This document describes machine-to-machine (M2M) communication to enable cooperation between two or more participating entities or communication devices possessed or controlled by those entities. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle with driving automation feature(s) engaged. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of manually operated vehicles or pedestrians or cyclists carrying personal devices), or road operators (e.g., those who maintain or operate traffic signals or workzones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be used to influence (directly or indirectly) DDT performance by one or more nearby road users

Cooperative Driving Automation(CDA) Committee

Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles

J3216_202107-TEST-REC (Historical)07/16/2021

Cooperative Driving Automation(CDA) Committee

Stepping Into SAE Level 3

21AVEP05_0905/01/2021

Honda and Toyota release new advanced driver-assistance systems that help to demarcate - or blur - the differences between SAE Level 2 and Level 3 capability. Honda and Toyota each recently announced the release of new, more-sophisticated driver-assistance systems for a special range of vehicles available in Japan starting in March 2021. Honda attracted global attention in November 2020, when it announced the Honda Legend fitted with Honda Sensing Elite would be the first vehicle ever awarded “type designation” from Japan's Ministry of Land, Infrastructure, Transport and Tourism (MLIT) for a driver-assistance system of SAE Level 3 capability. The Legend is joined by Toyota's 2022 Mirai and Lexus LS500h equipped with Advanced Drive, a system that, according to the company, embodies its “Mobility Teammate Concept.” This is an automated driving concept unique to Toyota that “seeks to enhance communication between drivers and cars, enable them to reach out to each other for mutual assist

Visnic, Bill

Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles

J3016_202104 (Current)

04/30/2021

This document describes [motor] vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. It provides a taxonomy with detailed definitions for six levels of driving automation, ranging from no driving automation (Level 0) to full driving automation (Level 5), in the context of [motor] vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways: Level 0: No Driving Automation Level 1: Driver Assistance Level 2: Partial Driving Automation Level 3: Conditional Driving Automation Level 4: High Driving Automation Level 5: Full Driving Automation These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on [motor] vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit

On-Road Automated Driving (ORAD) committee

Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles

J3016_202104-TEST-REC (Historical)04/30/2021

On-Road Automated Driving (ORAD) committee

The Sensing Systems That Make ADAS Work

TBMG-3863603/01/2021

To find out the latest information about sensors for automated driving systems, I interviewed Alberto Marinoni, Director of Product Marketing, TDK/Invensense (San Jose, CA).

Engineering FORD'S FUTURE

21AUTP03_0103/01/2021

Product platform and operations chief Hau Thai-Tang on navigating the microchip shortage, compact-unibody trucks, EV and AV challenges, and driving engineering efficiencies amid the lockdown. Security at Ford's Dearborn Proving Ground was tight on a frigid January day when we arrived for SAE's interview with Hau Thai-Tang. The gate guards were armed with infrared thermometers, and signs everywhere demanded masks be worn. Not even Bill Ford was permitted on site without a temperature check and PPE, we were told. The reasonable and safe ground rules for our wide-ranging conversation with Ford's chief product platform and operations officer included sitting 10 feet apart in an empty hall adjacent to the test track. We elevated our voices to cut through the mask muffling. A striking blue Mustang Mach-E provided a backdrop for talking electrification strategy. It also gave context for sharing his view of the other pandemic: the industry's worsening microchip shortage.

Brooke, Lindsay

Flash! Lidar's Next Generation Arrives

21AVEP03_0603/01/2021

Technology solutions from new players and alliances are poised to drive down cost. Electronics engineers may best know what typically happens in an emerging, rapidly moving technology space. First, innovation: Start-ups bring new solutions amid rounds of funding. Next is the often-protracted shakeout period. OEMs evaluate prototypes based on performance, quality, and cost; the technologies are refined. Product announcements are made. The “best way of doing it” becomes clearer. Then come the Tier 1s, bringing their proficiency in manufacturing and cost engineering. They take the most valid architectures, knock most if not all the cost out of them, and create a cost-effective solution, at scale.

Brooke, Lindsay

Velodyne Preps for Volume Lidar

21AVEP01_0701/01/2021

The $500 Velarray H800 is aimed at ADAS applications and automated production at scale. Prior to 2020, there were allegedly 80 to 100 “lidar companies” in the world, depending on who in Silicon Valley was compiling the list. Such was the over-inflated bubble of autonomous mobility prior to the pandemic. How many of those fledglings retain any viability today is anyone's guess, but one thing is certain: Velodyne is real, and remains the best-known player of the lidar world. So, its announcement last November of the Velarray H800 - first in a new family of solid-state lidars aimed at automotive ADAS and AV applications - continues to resonate among OEMs and Tier-1 integrators. In development since 2017, the H800 is based on Velodyne's MLA (micro-lidar array) technology that uses eight edge-emitting lasers. It also features the company's proprietary photo detectors and its own ASIC microchip - an application-specific integrated circuit designed for a special application.

Brooke, Lindsay

Level 2+: Taking High-Value ADAS Mainstream

21AVEP01_0301/01/2021

Enhanced SAE Level 2 automated driving systems avoid the cost, complexity - and uncertainty - of Level 3. Soon after SAE International released its J3016 “Levels of Automated Driving” standard in January 2014, engineers and product planners working in automated-vehicle development were probing the space between Level 2 and Level 3. New sensing and processor capabilities were poised to alter the lines of demarcation between L2's focus on driver assist and the controversial (and tricky) driver alerts and “handback” required by L3. There was room to expand the ADAS (advanced driver-assistance systems) frontier. Those doing the probing believed SAE Level 2 could be effectively built upon, with greater functionality and safety potential, as new innovations became available. The terms “enhanced L2” and “Level 2-point-something” coined by engineers gave way to a more market-friendly “Level 2+.” And as 2021 begins, Level 2+ is the dominant ADAS trend, engineers and analysts tell Autonomous

Brooke, Lindsay

AV and ADAS Testing from Out of the Box

20AVEP11_1011/01/2020

A new tool from Foretellix guides engineers through virtual systems testing to minimize the risk of getting dangerous predeployment bugs. For self-driving vehicle systems to gain the full confidence of the public, the mobility industry and government regulators, OEMs have to prove that AVs (and those equipped with enhanced SAE Level 2 automated-driving systems) are safer being driven by software than by humans. But a recent string of unfortunate events in 2020 involving automatic emergency braking (AEB) systems is causing concerns. Early in the year, Volvo recalled 750,000 cars from 2019 and 2020 production over a fault in its AEB. Engineers discovered a software glitch that prohibited the system from activating under certain temperatures. Then in June, in Taiwan, a Tesla Model 3 operating in Autopilot mode slammed into an overturned tractor-trailer rig at 70 mph, reportedly due to software issues related to the car's forward-facing sensor array and an AEB that failed to react. This

Brooke, Lindsay

SAE TOMORROW TODAY: Times When You Have to Take the Right Risk

1289206/05/2020

David Estrada, Chief Legal Officer at Nuro, joins host Grayson Brulte to discuss the leading factors of the mobility revolution. David kicks off by sharing the familial inspiration that shaped his well-rounded perspective. The two dive right in to how mobility has changed over the past two years and the role that tech companies' heavy investment in self-driving cars will shape the future. David then shares his perspective on how an elected official's first impression of riding in an AV compared to his own. Grayson and David dig into how the vision of Larry Page at Google pushed investment and development into AV. David then shares insights on driving behaviors and what kinds of trips can be replaced by AVs. The two look at what's next for Nuro's AV delivery services, why Houston as the ideal test market for AV delivery services, the benefits of Nuro's vehicles and the greatest challenges for scaling services. The AV conversation shifts to why SAE Level 2 automated systems will

Hineman, Marcie

Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles

J3216_202005 (Historical)

05/07/2020

Cooperative Driving Automation(CDA) Committee

Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles

J3216_202005-TEST-REC (Historical)05/07/2020

Cooperative Driving Automation(CDA) Committee

Impact of Lateral Alignment on the Energy Savings of a Truck Platoon

2020-01-059404/14/2020

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances. The results showed that energy savings generally increased in a non-linear fashion

Lammert, Michael P., McAuliffe, Brian, Smith, Patrick, Raeesi, Arash, Hoffman, Mark, Bevly, David

Design of a Mild Hybrid Electric Vehicle with CAVs Capability for the MaaS Market

2020-01-143704/14/2020

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer. MATLAB models of the vehicle system

Taoudi, Amine, Haque, Moinul Shahidul, Strzelec, Andrea, Follett, Randolph

GM deploying electricals of the future

20AUTP03_0803/01/2020

In tandem with its corporate strategy to “skip” vehicle hybridization and focus solely on electric vehicles (EVs) for future propulsion (see cover story), General Motors recently offered media a deeper look at the company's all-new vehicle electrical architecture that was first confirmed in mid-2019, saying the vehicle-wide electrical system is associated with more than 100 new patents. The advanced “digital vehicle platform,” known internally as Global B, debuted with the 2020 Cadillac CT5 sedan. It serves as the electrical foundation for the 2020 Chevrolet Corvette Stingray and the 2021 Chevrolet Tahoe and Suburban, GM Yukon and Cadillac Escalade and will carry into all of the company's future conventionally-powered and EV models.

Visnic, Bill

Tier 1s tout newest mobility tech at CES 2020

20AUTP02_0901/01/2020

The mammoth annual techfest formerly known as the Consumer Electronics Show has become a must-attend for the mobility industry, with dozens of displays by OEMs and suppliers of all dimensions. At this year's CES, Automotive Engineering was impressed by new developments in ADAS and AV sensing and processing, V2X connectivity, vehicle cabin sensing and related technologies, electrification advances and a number of vehicle introductions. Highlights of our reporting include:

Brooke, Lindsay

Democratize AV Technology!

20AVEP01_0401/01/2020

Aptiv's new generation of open-sourced architectures based on a few central processors aims to speed AV adoption. CTO Glen DeVos explains. The software-intensive, electrified and increasingly automated vehicle will define the 2020s. Its rise is driving both the industry-wide re-thinking of electrical architectures and the growth of engineering employment behind it. At the forefront of this trend is Aptiv, the technology Tier 1 spun off from Delphi in 2017. It now has more than 19,000 engineers among its 160,000 staff, comprising one of the highest engineer-to-employee ratios among large suppliers. “We've been adding about 1,500 engineers per year, primarily in software and systems engineering, at our 15 major technical centers,” said CTO Glen DeVos. These resources, he noted, will help Aptiv accelerate its customers' development of new vehicle platforms with greater active-safety capability, including automated-driving functionality.

Brooke, Lindsay

HEAT SEEKERS

20AUTP02_0101/01/2020

While engineers debate the use of thermal-imaging sensors for ADAS, their capability and value are being proven for AVs of all levels. What specific sensor types will comprise the advanced driver-assistance systems (ADAS) of the 2020s? That's a controversial subject among engineers who are developing SAE Level 2 and 3 (and the so-called “L2+”) ADAS sensing suites for new vehicles. Many of them believe that visible-light cameras fused with radar will suffice to deliver the object-identification accuracy, redundancy-and cost effectiveness-that OEMs and the driving public expect of ADAS-equipped vehicles. But a case is building for additional sensing capability, particularly for automatic emergency braking (AEB) and pedestrian-detection. Those safety-critical functions currently rely on camera-radar inputs to “see” ahead. They enable the vehicle to react to a range of scenarios-from stalled traffic on a highway to humans and animals suddenly appearing in the road. (In Michigan alone

Brooke, Lindsay

Q&A

19AUTP10_1610/01/2019

Swamy Kotagiri is Magna's chief technology officer and head of the company's Power & Vision segment. Automotive Engineering contributor Sebastian Blanco spoke with him at the 2019 opening of Magna Electronics' new manufacturing facility near Holly, Michigan. There, the company will be consolidating production lines to make and fully test around 12 million automotive-grade cameras a year. Some highlights of our conversation:

SUPPLIER EYE

19AUTP09_0709/01/2019

The value - and risks - of Technology Testbeds The world has been awaiting the arrival of the latest generation Chevrolet Corvette for some time. This past July, among much fanfare the mid-engined C8 (8th generation of this iconic nameplate) Stingray was revealed to the world. As an early owner of the C7, I know my car will be the last front-engined Corvette. And while some fellow enthusiasts are defiantly asserting that “real” Corvettes have their engines ahead of the driver, there is no looking back. Nostalgia aside, this industry is always in need of ‘technology testbeds’, a role that Corvette has played since the C1 debuted in 1953. Such production vehicles stretch the limit in terms of performance, design, efficiency, or all of the above. During the past decade, General Motors has introduced other products which the organization, suppliers and dealers have been using as incubators for related technologies, business processes, and new sourcing models.

WHAT WE'RE DRIVING

19AUTP09_0809/01/2019

As the sporting player in Volvo's C-segment sedan lineup, this all-wheel drive, turbocharged-and-supercharged R-Design S60 faces benchmark competition in the BMW 3-Series, Audi A4 and Mercedes-Benz C-Class. In pure performance, the stylish Swede stacks up nicely against the Germans: Its 316 hp (236 kW) pushes the 3,900 lb (1769 kg) car plus my 200-lb (91 kg) of dead weight from a standstill to 60 mph (97 km/h) in 5.5 s, according to my stopwatch. Dynamically, the S60 T6 (not my choice of nomenclature, as it's a 4-cyl., not a six) feels solid and secure, if not exceptionally nimble, when pushed hard in the corners. But where the S60 R-Design clearly beats the others is inside, the area where Volvo shows its taillamps to the other premium brands. The S60's cabin is a beautifully integrated blend of rich materials and tasteful accents - brushed aluminum of the lower IP contrasting with deep ebony, offset by delightful-to-touch control knobs. The front seats are both handsome and

Dining on Data

19AVEP05_0605/01/2019

Processing, in real-time, the enormous data stream that's flowing through AVs is increasingly the job of NVIDIA's mighty GPUs. Danny Shapiro relishes the feast. Every year, NVIDIA hosts its GPU Technology Conference (GTC), a multi-day news conference/expo to highlight the advances the tech company has made in the past 12 months. In 2018, the big automotive news at GTC was the introduction of DRIVE Constellation, a simulation system designed to “train” the artificial intelligence (AI) algorithms used for autonomous driving. One year and countless line of code updates later, NVIDIA announced at GTC 2019 that the Toyota Research Institute-Advanced Development (TRI-AD) would be the first publicly named customer for DRIVE Constellation. Danny Shapiro, NVIDIA's senior director of automotive, could have used the moment as an excuse to celebrate. Instead, he was all business as he sat down with SAE's Autonomous Vehicle Engineering and contemplated the work still to do.

Blanco, Sebastian

An Immersive Vehicle-in-the-Loop VR Platform for Evaluating Human-to-Autonomous Vehicle Interactions

2019-01-014304/02/2019

The deployment of autonomous vehicles in real-world scenarios requires thorough testing to ensure sufficient safety levels. Driving simulators have proven to be useful testbeds for assisted and autonomous driving functionalities but may fail to capture all the nuances of real-world conditions. In this paper, we present a snapshot of the design and evaluation using a Cooperative Adaptive Cruise Control application of virtual reality platform currently in development at our institution. The platform is designed so to: allow for incorporating live real-world driving data into the simulation, enabling Vehicle-in-the-Loop testing of autonomous driving behaviors and providing us with a useful mean to evaluate the human factor in the autonomous vehicle context.

Rastogi, Vibhor, Merco, Roberto, Kaur, Manveen, Rayamajhi, Anjan, Gavelli, Marco, Papa, Gianluca, Pisu, Pierluigi, Babu, Sabarish, Robb, Andrew, Martin, Jim

The Swedish Word for AV Tech

19AVEP03_0803/01/2019

Veoneer, a new Tier 1 supplier with well-established roots, is moving rapidly into AI, says veteran research boss Ola Boström. The first automotive camera with built-in Deep Learning-considered to be a significant step forward in autonomous-vehicle sensor technology-is due to launch this year. It was developed and will be manufactured by a Tier 1 whose name is still seeking broader recognition in the industry. “What is a…Veoneer?” asked an engineer waiting in the taxi line at this year's CES, when a monorail train wrapped with the company's logo flashed past above. Building brand cred among countless other spin-offs and tech start-ups who are clawing for visibility takes time, of course, even for the independent, publicly-traded Swedish company with 8,600 employees, formerly known as Autoliv's Electronics segment.

Brooke, Lindsay

Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles

J3016_201806 (Historical)

06/15/2018

This SAE Recommended Practice describes motor vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. It provides a taxonomy with detailed definitions for six levels of driving automation, ranging from no driving automation (level 0) to full driving automation (level 5), in the context of motor vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways. These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on motor vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit public access) that collectively serve users of vehicles of all classes and driving automation levels (including no driving automation), as well as motorcyclists, pedal cyclists, and pedestrians

On-Road Automated Driving (ORAD) committee

2021-12-29.TEST A Systematic Scenario Typology for Automated Vehicles Based on China-FOT

2018-01-0039

04/03/2018

To promote the development of automated vehicles (AVs), large scale of field operational tests (FOTs) were carried out around the world. Applications of naturalistic driving data should base on correlative scenarios. However, most of the existing scenario typologies, aiming at advanced driving assistance system (ADAS) and extracting discontinuous fragments from driving process, are not suitable for AVs, which need to complete continuous driving tasks. In this paper, a systematic scenario-typology consisting of four layers (from top to bottom: trip, cluster, segment and process) was first proposed. A trip refers to the whole duration from starting at initial parking space to parking at final one. The basic units ‘Process’, during which the vehicle fulfils only one driving task, are classified into parking process, long-, middle- and short-time-driving-processes. A segment consists of two neighboring long-time-driving processes and a middle or/and short one between them. A cluster refers

Liu, Lin, ZHU, Xichan, Chen, Mingyang, Ma, Zhixiong

2021-12-29.TEST A Systematic Scenario Typology for Automated Vehicles Based on China-FOT

2018-01-0039-TEST-REC04/03/2018

Liu, Lin, ZHU, Xichan, Chen, Mingyang, Ma, Zhixiong

XPONENTIAL 2018 – An AUVSI Experience

TBMG-2877904/01/2018

The Association for Unmanned Vehicle Systems International (AUVSI) is bringing this year's XPONENTIAL 2018 to the Colorado Convention Center in Denver, CO. The event, which runs from April 30 – May 3, will feature more than 200 presentations and panel discussions focused on all aspects of the unmanned vehicle and robotics market. Over 725 exhibitors representing more than 20 different industries will be showcasing their latest technology to an estimated 7,000 attendees from all over the world.

SUPPLIER EYE

17AUTP11_0711/01/2017

Facing the new disruptors Industry leaders remain so by staying ahead of the next ‘big’ trend. They view emerging shifts in business and technology as opportunities, regardless of the disruption such trends portend. Even when faced with unexpected (i.e., a natural disaster) or expected (global regulatory) shifts, suppliers must be agile and decisive. Ignorance of disruption is not an excuse. Recent history is littered with examples of the swift exit of key technologies that were once the lifeblood of many suppliers. Sparkplug wires, incandescent bulbs, mechanical throttle control-the list is long indeed. In many cases, the decline was signaled well in advance and took several vehicle cycles to unfold-allowing those impacted to integrate new capabilities, find partners or divest. Other times, the decline was rapid and resulted in hard decisions with few alternatives.

Robinet, Michael

THE NAVIGATOR

17AUTP11_0811/01/2017

The uncanny valley of partially-automated driving Automated driving has the potential to be the most disruptive force in transportation since Henry Ford rolled out the Model T. The potential impact on an industry that generates an estimated $4 trillion in annual revenues globally is enormous. No company wants to be left without a chair when the music stops. However, in that rush to win the automation race, are automakers producing interim products that might be better left parked in the storage lot behind the research labs?

Abuelsamid, Sam

Toyota rethinks THE FLAGSHIP

17AUTP11_0211/01/2017

The 2018 Lexus LS moves to twin-turbo V6 power and piles on the takumi. Toyota has engineered a complete road-to-roof redo of its flagship Lexus LS sedan, dropping the V8 engine in favor of a twin-turbo V6, adding Aisin's new 10-speed planetary automatic and retaining a hybrid-electric powertrain option-and that's just the beginning. The 2018 model marks the fifth generation of the luxury sedan that rocked the luxury-sedan establishment almost 30 years ago. While the LS has represented less than 2% of the brand's U.S. sales in recent years, its significance to Toyota exceeds its sheer numbers. Chief Engineer Toshio Asahi and his team began work on the new LS500 and hybrid LS500h in late 2011. One key goal was to attract a younger buyer with what Asahi calls “Brave Design,” picking up the Lexus family ‘spindle’ grille theme and developing a longer, more muscular exterior form. Lowering the hood by 1.2 in (30.5 mm), the decklid by 1.6 in (40.6 mm) and dropping the roof 0.6 in (15 mm

Sessions, Ron

THE NAVIGATOR

17AUTP10_0710/01/2017

Time for standard naming of safety features Smart cruise control. Intelligent cruise control. Adaptive cruise control. Radar speed control. As The Bard wrote so long ago, “A rose by any other name would smell as sweet.” Sadly that tale did not end well for the protagonists. In today's world of increasingly sophisticated active safety systems, engineers and consumers alike are being bombarded by more and more brand-specific labels for essentially the same technology. Unfortunately, imprecise branding driven more by marketers than technologists threatens to put us all at risk.

Abuelsamid, Sam

Hardware-in-the-Loop (HIL) Implementation and Validation of SAE Level 2 Autonomous Vehicle with Subsystem Fault Tolerant Fallback Performance for Takeover Scenarios

2017-01-199409/23/2017

The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing Autonomous Vehicles (AV) hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging autonomous lateral control and autonomous longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1]. However, the driver is still required to monitor the driving environment and handle scenarios where control is handed over to the driver due to subsystem faults of

Joshi, Adit

Electronic Horizon: A Map as a Sensor and Predictive Control

2017-01-194508/25/2017

During recent years, all major North American and European commercial vehicle OEMs have introduced predictive functionalities based on an electronic horizon for their on-highway fleets. This is a system concept that lets vehicles know what is happening on the road ahead and allows them to react to that information without driver involvement. When an electronic horizon is used in heavy-duty trucks, a significant reduction in fuel consumption is possible as a key application. This is achieved by optimizing the algorithms in the engine control unit, the transmission control device or other control units in the vehicle. There is a clear business case for the vehicle owners. In this paper we review the long development from early navigation technologies to an in-vehicle sensor, called an electronic horizon. We present an overview of different architectures from several perspectives as well as multiple use cases for commercial vehicles. Furthermore, we look at the future, in which the

Varnhagen, Dr. Raimund

Automation of Road Vehicles Using V2X: An Application to Intersection Automation

2017-01-007803/28/2017

Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs. After a brief outline of our research project and its experimental setup, we will discuss the challenges that arise with IPM

Katriniok, Alexander, Kleibaum, Peter, Ress, Christian, Eckstein, Lutz

Region Proposal Technique for Traffic Light Detection Supplemented by Deep Learning and Virtual Data

2017-01-010403/28/2017

In this work, we outline a process for traffic light detection in the context of autonomous vehicles and driver assistance technology features. For our approach, we leverage the automatic annotations from virtually generated data of road scenes. Using the automatically generated bounding boxes around the illuminated traffic lights themselves, we trained an 8-layer deep neural network, without pre-training, for classification of traffic light signals (green, amber, red). After training on virtual data, we tested the network on real world data collected from a forward facing camera on a vehicle. Our new region proposal technique uses color space conversion and contour extraction to identify candidate regions to feed to the deep neural network classifier. Depending on time of day, we convert our RGB images in order to more accurately extract the appropriate regions of interest and filter them based on color, shape and size. These candidate regions are fed to a deep neural network. In this

Moosaei, Maryam, Zhang, Yi, Micks, Ashley, Smith, Simon, Goh, Madeline J., Nariyambut Murali, Vidya

Human Factors Definitions for Automated Driving and Related Research Topics

J3114_201612 (Current)12/08/2016

The aim of this Information Report is to provide terms and definitions that are important for the user’s interaction with L2 through L4 driving automation system features per SAE J3016, which provides a basis for this document.

Driving Automation Systems Committee

I.D. Concept heralds VW's electric Bolt fighter for 2020

16AUTP11_0911/01/2016

“Our future is in efficient and ‘connected,’” said Volkswagen CEO Herbert Diess as he introduced his company's battery-electric product future at the 2016 Paris Motor Show. The VW I.D. Concept, with a claimed range of up to 373 mi (600 km) on a single charge, heralds a blitz of new electrified vehicles based on the company's new MEB modular platform dedicated to battery-electric models. A production version of the I.D. is planned for 2020, Diess said, with an autonomous version following by 2025. Diess compared the new BEV to the original VW Beetle, promising “it will be a real people's car” priced about the same as today's Golf.

Brooke, Lindsay

Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles

J3016_201609 (Historical)

09/30/2016

This Recommended Practice provides a taxonomy for motor vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis and that range in level from no driving automation (level 0) to full driving automation (level 5). It provides detailed definitions for these six levels of driving automation in the context of motor vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways. These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on motor vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit public access) that collectively serve users of vehicles of all classes and driving automation levels (including no driving automation), as well as motorcyclists, pedal cyclists

On-Road Automated Driving (ORAD) committee