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Automated Driving System Safety: Miles for 95% Confidence in “Vision Zero”

Driving Safety Consulting LLC-Richard Allen Young
  • Technical Paper
  • 2020-01-1205
To be published on 2020-04-14 by SAE International in United States
Engineering reliability models from RAND, MobilEye, and Volvo concluded that billions of miles of on-road data were required to validate that the real-world fatality rate of an “Automated Driving System-equipped vehicle” (AV) fleet for an improvement over human-driven conventional vehicles (CV). RAND said 5 billion miles for 20%, MobileEye 30 billion for 99.9%, and Volvo 5 billion for 50% improvement. All these models used the Gaussian distribution, which is inaccurate for low crash numbers. The current study proposes a new epidemiologic method and criterion to validate real-world AV data with 95% confidence for zero to ten fatal crashes. The upper confidence limit (UL) of the AV fatal crash rate has to be lower than the CV fatal crash rate with 95% confidence. That criterion is met if the UL of the AV fatal crash incidence rate ratio estimate is below one. That UL was estimated using the mid-P exact method for calculating confidence limits for a dual Poisson process, using a one-tailed 95% confidence level. The required AV mileage was adjusted by trial and error…
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A Novel Prediction Algorithm for Heavy Vehicles System Rollover Risk Based on Failure Probability Analysis and SVM Empirical Model

China Automotive Technology and Reseach Center Co.,Ltd-Zhenfeng Wang, Fei Li, Xinyu Wang
Harbin Institute of Technology-Zheng Wang
  • Technical Paper
  • 2020-01-0701
To be published on 2020-04-14 by SAE International in United States
The study of heavy vehicles rollover prediction, especially in algorithm-based heavy vehicles active safety control for improving road handling, is a challenging task for the heavy vehicle industry. Due to the high fatality rate caused by vehicle rollover, how to precisely and effectively predict the rollover of heavy vehicles became a hot topic in both academia and industry. Because of the strong non-linear characteristics of Human-Vehicle-Road interaction and the uncertainty of modeling, the traditional deterministic method cannot predict the rollover hazard of heavy vehicles accurately. To deal with the above issues, this paper applies a probability method of uncertainty to the design of a dynamic rollover prediction algorithm for heavy vehicles and proposes a novel algorithm for predicting the rollover hazard based on the combined empirical model of reliability index and failure probability. Moreover, the paper establishes a classification model of heavy vehicles based on the support vector machine (SVM) and uses the Monte Carlo method to calculate the failure probability of rollover limit state of heavy vehicles. The fishhook, double lane change, and slalom…
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Driver Visual Focus of Attention Estimation in Autonomous Vehicles

Dura Automotive Systems-Iyad Mansour
Oakland University-Alaaldin Hijaz, Wing-Yue Louie, Matthew Bellafaire, Osamah Rawashdeh
  • Technical Paper
  • 2020-01-1037
To be published on 2020-04-14 by SAE International in United States
Abstract-An existing challenge in current state-of-the-art autonomous vehicles is the process of safely transferring control from autonomous driving mode to manual mode because the driver may be distracted with secondary tasks. Such distractions may impair a driver’s situational awareness of the driving environment which will lead to fatal outcomes during a handover. Current state-of-the-art vehicles notify a user of an imminent handover via auditory, visual, and physical alerts but are unable to improve a driver’s situational awareness before a handover is executed. The overall goal of our research team is to address the challenge of providing a driver with relevant information to regain situational awareness of the driving task. In this paper, we introduce a novel approach to estimating a driver’s visual focus of attention using a 2D RGB camera as input to a Multi-Input Convolutional Neural Network with shared weights. The system was validated in a realistic driving scenario. The developed approach is a first step towards estimating a driver’s situational awareness from their observable indicators which will in the future be utilized to…
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Reference test system for machine vision used for ADAS functions

Texas A&M University-Abhishek Nayak, Sivakumar Rathinam, Adam Pike, Swaminathan Gopalswamy
  • Technical Paper
  • 2020-01-0096
To be published on 2020-04-14 by SAE International in United States
LDW and LKA systems have the potential to prevent or mitigate 483,000 crashes in the United States every year which includes 87,000 nonfatal injury crashes and 10,345 fatal crashes. Studies have shown that fatalities due to unintentional roadway departures can be significantly reduced if Lane Departure Warning (LDW) and Lane Keep Assist (LKA) systems are used effectively. While LDW and LKA technologies are available, there has been low customer acceptance and penetration of these technologies. These deficiencies can be traced to the inability of many of the perception systems to consistently recognize lane markings and localize the vehicle with respect to the lane marking in a real-world environment of variable markings, changing weather and occlusions. These challenges translate to (i) inconsistent lane detection; (ii) misidentification of lane markings; and (iii) the inability of the systems to locate lane markings in some conditions. Currently, there is no available standard or benchmark to evaluate the quality of either the lane markings or the perception algorithms. This project seeks to establish a reference test system that could be…
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Comparison of Occupant Fatality Factors in Underride Passenger Car Accidents in India and USA

Mercedes-Benz R&D India Pvt. Ltd.-Muthukumar Muthanandam, B S Vishak Nandan Aathresh, Avinash Penumaka, Vijaya Prakash Kalakala
  • Technical Paper
  • 2020-01-0984
To be published on 2020-04-14 by SAE International in United States
Underride accidents constitute around 5% and 4% of all accidents in India and the US respectively. Yet, the passenger car occupant fatality risk is the highest in this accident configuration when compared to other configurations. Especially in India, the fatality rate is even higher due to minimal usage of underride protection devices in the front, rear and sides of commercial vehicles. This study specifically aims to compare the factors influencing occupant fatality in the rear underride accident configuration, in India and the US. The influencing factors are identified by performing Principal Component Analysis (PCA), which is a linear feature extraction technique. The accident databases considered for this study are RASSI and NASS-CDS. After querying, a total of 88 cases from RASSI and 202 cases from NASS-CDS were extracted, where a passenger vehicle was involved in a rear underride accident with a commercial vehicle. The relevant variables involved in the rear underride accident configuration were initially identified for analysis, followed by an observation of their trends. The data corresponding to these variables were analyzed using PCA.…
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Driver response to left incurring path intrusions at sign-controlled intersections

Kodsi Engineering-Shady Attalla, Sam Kodsi
University of Guelph-Erika Ziraldo, Michele Oliver
  • Technical Paper
  • 2020-01-0886
To be published on 2020-04-14 by SAE International in United States
Straight intersecting path or “side” collisions account for 12% of all motor vehicle crashes and 24% of fatalities. While previous research has examined driver responses to hazards striking from the right (near side), no research has quantified driver responses to hazards striking from the left (far side) of an intersection. The purpose of this study was to measure driver response time (DRT) and response choice for two versions of this scenario. In one condition, the hazard vehicle was initially stopped at the intersection before accelerating into the path of the participant driver. In the other condition, the hazard vehicle approached and entered the intersection while moving at a constant speed of 50km/h. Testing was conducted using an Oktal full car driving simulator. 107 licenced drivers (NFemale=57, NMale=50) completed a short familiarization drive followed by the experimental drive in which they encountered both the initially stopped and moving conditions of the straight path hazard, in a counterbalanced order. DRT was defined as the time between when the hazard vehicle crossed a trigger located two meters from…
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Invesstigation of test method to reproduce Car-to-Car side impact

Nissan Motor Co., Ltd.-Matsuyama Takeo, Ryuji Ootani, Toshiyuki Ueda, Shigeru Hirayama
  • Technical Paper
  • 2020-01-1221
To be published on 2020-04-14 by SAE International in United States
Side impact is one of the severest crash modes among real-world accidents. In US market, even though most of vehicles recently have achieved top rating in crash performance assessment programs, it is reported that there is hardly any sign of decreasing trend in side-impact fatalities for the last few years. In response to this trend, IIHS is planning to introduce a new test protocol. One of clarification points on current side impact tests is whether the present side Moving Deformable Barrier (MDB) test reproduces real-world Car-to-Car (C2C) crash. Hence, this study addressed to identify key factors to reproduce C2C side impact by a series of parametric CAE study of MDB as follows: i) with and without suspension of MDB ii) change of height of Center Of Gravity (COG) of MDB ⅲ) barrier dimensions iv) barrier stiffness. Reproducibility of the MDB tests in the CAE study was evaluated by three indices of struck vehicle such as (1) kinematics, (2) body deformation modes (Plan and Front View) and (3) dummy injuries. As a result, it was found…
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Human Health Risk Assessment of Space Radiation

University of Pittsburgh-Ashmita Rajkumar
  • Technical Paper
  • 2020-01-0020
Published 2020-03-10 by SAE International in United States
Mars has been the topic of colonization and discovery for the last few decades but there have been hindrances in implementing the mission. This focus on Mars colonization has only deepened after the discovery of water on its surface. The discovery of water on Mars has led researchers to believe that its sustainability of life is higher than any other uncolonized planet. Although, life can survive on Mars, it is highly unethical to send communities to Mars without acknowledging the risks, especially those concerning the well being of humans. The risks of living on Mars are slowly unraveling through extensive research, but it is evident that certain health care measures must be taken in order to prevent potentially fatal conditions. One of the biggest problems is health concerns that astronauts face after returning from Mars. Health problems in space have been increasingly difficult to deal with because of the lasting circumstances that astronauts suffer upon returning back to Earth. As a result of these issues, NASA has delayed its Mars mission to circa 2028. Another…

Safer Helmets Reduce Potential for Traumatic Injury

  • Magazine Article
  • TBMG-36007
Published 2020-02-01 by Tech Briefs Media Group in United States

“Seventy-five percent of all fatal motorcycle accidents globally involve brain injury, with rotational forces acting on the brain being the primary cause of death,” According to NHTSA. By implementing a novel helmet design and materials set, KIRSH Helmets is to working to develop a more effective helmet for motorcycle riders, as well as in other applications. A patented design, in which fluid displacement technology replaces the typically used foam compression, utilizes a silicone liner injected with fluid. The resulting structure reduces rotational and angular forces during acceleration impacts.

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Silicon Valley Summit Identifies Safety Strategies for Self-driving Cars

Autonomous Vehicle Engineering: January 2020

Bradley Berman
  • Magazine Article
  • 20AVEP01_11
Published 2020-01-01 by SAE International in United States

AV industry leaders pinpointed several effective tactics, such as limiting vehicle speeds and empowering safety operators to ground vehicles.

Until recently, leading autonomous vehicle (AV) technologists posited that ultra-safe, go-anywhere robotaxis would soon be on the road. But questions about those timelines-and the safety of testing AVs on public roads-emerged in 2018 after a series of high-profile accidents. Consumers have since been caught in the middle between promises of eliminating highway fatalities and reports about deadly crashes.

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