Your Selections

Automated Vehicles
Show Only

Collections

File Formats

Content Types

Dates

Sectors

Topics

Authors

Publishers

Affiliations

Committees

Events

Magazine

Series

 

Approach for standardization of Advanced Driving Assistance System (ADAS) in India

International Centre For Automotive Tech.-Aditi Sethi
  • Technical Paper
  • 2019-28-2464
To be published on 2019-11-21 by SAE International in United States
Authors: Aditi Sethi1, Siddhanta Shrivastava2, Madhusudan Joshi3 Organization: 1,2,3 International Centre for Automotive Technology, Manesar Introduction: With the increasing utilization of electronics in Indian automobile industry, there is an essential requirement for standardizing the functional safety of sub-systems that constitute advanced driving assistance system (ADAS) as it would be the foundation stone for the automated vehicles in future. These systems assist the driver and the driving process, further increasing the car safety and road safety, subsequently reducing human error. Due to interaction of several electronic control units (ECUs) in a vehicle and complexity of the system, electronic stability plays a vital role. Therefore, the standards shall be more performance oriented and technology neutral. They shall also cover validation tests associated with safety, mechanical rigidity, durability, environmental protection and electromagnetic compatibility. Standardization of ADAS would authenticate the quality, regulate and smoothen the uniform implementation of these sub-systems. Interestingly the standardization of ADAS is in progress at the international level. It is therefore pertinent to consider adoption, formulation or both of international standards as a part of…
 

An ADAS Feature Rating System: Proposing a New Industry Standard

Velodyne LiDAR-David Heeren, Mircea Gradu
  • Technical Paper
  • 2019-24-0251
To be published on 2019-10-07 by SAE International in United States
The rapid introduction of Advanced Driver-Assistance Systems (ADAS) in modern vehicles has the commendable overarching goal of improving the Safety of the driver, passengers and other traffic participants. As integral part of Automated Vehicles included within the SAE Levels 1-3, ADAS prepare the path toward full autonomy and consequently they are subjected to some of the same challenges. A recent SAE EDGE™ report considers the following four areas to be unsettled domains in automated vehicle sensors, due mainly to the lack of common understanding around various aspects pertaining to each of them: • Terminology and taxonomy • Testing, simulation, and calibration • Security, robustness, and integrity • Data ownership and privacy Velodyne LiDAR, Inc. is the lead company in automotive Lidar sensing technology, but also one of the strongest Safety Advocacy voices within the industry. Accordingly, Velodyne published several thought leading white papers addressing the first three topics listed above. This new SAE paper by Velodyne will build on the previous framework related to developing, testing, validating and marketing Lidar centric Safety oriented ADAS solutions.…
 
new

A Maneuver-Based Threat Assessment Strategy for Collision Avoidance

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Beihang University, China-Weiwen Deng
General Motors LLC, United States-Jinsong Wang
  • Journal Article
  • 07-12-01-0003
Published 2019-08-22 by SAE International in United States
Advanced driver-assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of the driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This article presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modelled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models. Subsequently, time to collision (TTC) is calculated in a strategy of employing collision detection at every predicted trajectory instance. For this purpose, safe areas via bounding boxes are applied on every vehicle, and Separating Axis Theorem (SAT) is applied for collision prediction…
 
new

Developing a Standardized Performance Evaluation of Vehicles with Automated Driving Features

SAE International Journal of Connected and Automated Vehicles

Virginia Polytechnic Institute and State University, USA-Alexis Basantis
Virginia Tech Transportation Institute (VTTI), USA-Zachary Doerzaph, Leslie Harwood, Luke Neurauter
  • Journal Article
  • 12-02-03-0011
Published 2019-08-21 by SAE International in United States
Objectives: The project goal was to create an initial set of standardized tests to explore whether they enable the ongoing evaluation of automated driving features as they evolve over time. These tests focused on situations that were representative of several daily driving scenarios as encountered by lower-level automated features, often called Advanced Driver Assistance Systems (ADAS), while looking forward to higher levels of automation as new systems are deployed. Methods: The research project initially gathered information through a review of existing literature about ADAS and current test procedures. Thereafter, a focus group of industry experts was convened for additional insights and feedback. With this background, the research team developed a series of tests designed to evaluate a variety of automated driving features in currently available implementations and anticipated future variants. Key ADAS available on current production vehicles include adaptive cruise control (ACC), lane keeping assist (LKA), and automatic emergency braking (AEB). Seven of the most automated production vehicles available in 2018 from six manufacturers were subjected to a series of standardized tests that were performed…
 
new

EDITORIAL: AI, ADAS & AVs-oh my!

SAE Truck & Off-Highway Engineering: August 2019

Editor-in-Chief-Ryan Gehm
  • Magazine Article
  • 19TOFHP08_06
Published 2019-08-01 by SAE International in United States

Active safety and advanced driver-assistance systems (ADAS), along with increasingly sophisticated artificial intelligence (AI) platforms-are the building blocks essential to climbing the SAE levels of automation. Acquisitions, partnerships and advanced-technology demonstrations in these areas are occurring at a dizzying rate, as the industry has set its sights on Level 4 (L4) automated vehicles (AVs).

Annotation icon
 

Motion Cueing Algorithm for a 9-DoF Driving Simulator: MPC with Linearized Actuator Constraints

SAE International Journal of Connected and Automated Vehicles

BMW Group, Germany-Markus Schwienbacher, Joost Venrooij
Technical University of Munich, Germany-Felix Ellensohn, Daniel Rixen
  • Journal Article
  • 12-02-03-0010
Published 2019-07-09 by SAE International in United States
In times when automated driving is becoming increasingly relevant, dynamic simulators present an appropriate simulation environment to faithfully reproduce driving scenarios. A realistic replication of driving dynamics is an important criterion to immerse persons in the virtual environments provided by the simulator. Motion Cueing Algorithms (MCAs) compute the simulator’s control input, based on the motions of the simulated vehicle. The technical restrictions of the simulator’s actuators form the main limitation in the execution of these input commands. Typical dynamic simulators consist of a hexapod with six degrees of freedom (DoF) to reproduce the vehicle motion in all dimensions. Since its workspace dimensions are limited, significant improvements in motion capabilities can be achieved by expanding the simulator with redundant DoF by means of additional actuators. This article introduces a global optimization scheme that is able to find an optimal motion for a 9-DoF driving simulator with three redundant DoF. The simulator consists of a tripod with three DoF in longitudinal, lateral and yaw direction as well as a hexapod, which is mounted on top of the…
Datasets icon
Annotation icon
 

What M&E Can Teach the AV Industry About Data

Autonomous Vehicle Engineering: July 2019

Jason Coari, Mark Pastor
  • Magazine Article
  • 19AVEP07_05
Published 2019-07-01 by SAE International in United States

Media & entertainment offers important learnings on data retention, management, scalability and security.

At first glance, autonomous vehicles would seem to have little in common with the Media and Entertainment (M&E) industry, beyond action-movie car chases and in-vehicle entertainment screens.

Annotation icon
 

ZF's Current Work Builds for the EV, AV Future

Autonomous Vehicle Engineering: July 2019

Bill Visnic
  • Magazine Article
  • 19AVEP07_09
Published 2019-07-01 by SAE International in United States

The Tier-1 giant's “vision” for improving future mobility leverages its latest safety and chassis-development innovations.

As the product-development landscape for light-vehicle electrification and automated-driving technologies becomes less cluttered, it's apparent that established automotive Tier 1 mega-suppliers are intent on merging their established competencies with whatever new product lines are required in the electrified, automated future…whenever it comes.

Annotation icon
 

The Navigator

Autonomous Vehicle Engineering: July 2019

Sam Abuelsamid
  • Magazine Article
  • 19AVEP07_02
Published 2019-07-01 by SAE International in United States

As the world turns to C-V2X, Europe picks WiFi

Vehicle-to-everything (V2X) communications is a relatively straightforward and inexpensive technology that has the potential to reduce crashes by improving driver situational awareness. Compared to the automated-driving technology that most of the industry is rushing to develop, V2X is cheap and can even be retrofitted to existing vehicles.

Annotation icon
 

Unsettled Technology Areas in Autonomous Vehicle Test and Validation

Florida Polytechnic Univ.-Rahul Razdan
  • Research Report
  • EPR2019001
Published 2019-06-12 by SAE International in United States
Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more.Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized.This paper explores the ADS validation challenge by reviewing existing approaches and examining the effectiveness of those approaches, presenting critical techniques required to bring safe and effective solutions to market, discussing unsettled topics,…
Datasets icon
Annotation icon