Current challenges in autonomous driving

2021

Vehicle System Dynamics, 2015

In recent years, road vehicle automation has become an important and popular topic for research and development in both academic and industrial spheres. New developments received extensive coverage in the popular press, and it may be said that the topic has captured the public imagination. Indeed, the topic has generated interest across a wide range of academic, industry and governmental communities, well beyond vehicle engineering; these include computer science, transportation, urban planning, legal, social science and psychology. While this follows a similar surge of interest-and subsequent hiatus-of Automated Highway Systems in the 1990's, the current level of interest is substantially greater, and current expectations are high. It is common to frame the new technologies under the banner of "self-driving cars"-robotic systems potentially taking over the entire role of the human driver, a capability that does not fully exist at present. However, this single vision leads one to ignore the existing range of automated systems that are both feasible and useful. Recent developments are underpinned by substantial and long-term trends in "computerisation" of the automobile, with developments in sensors, actuators and control technologies to spur the new developments in both industry and academia. In this paper we review the evolution of the intelligent vehicle and the supporting technologies with a focus on the progress and key challenges for vehicle system dynamics. A number of relevant themes around driving automation are explored in this article, with special focus on those most relevant to the underlying vehicle system dynamics. One conclusion is that increased precision is needed in sensing and controlling vehicle motions, a trend that can mimic that of the aerospace industry, and similarly benefit from increased use of redundant by-wire actuators.

Autonomous vehicles are also commonly known as selfdriving vehicles, which do not require human involvement in order to operate or control themselves. In recent years, advancement in automotive thinking have improved but still require human input, depending on the degree of automation[1]. Experts expect vehicles to be able to drive themselves within 3-7 years. This paper describes the current state, the latest trends and the study of self-driving cars in the automotive industry[2]. A detailed analysis of the technology used by automotive vehicles to feel their position and the degree of automation in such vehicles is also included. As the widespread acceptance of self-driving vehicles is considered inevitable, so the need for specific technical and legal guidelines will be essential for a safe and conflict-free journey. Potential concerns about autonomous vehicles should be discarded with safe policies and technologies as discussed in the paper[3].

IOP Conference Series: Materials Science and Engineering, 2017

Mobility is a basic necessity of contemporary society and it is a key factor in global economic development. The basic requirements for the transport of people and goods are: safety and duration of travel, but also a number of additional criteria are very important: energy saving, pollution, passenger comfort. Due to advances in hardware and software, automation has penetrated massively in transport systems both on infrastructure and on vehicles, but man is still the key element in vehicle driving. However, the classic concept of 'human-in-the-loop' in terms of 'hands on' in driving the cars is competing aside from the self-driving startups working towards so-called 'Level 4 autonomy', which is defined as "a self-driving system that does not requires human intervention in most scenarios". In this paper, a conceptual synthesis of the autonomous vehicle issue is made in connection with the artificial intelligence paradigm. It presents a classification of the tasks that take place during the driving of the vehicle and its modeling from the perspective of traditional control engineering and artificial intelligence. The issue of autonomous vehicle management is addressed on three levels: navigation, movement in traffic, respectively effective maneuver and vehicle dynamics control. Each level is then described in terms of specific tasks, such as: route selection, planning and reconfiguration, recognition of traffic signs and reaction to signaling and traffic events, as well as control of effective speed, distance and direction. The approach will lead to a better understanding of the way technology is moving when talking about autonomous cars, smart/intelligent cars or intelligent transport systems.

IEEE Transactions on Intelligent Transportation Systems, 2013

Vehicle automation is proposed as one of the solutions to make transport safer, more comfortable and more environmentally friendly. It is gradually being introduced through Advanced Driver Assistance Systems (ADAS). ADAS started as Anti-lock Braking Systems (ABS) and have now extended to Adaptive Cruise Control (ACC) and Lane Keeping Assist Systems (LKAS). This work aims to contribute to this evolution, by discussing how driving systems can share the road with human drivers. It presents the legal safety concept for the design of a highly automated driving system for highways. The legal safety concept proposes to base driving system design on traffic rules. This allows fully automated driving in traffic with human drivers, without necessarily changing equipment on other vehicles or infrastructure. The driving system uses traffic rules to predict legal or nonlegal trajectories of objects in its perception zone and worst-case objects outside its perception zone. If all objects respect traffic rules, accidents will be avoided. If not, driving defensively will avoid most accidents. Today, international law allows highly automated driving, but not yet fully automated driving. The driving system interacts with the human driver, via human rules. The HAVEit project (European Seventh Framework Programme) and ABV project (French National Research Agency) propose human rules based on the horse-rider metaphor (Hmetaphor). If needed, the driving system takes over control in order to avoid accidents. If the human driver cannot continue driving, the driving system brings the vehicle to a safe standstill on the emergency lane. The consequences of these human rules on driving system design are explored. System rules form the third set of rules of the legal safety concept. With system rules, system components respect the limitations of other system components. The requirements on perception, control and Human-Machine Interface (HMI) components of the legal safety system are discussed. The decision component, which is the central component of the legal safety system, is completely worked out from requirements to design. The legal safety system has been implemented on PC and automotive Electronic Control Units (ECUs). The integration and validation of legal safety components on LIVIC, HAVEit and ABV demonstrators are presented. The work concludes that, for highway environments, legal safety decision, control and HMI can be achieved with state-of-the-art technology, and legal safety perception could be available in medium term.

IEEE open journal of vehicular technology, 2022

The emergence of autonomous driving represents a pivotal milestone in the evolution of the transportation system, integrating seamlessly into the daily lives of individuals due to its array of advantages over conventional vehicles. However, selfdriving cars pose numerous challenges contributing to accidents and injuries annually. This paper aims to comprehensively examine the limitations inherent in autonomous driving and their consequential impact on accidents and collisions. Using data from the DMV, NMVCCS, and NHTSA, the paper reveals the key factors behind self-driving car accidents. It delves into prevalent limitations faced by self-driving cars, encompassing issues like adverse weather conditions, susceptibility to hacking, data security concerns, technological efficacy, testing and validation intricacies, information handling, and connectivity glitches. By meticulously analyzing reported accidents involving self-driving cars during the period spanning 2019 to 2022, the research evaluates statistical data pertaining to fatalities and injuries across diverse accident classifications. Additionally, the paper delves into the ethical and regulatory dimensions associated with autonomous driving, accentuating the legal complexities that arise from accidents involving self-driving vehicles. This review assists researchers and professionals by identifying current autonomous driving limitations and offering insights for safer adoption. Addressing these limitations through research can transform transportation systems for the better.

Springer Vieweg, 2022

As the first of its kind, this Springer-publication analyzes all reported car accidents state wide (1.28 million) over a 10-year period. It synthesizes a supportive developer checklist, considering Artificial Intelligence and visual limits of image recognition. The study based on technical, ethical and legal requirements as well as examples concerning Autonomous Vehicles. Integrating of highly sensitive international court rulings and growing consumer expectations make this book a helpful guide for product development from initial concept until market introduction. Prof. Dr.-Ing. MBA Thomas Winkle bases his work on 30 years research and hands-on experience from Volkswagen Accident Research, Audi Legal Service, Audi Development, Daimler Research, as well as the Daimler-Benz Foundation. Overview: Growing consumer expectations and innovations of Artificial Intelligence lead to high requirements of automated or autonomous vehicles. Manufacturers must develop as safely as possible according to the state of the art in science and technology, weighing up risks, technical suitability and ethical economic feasibility. Otherwise they can be held responsible for damage caused by the technical system. In this research, the author develops innovative ways to meet this high safety standard. Initially, Chapter 2 uses a meta-analysis of previous accident data, which have so far only been researched selectively, to document the possibilities and limitations of assessing the safety potential of vehicle systems. The analysis takes into account different levels of automation - both a posteriori and a priori. Following these findings, Chapter 3 documents the first in-depth analysis of 1.28 million accidents covering the entire area of one German state, including 374 crashes with restricted visibility due to weather and light conditions. The comparison between machine and human perception related to accident causes shows the need to include such scenarios in the development and validation for safe automated vehicles. Chapter 4 describes the growing consumer expectations and the positive develop-ment of vehicle safety in recent decades. From the initial idea to development and sign-off, the paper presents examples of common standards including tools and method descriptions. Furthermore, there follows a development guide with 101 questions on the requirements that contribute to the duty of care in the development of automated vehicles and fulfill the highest court rulings on product liability. Finally, in Chapter 5, qualitative interviews with engineers, executives and a psy¬cho-logist from the development departments of automobile manufacturers show how a structured guideline-based process with expert feedback loops increases product quality in terms of safety in use and functional safety. This work demonstrates that area-wide accident data, structured guidelines and continuous exchange of experts make an essential contribution to safe development in the dilemma between innovation and consumer protection.

International journal of engineering research and technology, 2020

Road safety is a concern of everyone in the current scenario of increased vehicular traffic. Internet is part of our daily life and available in most of the places because of revolution of electronic communication. It has become an integral part of our lives. We are living in a world of automation. Almost everything around, us is automated. Automation plays an important role in the field of transportation. As of now, vehicles are just monitored but not automatically controlled pertaining to the road safety rules. In this work a system is designed for automatic control of vehicles in restricted areas, where the safety signage boards are installed. The four applications namely speed control, hump detection, no parking and no horn zone are implemented using IoT.

2018

This chapter introduces the main technology bricks and some related socioeconomic aspects of automated driving. Vehicles automation technology is advancing at a vertiginous pace. However, the complexity behind some highly uncertain and dynamic driving scenarios imposes the need to distinguish between the different automation levels. This chapter starts from these considerations to elaborate thereafter on the maturity of the currently used technologies—situation awareness, risk assessment, decision-making, human–machine interaction, planning, control—and their near future possibilities. The introduction of connectivity among vehicles and with the digital world brings a number of new opportunities, when combined with automation, that are introduced with the focus on cooperative automated driving. After presenting this technological panorama, different relevant projects are described with the aim to understand the differences between the existing prototypes and the upcoming products an...

2015 IEEE International Symposium on Technology and Society (ISTAS), 2015

Drawing perspectives from science and technology studies, philosophy of science, and literature from ethics and social justice, this paper examines the promises and challenges in the development of self-driving vehicle (SDV) technology. We start with the premise that the combination of different computing technologies embedded in SDVs is a powerful tool for efficiency in communications, information gathering, processing, and storage. However, by focusing on efficiency, SDVs provide a new mode of industrialized transportation whose users can only choose between transportation services, but have little or no say about the broader social implications of the technology. We argue that perspectives from social justice and ethics show that SDVs have implications beyond transportation, with profound consequences for users and societies. In particular, values such as privacy, security, and responsibility may be changed for good or bad, in both the short and long-term. The examination of these changes, while the technology is still under foundational development, is as urgent as it is needed.