This document specifies the minimum recommendations for Blind Spot Monitoring System (BSMS) operational characteristics and elements of the user interface. A visual BSMS indicator is recommended. BSMS detects and conveys to the driver via a visual indicator the presence of a target (e.g., a vehicle), adjacent to the subject vehicle in the “traditional” Adjacent Blind Spot Zone (ABSZ). The BSMS is not intended to replace the need for interior and exterior rear-view mirrors or to reduce mirror size. BSMS is only intended as a supplement to these mirrors and will not take any automatic vehicle control action to prevent possible collisions. While the BSMS will assist drivers in detecting the presence of vehicles in their ABSZ, the absence of a visual indicator will not guarantee that the driver can safely make a lane change maneuver (e.g., vehicles may be approaching rapidly outside the ABSZ area). This document applies to original equipment and aftermarket BSMS systems for passenger

Advanced Driver Assistance Systems (ADAS) Committee

A Comparative Study on Various Methodologies and Solutions for Evaluation of Short-Range Radar to Validate the Features of Autonomous Vehicle.

2021-26-046809/22/2021

Autonomous vehicle is a vehicle capable of sensing its environment and taking decisions automatically with no human interventions. To achieve this goal, ADAS (Advance Driving Assistance System) technologies play an important role and even today technologies are improving and emerging. The sensing of environment can be achieved with the help of sensors like Radar and Camera. Radar sensors are used in detecting the range, speed and directions of multiple targets using complex signal processing algorithms. Radar with long range and short range are widely used in the autonomous vehicles. Radar sensors with long range can be used to realize features like Adaptive Cruise Control, Advance Emergency Brake Assist. The short-range radar sensors are used for Blind Spot Monitoring, Lane Change Assist, Rear Pre-Crash System, Rear Cross Traffic Alert, Occupant safe exist, Trailer Merge Assist and Front Cross Traffic Alert. To realize the Autonomous Vehicle functionalities four short range radar

Sujeendra, M R, Kesana, Sindhu Prabha, Saddaladinne, Jagadeesh Babu

Drivers’ Responses to Lead Vehicles: Thresholds for Triggering an Emergency Response, Age Differences, Crash Risks, and Influence of Secondary Task Engagement

2021-01-089804/06/2021

Analyses of driver response time studies and fatal crash statistics were examined to determine: 1. whether all rear-end crash types can be analyzed as one crash type, 2. average braking thresholds for drivers, and 3. the influence cell phone usage has on drivers’ response times when responding to a lead vehicle. The goal of this research is to recommend protocols for investigating LV crashes that is supported by the literature. Two distinct lead vehicle [LV] response time events emerged: LV platoon (two vehicles traveling together in close proximity) and LV looming (a vehicle approaching a stopped or much slower LV). In normal driving, platoon LV events were very common but resulted in very few crashes per exposure. Young drivers were over-represented when they did occur. Onset of the hazardous event was when the LV decelerated, and drivers began braking roughly 3 to 5 seconds before impact. These results were consistent with the braking thresholds by naturalistic drivers in congested

Muttart, Jeffrey, Dinakar, Swaroop, Edewaard, Darlene

Coalesce of Artificial Intelligence into ADAS Hardware-In-the-Loop Testing

2021-01-019304/06/2021

Automotive industry is inclined towards connected, comfortable, environment friendly, efficient and smarter systems. Advanced Driver Assist System (ADAS) technology assist drivers to achieve a safer as well as better ride by automation and improvisation of the vehicular systems. With the advent of ADAS system, there is a significant focus not only in the development of Electronic Control Units (ECUs) and its features to cater to the emerging market but also on the information that could be displayed to meet the functional as well as safety requirements. This ADAS information display ensures timely notification to the driver with unique alerts that can be acoustic or visual. These systems should be tested thoroughly to ensure reliability as failures may impose severe risk on the OEM. Hardware in the loop testing has been largely adopted by industry against manual testing in lieu of the testing constraints imposed by the latter. This paper discusses on the existing test methods for ADAS

Krishnamoorthy, Bharathi, Nammalwar, Giri, Wulf, Torsten, Pazhur, Nandini

Performance of the Ford Pre-Collision Assist with Automatic Emergency Braking System in Instrumented Tests

2021-01-089404/06/2021

Modern Ford vehicles can be manufactured with a system known as Pre-Collision Assist with Automatic Emergency Braking (AEB). The Pre-Collision Assist feature uses camera technology to detect a potential collision with a vehicle or pedestrian directly ahead. If a potential collision is detected, an alert sound is emitted, and a warning message displays in the vehicle’s message center. If the driver response is not sufficient, AEB will be pre-charged and brake-assist sensitivity will be increased to provide full responsiveness if the driver does brake. If there is no perceived corrective action and a collision is imminent, the vehicle’s brakes can apply automatically. By detecting the possible collision and actuating the braking system, it is possible to prevent some collisions and lessen the severity of others. Testing of this system was conducted using a 2020 Ford Explorer. During several tests, the instrumented Ford was driven at a simulated target vehicle or pedestrian dummy. Data

Vandiver, Wesley, Anderson, Robert

CES 2021: GM creates BrightDrop electrified delivery and logistics company

21AUTP02_0902/01/2021

During her CES 2021 keynote in January, GM Chairman and CEO Mary Barra announced the creation of a new logistics company called BrightDrop. The new business will create an ecosystem of electrified products, software and services for first-to-last-mile delivery. This includes EPI, a new electric pallet to shuttle packages, as well as a new commercial delivery truck based on GM's Ultium battery platform, the EV600. The first customer of the new business will be FedEx Express. According to GM, BrightDrop's electrified solutions were created to help businesses reduce costs, maximize productivity, improve employee and freight security and support sustainability efforts. The EP1 pallet will be available in early 2021 and the EV600 light commercial vehicle (LCV) is expected to be on the road by late 2021. The EV600 is GM's first commercial application of its Ultium battery platform and the truck will feature both Level-2 and DC fast-charging capabilities.

Seredynski, Paul

Western Star develops all-new 49X with quieter cab, lighter but stronger chassis

20TOFHP12_0912/01/2020

Purpose-built from the ground up, the next-generation Western Star 49X vocational truck is underpinned by a stronger, lighter chassis and equipped with a new X-series steel-reinforced aluminum cab that's claimed to be the segment's largest with 10 to 13% more space while being 8% lighter. Technology upgrades that bolster productivity, safety and uptime for the vocational market include Detroit Assurance active safety systems such as Side Guard Assist and the Detroit DT12 Vocational series of automated manual transmissions, which debuts on the Class 8 vocational truck. “We've completely rethought the foundation of the 49X to make it easier to upfit,” David Carson, senior vice president, vocational segment, Daimler Trucks North America, stressed during a virtual press event introducing the new truck. Engineers focused on clear back-of-cab packaging and features that contribute to easier upfitting: forward-mounted DEF tanks; standard in-cab battery box; multiple air tank mounting

Gehm, Ryan

Candidate Improvements to Dedicated Short Range Communications (DSRC) Message Set Dictionary [SAE J2735] Using Systems Engineering Methods

J3067_202010 (Current)

10/06/2020

This document is not a standard, it is a candidate for a standard being submitted to SAE for their consideration as a comment to SAE J2735. The term SAE J2735 SE candidate is used within this document to refer to this submission. This document specifies dialogs, messages, and the data frames and data elements that make up the messages specifically for use by applications intended to utilize the 5.9 GHz Dedicated Short Range Communications for Wireless Access in Vehicular Environments (DSRC/WAVE, referenced in this document simply as “DSRC"), communications systems. Although the scope of this Standard is focused on DSRC, these dialogs, messages, data frames and data elements have been designed, to the extent possible, to be of use for applications that may be deployed in conjunction with other wireless communications technologies. This standard therefore specifies the definitive message structure and provides sufficient background information to allow readers to properly interpret the

V2X Communications Steering Committee

Unsettled Issues Facing Automated Vehicles and Insurance

EPR202001508/05/2020

This SAE EDGE™ Research Report explores how the deployment of automated vehicles (AVs) will affect the insurance industry and the principles of liability that underly the structure of insurance in the US. As we trade human drivers for suites of sensors and computers, who (or what) is responsible when there is a crash? The owner of the vehicle? The automaker that built it? The programmer that wrote the code?Insurers have over 100 years of experience and data covering human drivers, but with only a few years’ worth of information on AVs – how can they properly predict the true risks associated with their deployment? Without an understanding of the nature and risks of AVs, how can the government agencies that regulate the insurance industry provide proper oversight? Do the challenges AVs present require a total reworking of our insurance and liability systems, or can our current structures be adapted to fit them with minor modifications?{"bold":"Unsettled Legal Issues Facing Automated

Williams, Ian

Heavy Vehicle Event Data Recorder (HVEDR) - Data and Triggers

J2728-1_202006 (Current)

06/09/2020

This document provides a list of data elements and event triggers for recording of event data relevant to crash investigations for heavy vehicles. The list of data elements includes recommended source(s) and formatting.

Truck and Bus Event Data Recorder Committee

Heavy Vehicle Event Data Recorder (HVEDR) - Data and Triggers

J2728-1_202006-TEST-REC (Historical)06/09/2020

Truck and Bus Event Data Recorder Committee

On-Board System Requirements for V2V Safety Communications

J2945/1_202004 (Current)04/30/2020

This standard specifies the system requirements for an on-board vehicle-to-vehicle (V2V) safety communications system for light vehicles1, including standards profiles, functional requirements, and performance requirements. The system is capable of transmitting and receiving the SAE J2735-defined basic safety message (BSM) [1] over a dedicated short range communications (DSRC) wireless communications link as defined in the Institute of Electrical and Electronics Engineers (IEEE) 1609 suite and IEEE 802.11 standards [2] to [6].

V2X Core Technical Committee

Collision Probability Field for Motion Prediction of Surrounding Vehicles Using Sensing Uncertainty

2020-01-069704/14/2020

Intelligent driving assistant systems have been studied meticulously for autonomous driving. When the systems have the responsibility for driving itself, such as in an autonomous driving system, it should be aware of its’ surroundings including moving vehicles and must be able to evaluate collision risk for the ego vehicle's planned motion. However, when recognizing surrounding vehicles using a sensor, the measured information has uncertainty because of many reasons, such as noise and resolution. Many previous studies evaluated the collision risk based on the probabilistic theorem which the noise is modeled as a probability density function. However, the previous probabilistic solutions could not assess the collision risk and predict the motion of surrounding vehicles at the same time even though the motion is possible to be changed by the estimated collision risk. Thus, this paper proposes the collision probability field to simultaneously predict the motions of surrounding vehicles

Lee, Minchul, Sunwoo, Myoungho, Jo, Kichun

Dynamic Object Map Based Architecture for Robust CVS Systems

2020-01-008404/14/2020

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications. The architecture is validated with simulations and in a real environment using

Valiente, Rodolfo, Raftari, Arash, Zaman, Mahdi, Pourmohammadi Fallah, Yaser, Mahmud, Syed

Vision System for Detecting a Small Object with Arbitrary Shape at Far Range

2020-01-009404/14/2020

For one of the advanced sensing technologies for the autonomous driving, we have been working on the new vision system. It focuses on detecting the small object at far ranges. It enables to detour a vehicle by avoiding small object. This system is based on the high-resolution mono-camera with narrow FOV and the algorithms for object-detection and lane-detection. Since we have already proposed the system for the traffic cones, we proceed to a new algorithm for an unknown object with arbitrary shape. It can detect the object and estimate its range by using the information on the lane even though the shape and dimension of the object are unknown. Here the system architecture and how the algorithm to detect the object and estimate its range are described. The algorithm is at first validated by a computer-generated image. And then it is applied to real images. For the cones, the accuracy was +/- 4 [m] for the ranges between 50 and 150 [m]. For unknown objects (a tire and a cardboard), the

Miyahara, Shunji, Li, Huan, Xie, Kunpeng, Bai, Jincheng

Reference Test System for Machine Vision Used for ADAS Functions

2020-01-009604/14/2020

Advanced Driver Assistance Systems (ADAS) like Lane Departure Warning (LDW) and Lane Keep Assist (LKA) have been available for several years now but has experienced low customer acceptance and market penetration. 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 markings in the real-world with poor markings, changing weather conditions and occlusions. Currently, there is no available standard or benchmark to evaluate the quality of either the lane markings or the perception algorithms. This work seeks to establish a reference test system that could be used by transportation agencies to evaluate the quality of their markings to support ADAS functions that rely on pavement markings. The test system can also be used by designers as a benchmark for their proprietary systems. To support this development, an extensive video dataset was collected at different times of

Nayak, Abhishek, Rathinam, Sivakumar, Pike, Adam, Gopalswamy, Swaminathan

Perceptions of Two Unique Lane Centering Systems: An FOT Interview Analysis

2020-01-010804/14/2020

The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance. Perceptions of adaptive cruise control (ACC) were similar across vehicles

Landry, Steven, Seppelt, Bobbie, Russo, Luca, Mehler, Bruce, Angell, Linda, Gershon, Pnina, Reimer, Bryan

Simulation of Curved Road Collision Prevention Warning System of Automobile Based on V2X

2020-01-070704/14/2020

Li, Xuanhe, Wu, Jian, He, Rui, Zhu, Bing, Zhao, Jian, Zhou, Hang

A Forward Collision Warning System Using Deep Reinforcement Learning

2020-01-013804/14/2020

Forward collision warning is one of the most challenging concerns in the safety of autonomous vehicles. A cooperation between many sensors such as LIDAR, Radar and camera helps to enhance the safety. Apart from the importance of having a reliable object detector, the safety system should have requisite capabilities to make reasonable decisions in the moment. In this work, we concentrate on detecting front vehicles of autonomous cars using a monocular camera, beyond only a detection method. In fact, we devise a solution based on a cooperation between a deep object detector and a reinforcement learning method to provide forward collision warning signals. The proposed method models the relation between acceleration, distance and collision point using the area of the bounding box related to the front vehicle. An agent of learning automata as a reinforcement learning method interacts with the environment to learn how to behave in eclectic hazardous situations. The agent follows a

Fekri, Pedram, Abedi, Vajiheh, Dargahi, Javad, Zadeh, Mehrdad

An Improved Probabilistic Threat Assessment Method for Intelligent Vehicles in Critical Rear-End Situations

2020-01-069804/14/2020

Threat assessment (TA) method is vital in the decision-making process of intelligent vehicles (IVs), especially for ADAS systems. In the research of TA, the probabilistic threat assessment (PTA) method is acting an increasing role, which can reduce the uncertainties of driver’s maneuvers. However, the driver behavior model (DBM) used in present PTA methods was mainly constructed by limited data or simple functions, which is not entirely reasonable and may affect the performance of the TA process. This work aims to utilize crash data extracted from Event Data Recorder (EDR) to establish more accurate DBM and improve the current PTA method in rear-end situations. EDR data with responsive maneuvers were firstly collected, which were then employed to construct the initial DBM (I-DBM) model by using the multivariate Gaussian distribution (MGD) framework. Besides, the model was further subdivided into six parts by two important risk indicators, Time-to-collision (TTC) and velocity. To

Zhou, Huajian, Zhong, Zhihua, Wang, Xiaowei, Huang, Jin

Advanced Driver-Assistance Systems for City Bus Applications

2020-01-120804/14/2020

The bus sector is currently lagging behind when it comes to implementing autonomous systems for improved vehicle safety. However, in cities such as London, public transport strategies are changing, with requirements being made for advanced driver-assistance systems (ADAS) on buses. This study discusses the adoption of ADAS systems within the bus sector. A review of the on-road ADAS bus trials shows that passive forward collision warning (FCW) and intelligent speed assistance (ISA) systems have been successful in reducing the number of imminent pedestrian/vehicle collision events and improving speed limit compliance, respectively. Bus accident statistics for Great Britain have shown that pedestrians account for 82% of all fatalities, with three quarters occurring with frontal bus impacts. These statistics suggest that the bus forward collision warning system is a priority for inclusion in future vehicles to enhance the driver’s direct vision, and to increase reaction time for earlier

Blades, Luke, Douglas, Roy, Early, Juliana, Lo, Chun Yi, Best, Robert

Empirical Study of the Braking Performance of Pedestrian Autonomous Emergency Braking (P-AEB)

2020-01-087804/14/2020

Vehicle manufacturers are beginning to improve existing autonomous emergency braking (AEB) algorithms by adding pedestrian identification and avoidance capability. The Insurance Institute for Highway Safety (IIHS) has performed tests on eleven such vehicles; data are publicly available and were analyzed for this study. The first objective of this study was to compare Forward Collision Warning (FCW) engagement distance to target, pedestrian automatic emergency braking (P-AEB) brake application time, and incidences of impact across different manufacturers. It was observed that there exists a wide variation in FCW and AEB performance across manufacturers. FCW engagement distance tended to increase with test speed. Time from FCW engagement to AEB engagement was usually less than one second, with some manufacturer-specific variation. Incidences of impact tended to increase with travel speed, although some vehicles tested maintained constant number of incidences of impacts at all speeds

Siddiqui, Omair, Famiglietti, Nicholas, Nguyen, Benjamin, Hoang, Ryan, Landerville, Jon

Heavy Vehicles Kinematics of Automatic Emergency Braking Test Track Scenarios

2020-01-099504/14/2020

This paper presents the test track scenario design and analysis used to estimate the performances of heavy vehicles equipped with forward collision warning and automatic emergency braking systems in rear-end crash scenarios. The first part of this design and analysis study was to develop parameters for brake inputs in test track scenarios simulating a driver that has insufficiently applied the brakes to avoid a rear-end collision. In the second part of this study, the deceleration limits imposed by heavy vehicles mechanics and brake systems are used to estimate automatic emergency braking performance benefits with respect to minimum stopping distance requirements set by Federal Motor Vehicle Safety Standards. The results of this study were used to complete the test track procedures and show that all heavy vehicles meeting regulatory stopping distance requirements have the braking capacity to demonstrate rear-end crash avoidance improvements in the developed tests.

Salaani, M. Kamel, Elsasser, Devin, Boday, Christopher

Testing methods and recommended validation strategies for Active Safety to optimize efficiency

2020-01-134804/14/2020

Given the current proliferation of active safety features on new vehicles, especially for Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving (HAD) technologies, it is evident that there is a need for testing methods beyond a vehicle level physical test. This paper will discuss the current state of the art in the industry for simulation-based verification and validation (V&V) testing methods. These will include, but are not limited to, "Hardware-in-the-Loop", "Software-in-the-Loop", "Model-in-the-Loop", "Driver-in-the-Loop", and any other suitable combinations of the aforementioned. Aspects of the test processes and needed components for simulation will be addressed, detailing the scope of work needed for various types of testing. The paper will provide an overview of standardized test aspects, active safety software validation methods, best practices and standards. The focus will be on trade-offs of cost and performance, as well as providing general guidance for the

Allen, Jace, Koo, Winston, Murugesan, Dhyaneshwar, Zagorski, Chad

Optimization of Braking Strategy for Automatic Emergency Braking System in Vehicle-Pedestrian Accidents

07-12-02-000903/23/2020

Braking strategy is the core of the automatic emergency braking (AEB) system. How to make the braking strategy of the AEB system more suitable for real traffic conditions and more acceptable to drivers is a very important research. This article carries out the braking strategy optimization for the AEB system. From the vehicle-pedestrian accidents collected by the National Automobile Accident In-depth Investigation System (NAIS) of Songjiang Station, this article selects typical cases equipped with event data recorder (EDR) and then analyzes the EDR data. On this basis, the strategy for the optimization of the AEB system is formed. The optimized strategy is simulated in the test scenario specified in the European New Car Assessment Programme (Euro-NCAP) and compared with the real vehicle test results. The result illustrates that the optimized braking strategy is more effective to avoid or mitigate collisions.

Qian, Yubin, Yang, Xueyan, Xiao, Lingyun, Zhu, Yican

Takeover Level of Autonomous Vehicle Based on Driver’s Neuromuscular Characteristic

2020-01-5017

02/24/2020

Taking over vehicle control from a Level 3 conditionally automated vehicle can be a demanding task for a driver, to which great research effort has been contributed in recent years. Nevertheless, more attention should be given to the following aspects. The present research of take-over either only considers the influence of drivers’ visual and second task in single scenarios. However, the drivers’ NMS (Neuromuscular) characteristic hasn’t been investigated yet, especially in complex traffic scenarios. In this paper, a take-over experiment with complex traffic scenarios are conducted to observe the state of vehicle state and arm’ EMG (Electromyography) signal. After that, the driving styles are recognized based on the experimental data. Finally, a take-over level with driving style is proposed by clustering based on the condition of human-vehicle-road.

Hanbing, Wei, Yanhong, Wu, Yuxuan, Zhang, Rui, Xu