Autonomous Driving – the Changes to Come
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Future Outlook in Commercial Vehicles
ADAS In Commercial Pulse Q2’20 Vehicles What’s inside ? 1. Activities of 4 key commercial vehicle manufacturers in ADAS and higher autonomy • Tesla, Daimler Trucks, Traton and Volvo Trucks Image: Daimler Freightliner Inspiration Truck Activities of 4 key emerging players in autonomous CVs • Embark, TuSimple, Nikola Motors, Einride 2. Regulations impacting autonomous CVs in the U.S & EU 3. Future outlook THEMES AND Themes covered in this scope Key Takeaways . Players are focusing on Level-4 technologies KEY TAKEAWAYS Activities of 4 key commercial vehicle that take over on the highways, aiming at manufacturers in ADAS & higher autonomy improving safety and gaining greater fuel o Tesla efficiency. e.g. from platooning. IN ADAS in CVs o Daimler Trucks . Collaborative business models and o Traton investments could accelerate L4-L5 capabilities o Volvo Trucks in the near future and find use cases in last-mile delivery, construction and mining areas Today, we are seeing vehicle automation quickly becoming available throughout the Activities of 4 key emerging players in commercial vehicle market with significant autonomous commercial vehicles . Players like Embark plans to skip Level 3 and go interest and investment by the players. o Embark straight to Level 4, while TuSimple has ambitious o TuSimple plans to scale up Level 4 freight network by 2021 o Nikola Motors . Hydrogen powered autonomous trucks could gain ADAS functionalities such as adaptive cruise o Einride traction and fuel the freight chain control (ACC), automatic emergency braking (AEB) and lane keeping assist (LKA) are . Currently, no federal regulation on autonomous accelerating for commercial vehicles. Truck Regulation impacting autonomous commercial vehicles in the U.S and EU trucking technology exists in the U.S. -
Development & Policy Forecast for Global and Chinese NEV Markets
Development & Policy Forecast for Global and Chinese NEV Markets in 2021 Invited by China EV 100, officials and experts from domestic and foreign government agencies, industry associations, research institutions and businesses attended the 7th China EV 100 Forum in January 15-17, 2021. The summary below captures the observations and insight of the speakers at the forum on the industry trend and policy forecast in the world and China in 2021. Ⅰ. 2021 Global & China Auto Market Trend 1. In 2021, the global auto market may resume growth, and the NEV boom is set to continue. 2020 saw a prevalent downturn of the auto sector in major countries due to the onslaught of COVID-19, yet the sales of NEVs witnessed a spike despite the odds, with much greater penetration in various countries. The monthly penetration of electric vehicles in Germany jumped from 7% to 20% in half a year and is expected to hit 12% in 2020, up 220% year on year; Norway reported an 80% market share of EVs in November, which is projected to exceed 70% for the whole year, topping the global ranking. Multiple consultancy firms foresee a comeback of global sales growth and a continuance of NEV boom in 2021 as coronavirus eases. 2. China's auto market as a whole is expected to remain stable in 2021, 1 with a strong boost in NEV sales. In 2020, China spearheaded global NEV market growth with record sales of 1.367 million units. The Development Research Center of the State Council expects overall auto sales to grow slightly in 2021, which ranges 0-2%. -
ADVANCED DRIVER ASSISTANCE SYSTEMS (ADAS) JUNE 2019 a Guide to Advanced Driver Assistance Systems
ADVANCED DRIVER ASSISTANCE SYSTEMS (ADAS) JUNE 2019 A Guide to Advanced Driver Assistance Systems As technology becomes more advanced, a growing number of vehicles are being built with intelligent systems to help motorists. Advanced Driver Assistance Systems, or ADAS, is a term used to describe these smart features. ADAS includes relatively simple features like rear view cameras to help with parking through to more complicated systems like Lane Departure Warning (LDW) that can detect a vehicle’s surroundings. These advanced systems can actually take some control of the vehicle, such as Autonomous Emergency Braking (AEB). In this guide, we describe the ADAS technology available and their benefits, which could be useful when you and your drivers are selecting your next vehicle. What is ADAS? Whether your car has adaptive high beams, a collision detection system or autonomous night vision, these are all classed as Advanced Driver Assistance Systems (ADAS). If you and your drivers understand what these smart features are and what they do, you can get the most benefit from them, improving your driving experience and making other road users safer. Please be aware that the information in this guide is correct as at June 2019 but things move fast in this area. 1 A guide to advanced driver assistance systems Light Assisted Technology AFLS - Adaptive Front Lighting System System that automatically turns the headlight beam to the right or left dependent on the vehicle’s direction. AHBC – Adaptive High Beam Control ALC - Adaptive Light Control Detects oncoming traffic and vehicles in front, automatically adjusting the headlamp beam high and low. -
State of the Art of Adaptive Cruise Control and Stop and Go Systems
1st AUTOCOM Workshop on Preventive and Active Safety Systems for Road Vehicles State of the Art of Adaptive Cruise Control and Stop and Go Systems Emre Kural, Tahsin Hacıbekir, and Bilin Aksun Güvenç Department of Mechanical Engineering, østanbul Technical University, Gümüúsuyu, Taksim, østanbul, TR-34437, Turkey Abstract—This paper presents the state of the art of Number of Traffic Accidents in European Country Adaptive Cruise Control (ACC) and Stop and Go systems as x1000 well as Intelligent Transportation Systems enhanced with inter vehicle communication. The sensors used in these 400 systems and the level of their current technology are introduced. Simulators related to ACC and Stop and Go 300 (S&G) systems are also surveyed and the MEKAR 200 simulator is presented. Finally, future trends of ACC and Stop and Go systems and their advantages are emphasized. 100 0 I. INTRODUCTION y in e ly K y n a c a U e a n It rk a u New trends in automotive technology result in new rm Sp r e F T systems to produce safer and more comfortable vehicles. G Many driver assistant systems are introduced by automotive manufacturers in order to prevent a possible Figure 1. Traffic Accident Statistics in Europe accident from happening either by intervening in the And as a result, the driver’s routine interventions are control of the vehicle temporarily or by warning the lessened and due to a more controlled driving, fuel driver audibly and visually. consumption will be reduced. On the other hand, the The key reason as to why researchers focus on the automation of highways will also allow an increase in the subject of producing safer cars is related to the statistics number of vehicles traveling on roads without causing that expose the serious consequences of accidents. -
A Hierarchical Control System for Autonomous Driving Towards Urban Challenges
applied sciences Article A Hierarchical Control System for Autonomous Driving towards Urban Challenges Nam Dinh Van , Muhammad Sualeh , Dohyeong Kim and Gon-Woo Kim *,† Intelligent Robotics Laboratory, Department of Control and Robot Engineering, Chungbuk National University, Cheongju-si 28644, Korea; [email protected] (N.D.V.); [email protected] (M.S.); [email protected] (D.K.) * Correspondence: [email protected] † Current Address: Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk 28644, Korea. Received: 23 April 2020; Accepted: 18 May 2020; Published: 20 May 2020 Abstract: In recent years, the self-driving car technologies have been developed with many successful stories in both academia and industry. The challenge for autonomous vehicles is the requirement of operating accurately and robustly in the urban environment. This paper focuses on how to efficiently solve the hierarchical control system of a self-driving car into practice. This technique is composed of decision making, local path planning and control. An ego vehicle is navigated by global path planning with the aid of a High Definition map. Firstly, we propose the decision making for motion planning by applying a two-stage Finite State Machine to manipulate mission planning and control states. Furthermore, we implement a real-time hybrid A* algorithm with an occupancy grid map to find an efficient route for obstacle avoidance. Secondly, the local path planning is conducted to generate a safe and comfortable trajectory in unstructured scenarios. Herein, we solve an optimization problem with nonlinear constraints to optimize the sum of jerks for a smooth drive. In addition, controllers are designed by using the pure pursuit algorithm and the scheduled feedforward PI controller for lateral and longitudinal direction, respectively. -
Human Centred Design of First and Last Mile Mobility Vehicles
Coventry University DOCTOR OF PHILOSOPHY Human centred design of first and last mile mobility vehicles Wasser, Joscha Award date: 2020 Awarding institution: Coventry University Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of this thesis for personal non-commercial research or study • This thesis cannot be reproduced or quoted extensively from without first obtaining permission from the copyright holder(s) • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 11. Oct. 2021 Human Centred Design of First and Last Mile Mobility Vehicles by 1,2,4 Joscha Wasser A thesis submitted in partial fulfilment of the University’s requirements for the Degree of Doctor of Philosophy. Supervisors: Andrew Parkes1, Cyriel Diels3, Michael Tovey1 and Anthony Baxendale2 1 The National Transport Design Centre, Swift Road, Coventry CV1 2TT, UK 2 HORIBA MIRA Ltd, Watling Street, Nuneaton, Warwickshire, CV10 0TU, UK 3 Royal College of Art, Kensington Gore, Kensington, London SW7 2EU, UK 4 Fraunhofer FKIE, Fraunhoferstraße 20, 53343 Wachtberg, Germany Content removed on data protection grounds 2 3 4 5 6 Content removed on data protection grounds 7 Content removed on data protection grounds 8 Content removed on data protection grounds 9 10 Acknowledgements I would like to express my sincere gratitude to Dr. -
Paving the Way to Self-Driving Cars with ADAS (Rev. A)
Paving the way to self-driving cars with advanced driver assistance systems Hannes Estl Worldwide Systems Marketing for Advanced Driver Assistance Systems (ADAS), Texas Instruments Recent publicity has attracted the public eye to the development of automated vehicles, especially Google’s experimental cars that have logged thousands of self-driven miles with minimal help from human drivers. These events are truly impressive, and in the long term will help revolutionize vehicle operation and our experience of driving. But the excitement about self-driving cars can make it easy to overlook numerous short-term developments by automotive manufacturers that are equally important in transforming the act of driving. Collectively known as Advanced Driver Assistance Systems (ADAS), these developments are designed to make cars safer, and their gradual introduction is already improving road safety. In addition, ADAS features represent an evolution in vehicle sensing, intelligence and control that will ultimately lead to self-driving cars. ADAS technologies exist at different levels of active Volume production of automobiles with fully assistance and are being introduced in overlapping autonomous control is probably a decade away stages. Driver information systems, such as simple at this time, although as today’s experiments rear-view cameras, surround-view displays, and demonstrate, the essential technology for self- blind spot and lane departure warnings, provide driving cars already exists. However, advanced information but leave the driver in full control at all electronic systems take up much of the space in times. Partially autonomous systems, such as lane- automated test vehicles and are far more expensive keep assistance and active cruise control, enable than the cars themselves. -
AUTONOMOUS VEHICLES the EMERGING LANDSCAPE an Initial Perspective
AUTONOMOUS VEHICLES THE EMERGING LANDSCAPE An Initial Perspective 1 Glossary Abbreviation Definition ACC Adaptive Cruise Control - Adjusts vehicle speed to maintain safe distance from vehicle ahead ADAS Advanced Driver Assistance System - Safety technologies such as lane departure warning AEB Autonomous Emergency Braking – Detects traffic situations and ensures optimal braking AUV Autonomous Underwater Vehicle – Submarine or underwater robot not requiring operator input AV Autonomous Vehicle - vehicle capable of sensing and navigating without human input CAAC Cooperative Adaptive Cruise Control – ACC with information sharing with other vehicles and infrastructure CAV Connected and Autonomous Vehicles – Grouping of both wirelessly connected and autonomous vehicles DARPA US Defense Advanced Research Projects Agency - Responsible for the development of emerging technologies EV Electric Vehicle – Vehicle that used one or more electric motors for propulsion GVA Gross Value Added - The value of goods / services produced in an area or industry of an economy HGV Heavy Goods Vehicle – EU term for any truck with a gross combination mass over 3,500kg (same as US LGV) HMI Human Machine Interface – User interface between a vehicle and the driver / passenger IATA International Air Transport Association - Trade association of the world’s airlines LIDAR Light Detection and Ranging - Laser-based 3D scanning and sensing MaaS Mobility as a Service - Mobility solutions that are consumed as a service rather than purchased as a product ODD Operational Design -
MG Gloster, a Premium SUV Owner Will Be Introduced to Level-1 ADAS and Enable the Intelligent Human-Machine Interface
INDIA’S FIRST AUTONOMOUS LEVEL-1 * PREMIUM SUV WITH *Advanced Driver Assistance System (ADAS) is not a substitute for human eye and driver vigilance, it is a driver assist system that enhances driving experience and safety. The driver shall remain responsible for safe, vigilant and attentive driving. WHAT IS AND HOW DOES IT WORK? Almost all vehicle accidents are caused by human error, which can be reduced to an extend with the Advanced Driver Assistance System also known as ADAS*. ADAS is a group of safety and convenience functions intended to improve comfort for drivers and road safety and, preventing or reducing the severity of potential accidents. ADAS can do all this by alerting the driver, implementing possible safeguards in the vehicle & automating driving controls (based on the driving automation level of the vehicle). While Autonomous Level-5 denotes the global future dream of completely driverless cars, Level-1 acts as a driver assitant and the vehicle is dependent on the driver to monitor the driving environment and conditions. The Level-1 ADAS enhances your driving experience and makes it safer, more comfortable and more convenient. With MG Gloster, a premium SUV owner will be introduced to Level-1 ADAS and enable the intelligent human-machine interface. ADAPTIVE CRUISE CONTROL (ACC) Adaptive Cruise Control, also known as ACC is an advanced version of cruise control, particularly 80km/hr 80km/hr helpful for long drives as it senses the road ahead and enables the vehicle to control its acceleration and braking to achieve desired speed but also maintain safe distance from cars ahead. -
Scenarios for Autonomous Vehicles – Opportunities and Risks for Transport Companies
Position Paper / November 2015 Scenarios for Autonomous Vehicles – Opportunities and Risks for Transport Companies Imprint Verband Deutscher Verkehrsunternehmen e. V. (VDV) Kamekestr. 37–39 · 50672 Cologne · Germany T +49 221 57979-0 · F +49 221 57979-8000 [email protected] · www.vdv.de Contact Martin Röhrleef üstra Hannover, Head of the Mobility Association Department Chairman of the VDV working group “Multimodal Mobility” T +49 511 1668-2330 F +49 511 1668-962330 [email protected] Dr. Volker Deutsch VDV, Head of the Traffic Planning Department T +49 221 57979-130 F +49 221 57979-8130 [email protected] Dr. Till Ackermann VDV, Head of the Business Development Department T +49 221 57979-110 F +49 221 57979-8110 [email protected] Figure sources Title, page 18 VDV Page 5 VDA Page 9 Morgan Stanley Summary: Autonomous vehicles: opportunities and risks for public transport The development and operation of fully automated, driverless vehicles (“autonomous vehicle”) will have a disruptive impact on the transport market and thoroughly mix up the present usage patterns as well as the present ownership and business models. The autonomous vehicle is a game changer, not least because the traditional differences between the various modes of transport become indistinct as an autonomous vehicle can be everything, in principle: a private car, a taxi, a bus, a car-sharing vehicle or a shared taxi. To express it dramatically: the autonomous vehicle could be part of the public transport system – but it could also seriously threaten the existence of today’s public and long-distance transport: The autonomous vehicle can threaten the existence of public transport because it makes driving much more attractive. -
Driver Assistance Technologies Pradip Kumar Sarkar
Chapter Driver Assistance Technologies Pradip Kumar Sarkar Abstract Topic: Driver Assistance Technology is emerging as new driving technology popularly known as ADAS. It is supported with Adaptive Cruise Control, Automatic Emergency Brake, blind spot monitoring, lane change assistance, and forward col- lision warnings etc. It is an important platform to integrate these multiple applica- tions by using data from multifunction sensors, cameras, radars, lidars etc. and send command to plural actuators, engine, brake, steering etc. ADAS technology can detect some objects, do basic classification, alert the driver of hazardous road conditions, and in some cases, slow or stop the vehicle. The architecture of the elec- tronic control units (ECUs) is responsible for executing advanced driver assistance systems (ADAS) in vehicle which is changing as per its response during the process of driving. Automotive system architecture integrates multiple applications into ADAS ECUs that serve multiple sensors for their functions. Hardware architecture of ADAS and autonomous driving, includes automotive Ethernet, TSN, Ethernet switch and gateway, and domain controller while Software architecture of ADAS and autonomous driving, including AUTOSAR Classic and Adaptive, ROS 2.0 and QNX. This chapter explains the functioning of Assistance Driving Technology with the help of its architecture and various types of sensors. Keywords: sensors, ADAS architecture, levels, technologies 1. Introduction In order to enhance road safety as well as to satisfy increasingly stringent government regulations in western countries, automobile makers are confronted with incorporating a range of diverse technologies for driver assistance to their new model. These technologies help drivers to avoid accidents, both at high speeds and for backward movement for parking. -
Industry Ponders Natural Gas Applications
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