision warning, precrash brake assist, and autonomous precrash brake. Real-world rear-end crashes were extracted from a nationally representative sample of collisions in the United States. A sample of 1396 collisions, corresponding to 1.1 million crashes, were computationally simulated as if they occurred, with the driver operating a precollision-system-equipped vehicle. A probability-based framework was developed to account for the variable driver reaction to the warning system. As more components were added to the algorithms, greater benefits were realized. The results indicate that the exemplar PCS investigated in this paper could reduce the severity (i.e., ΔV) of the collision between 14% and 34%. The number of moderately to fatally injured drivers who wore their seat belts could have been reduced by 29% to 50%. These collision-mitigating algorithms could have prevented 3.2% to 7.7% of rear-end collisions. This paper shows the dramatic reductions in serious and fatal injuries that a PCS, which is one of the first intelligent vehicle technologies to be deployed in production cars, can bring to highway safety when available throughout the fleet. This paper also presents the framework of an innovative safety benefits methodology that, when adapted to other emerging active safety technologies, can be employed to estimate potential reductions in the frequency and severity of highway crashes.

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Citations
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Journal ArticleDOI

Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques

TL;DR: Frontal collision due to unsafe cut-ins is the target crash type of this paper and the cross-entropy method is used to recursively search for the optimal skewing parameters to accelerate the verification of AVs in simulations and controlled experiments.
Journal ArticleDOI

In the Passenger Seat: Investigating Ride Comfort Measures in Autonomous Cars

TL;DR: The novel concept of the loss of driver controllability is introduced here, and traditional comfort measures are examined and autonomous passenger awareness factors are proposed and path-planning methods are categorized in light of the offered factors.
Journal ArticleDOI

Effectiveness of low speed autonomous emergency braking in real-world rear-end crashes.

TL;DR: The findings showed a 38 percent overall reduction in rear-end crashes for vehicles fitted with AEB compared to a comparison sample of similar vehicles, and areas requiring further research were identified and widespread fitment through the vehicle fleet is recommended.
Journal ArticleDOI

Recent advances in connected and automated vehicles

TL;DR: A comprehensive review on five selected subjects that lie in the heart of CAV research, showing how they interact with each other and how they can be integrated into a seamless user experience.
Journal ArticleDOI

An Overview of Vehicular Communications

Fabio Arena, +1 more
- 01 Jan 2019 - 
TL;DR: The main aim of the review carried out in this paper is to examine and assess the most relevant systems, applications, and communication protocols that will distinguish the future road infrastructures used by vehicles.
References
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Journal ArticleDOI

A theory of visual control of braking based on information about time-to-collision.

TL;DR: A mathematical analysis of the changing optic array at the driver's eye indicates that the simplest type of visual information, which would be sufficient for controlling braking and likely to be easily picked up by the driver, is information about time-to-collision, rather than information about distance, speed, or acceleration/deceleration.
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Collision warning timing, driver distraction, and driver response to imminent rear-end collisions in a high-fidelity driving simulator.

TL;DR: Analysis of the braking process showed that warnings provide a potential safety benefit by reducing the time required for drivers to release the accelerator, but they do not, however, speed application of the brake, increase maximum deceleration, or affect meanDeceleration.
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AIS 2005: A contemporary injury scale

TL;DR: The abbreviated injury scale (AIS) is the only dictionary specifically designed as a system to define the severity of injuries throughout the body and provides measures of injury severity that can be used to stratify and classify injury severity in all body regions.
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Model-Based Threat Assessment for Avoiding Arbitrary Vehicle Collisions

TL;DR: A model-based algorithm that estimates how the driver of a vehicle can either steer, brake, or accelerate to avoid colliding with an arbitrary object and is computationally efficient and can be used to assist the driver in avoiding or mitigating collisions with all types of road users in all kinds of traffic scenarios.
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Automated On-Ramp Merging System for Congested Traffic Situations

TL;DR: An automated merging system that was developed with two principal goals, i.e., to permit the merging vehicle to sufficiently fluidly enter the major road to avoid congestion on the minor road and to modify the speed of the vehicles already on the main road to minimize the effect on that already congested main road, is described.
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