Relevant bibliographies by topics / Highly automated driving

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Highly automated driving'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Highly automated driving"

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Bartels, Arne, Thanh-Binh To, Simon Karrenberg, and Andreas Weiser. "Highly Automated Driving on Motorways." ATZ worldwide eMagazine 113, no. 9 (February 9, 2011): 28–33. http://dx.doi.org/10.1365/s38311-011-0086-4.

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Mazzega, Jens, Frank Köster, Karsten Lemmer, and Thomas Form. "Testing of Highly Automated Driving Functions." ATZ worldwide 118, no. 10 (September 27, 2016): 44–48. http://dx.doi.org/10.1007/s38311-016-0101-x.

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Navarro, Jordan, and Catherine Gabaude. "Human factors perspectives on highly automated driving." Le travail humain 83, no. 4 (2020): 285. http://dx.doi.org/10.3917/th.834.0285.

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Junietz, Philipp, Udo Steininger, and Hermann Winner. "Macroscopic Safety Requirements for Highly Automated Driving." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 3 (February 21, 2019): 1–10. http://dx.doi.org/10.1177/0361198119827910.

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The common expectation for highly automated vehicles (HAVs) is that an introduction will lead to increased road safety and a reduction in traffic fatalities—at least in relation to the mileage. However, quantizing the safety requirements is still in discussion. This paper analyzes the risk acceptance in other fields and applies the safety level on today’s traffic to derive references for acceptable risks. The focus is on macroscopic safety requirements, meaning accident rates per mileage, and not the behavior in individual driving situations. It was concluded that the acceptable risk varies according to the group involved and with the field share of automated vehicles. Increased safety of conventional driving in the future could lead to higher requirements as well. We also point out that it is not guaranteed that the given acceptable risk levels will also accepted by the user, because factors other than the accident statistics are relevant. However, as none of these risk levels can be proven before introduction, the monitoring of vehicles in the field is suggested. Despite increased research efforts in safety validation, uncertainty surrounding the safety of HAVs will remain at the time of introduction. Different introduction and risk management strategies are briefly introduced.
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Kämpchen, Nico, Michael Aeberhard, Michael Ardelt, and Sebastian Rauch. "Technologies for highly automated driving on highways." ATZ worldwide 114, no. 6 (June 2012): 34–38. http://dx.doi.org/10.1007/s38311-012-0176-y.

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Kerschbaum, Philipp, Lutz Lorenz, and Klaus Bengler. "Highly automated driving with a decoupled steering wheel." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 58, no. 1 (September 2014): 1686–90. http://dx.doi.org/10.1177/1541931214581352.

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Navarro, Jordan. "A state of science on highly automated driving." Theoretical Issues in Ergonomics Science 20, no. 3 (February 22, 2018): 366–96. http://dx.doi.org/10.1080/1463922x.2018.1439544.

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Heitz, Thomas, Arne Schacht, Tim Bayer, and Daniel Kreutz. "Steering Concepts for Highly Automated and Autonomous Driving." ATZ worldwide 120, no. 11 (October 26, 2018): 18–23. http://dx.doi.org/10.1007/s38311-018-0154-0.

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Henriques, Bernardo, Thomas Mauthner, Gernot Hasenbichler, and Indula Amarasinghe. "Garbage Collection Vehicles with Highly Automated Driving Features." ATZheavy duty worldwide 14, no. 2 (June 2021): 10–15. http://dx.doi.org/10.1007/s41321-021-0419-1.

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Skottke, Eva-Maria, Günter Debus, Lei Wang, and Lynn Huestegge. "Carryover Effects of Highly Automated Convoy Driving on Subsequent Manual Driving Performance." Human Factors: The Journal of the Human Factors and Ergonomics Society 56, no. 7 (March 4, 2014): 1272–83. http://dx.doi.org/10.1177/0018720814524594.

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Dissertations / Theses on the topic "Highly automated driving"

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Behere, Sagar. "Reference Architectures for Highly Automated Driving." Doctoral thesis, KTH, Inbyggda styrsystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-179306.

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Highly automated driving systems promise increased road traffic safety, as well as positive impacts on sustainable transportation by means of increased traffic efficiency and environmental friendliness. The design and development of such systems require scientific advances in a number of areas. One area is the vehicle's electrical/electronic (E/E) architecture. The E/E architecture can be presented using a number of views, of which an important one is the functional view. The functional view describes the decomposition of the system into its main logical components, along with the hierarchical structure, the component inter-connections, and requirements. When this view captures the principal ideas and patterns that constitute the foundation of a variety of specific architectures, it may be termed as a reference architecture. Two reference architectures for highly automated driving form the principal contribution of this thesis. The first reference architecture is for cooperative driving. In a cooperative driving situation, vehicles and road infrastructure in the vicinity of a vehicle continuously exchange wireless information and this information is then used to control the motion of the vehicle. The second reference architecture is for autonomous driving, wherein the vehicle is capable of driver-less operation even without direct communication with external entities. The description of both reference architectures includes their main components and the rationale for how these components should be distributed across the architecture and its layers. These architectures have been validated via multiple real-world instantiations, and the guidelines for instantiation also form part of the architecture description. A comparison with similar architectures is also provided, in order to highlight the similarities and differences. The comparisons show that in the context of automated driving, the explicit recognition of components for semantic understanding, world modeling, and vehicle platform abstraction are unique to the proposed architecture. These components are not unusual in architectures within the Artificial Intelligence/robotics domains; the proposed architecture shows how they can be applied within the automotive domain. A secondary contribution of this thesis is a description of a lightweight, four step approach for model based systems engineering of highly automated driving systems, along with supporting model classes. The model classes cover the concept of operations, logical architecture, application software components, and the implementation platforms. The thesis also provides an overview of current implementation technologies for cognitive driving intelligence and vehicle platform control, and recommends a specific setup for development and accelerated testing of highly automated driving systems, that includes model- and hardware-in-the-loop techniques in conjunction with a publish/subscribe bus. Beyond the more "traditional" engineering concepts, the thesis also investigates the domain of machine consciousness and computational self-awareness. The exploration indicates that current engineering methods are likely to hit a complexity ceiling, breaking through which may require advances in how safety-critical systems can self-organize, construct, and evaluate internal models to reflect their perception of the world. Finally, the thesis also presents a functional architecture for the brake system of an autonomous truck. This architecture proposes a reconfiguration of the existing brake systems of the truck in a way that provides dynamic, diversified redundancy, and an increase in the system reliability and availability, while meeting safety requirements.

QC 20151216

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Eriksson, Hans Olof Alexander. "Control transitions in highly automated driving." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/416080/.

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The focus of this thesis is to assess how drivers interact with automated driving systems, more specifically: how control transitions from automated driving to manual driving and vice versa are executed and can be improved upon. In doing so, it identifies the key elements in research into control transitions in automated driving and addresses them. Whilst automated driving shows great promise in reducing road accident rates and congestion it is no panacea in driving safety at its current level (SAE Level 2 and Level 3). Until full autonomy (SAE Level 4) can be realised drivers will still have to be prepared to resume control when the automated driving system can no longer handle a situation. Research has shown that when drivers are exposed to automation, their reaction time slows, and the sudden change of task creates a sudden spike in workload. Such events could lead to incidents. To investigate this problem, the thesis utilise a multi-method using driving simulators as well as on road trials. Ultimately, the thesis aims to provide insights into how drivers handle the transition of control and whether this transition can be assisted by different levels of information support. Recommendations regarding the design of control transitions in highly automated driving are valuable for policy makers and vehicle manufacturers alike when designing and deploying automated vehicles of the future.
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Louw, Tyron Linton. "The human factors of transitions in highly automated driving." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/17148/.

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The aim of this research was to investigate the nature of the out-of-the-loop (OoTL) phenomenon in highly automated driving (HAD), and its effect on driver behaviour before, during, and after the transition from automated to manual control. The work addressed questions relating to how automation affects drivers' (i) performance in transition situations requiring control- and tactical-level responses, (ii) their behaviour in automation compared to in manual driving, (iii-iv) their visual attention distribution before and during the transition, as well as (v) their perceptual-motor performance after resuming control. A series of experiments were developed to take drivers progressively further OoTL for short periods during HAD, by varying drivers' secondary task engagement and the amount of visual information from the system and environment available to them. Once the manipulations ended, drivers were invited to determine a need to resume control in critical and non-critical vehicle following situations. Results showed that, overall, drivers looked around more during HAD, compared to manual driving, and had poorer vehicle control in critical transition situations. Generally, the further OoTL drivers were during HAD, the more dispersed their visual attention. However, within three seconds of the manipulations ending, the differences between the conditions resolved, and in many cases, this was before drivers resumed control. Differences between the OoTL manipulations emerged once again in terms of the timing of drivers' initial response (take-over time) in critical events, where the further OoTL drivers were the longer it took them to resume control, but there was no difference in the quality of the subsequent vehicle control. Results suggest that any information presented to drivers during automation should be placed near the centre of the road and that kinematically early avoidance response may be more important for safety than short take-over times. This thesis concludes with a general conceptualisation of the relationship between a number of driver and vehicle/environment factors that influence driver performance in the transition.
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Vanholme, Benoit. "Highly automated driving on highways based on legal safety." Thesis, Evry-Val d'Essonne, 2012. http://www.theses.fr/2012EVRY0018/document.

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A travers des systèmes d’assistance à la conduite, l’automatisation de la conduite est introduite graduellement, avec le but de créer un transport plus sûr, confortable et moins polluant. Cette thèse discute le développement d’un système d’assistance à la conduite qui permet une conduite automatisée sur autoroute. La thèse présente le concept « Legal Safety », qui base le développement d’un système d’assistance à la conduite sur le code de la route international. Ceci permet de partager la route avec des conducteurs humains, sans nécessairement changer l’équipement sur l’infrastructure ou sur les autres véhicules. Le « Legal Safety » permet aussi un partage intuitif avec le conducteur du véhicule égo. Chapitre 1 situe le concept « Legal Safety » dans les concepts des systèmes d’assistance à la conduite existants, et discute la méthodologie de recherche de la thèse. Chapitre 2 présente les spécifications sur les composants de perception, contrôle et IHM et compare ces spécifications avec l’état de l’art de ces composants. Chapitre 3 propose le développement d’un composant de calculation de trajectories pour une conduite sur autoroute et discute la contribution de la thèse par rapport l’état de l’art. Chapitre 4 présente le développement du système sur les véhicules et simulateurs du laboratoire LIVIC et des projets HAVEit et ABV. Les différentes implémentations sur PC et sur ECU sont discutées. Chapitre 5 discute les contributions de la thèse. Ce chapitre conclue que le « Legal Safety » pour les composants décision, contrôle et IHM serait possible avec la technologie état de l’art. Une perception selon le « Legal Safety » pourrait être développée en moyen terme
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). 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 can interact with the human driver, via human rules. If needed, the driving system takes over control in order to avoid accidents. With the third set of rules of the legal safety concept, 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
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Hiller, Tobias [Verfasser], and Hubert [Gutachter] Roth. "Highly precise MEMS gyroscopes for fully automated driving / Tobias Hiller ; Gutachter: Hubert Roth." Siegen : Universitätsbibliothek der Universität Siegen, 2021. http://d-nb.info/1232495522/34.

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Banks, Victoria A. "Human factors considerations in the design and development of highly automated driving systems." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/397266/.

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Increasing levels of automation within the driving task has seen the driver’s role change from an active operator to one of a passive monitor. However, systems design has been plagued by criticism for failing to acknowledge the new role of the driver within the system network. To further our understanding of the driver’s role within an automated driving system, the theory of Distributed Cognition was adopted. Distributed Cognition provides a useful framework for the investigation of task partitioning between multiple system agents. A novel Systems Design Framework has been developed as part of this thesis that utilises both qualitative and quantitative research methodologies within the Distributed Cognition paradigm. The framework is divided into two phases, the first phase requires an understanding of how individual system agents function to create models that show how these components share information using Operator Sequence Diagrams whilst empirical methods were used to validate these models in the second phase (e.g. Verbal Protocol Analysis and Network Analysis). These extension methodologies were useful in highlighting a number of design weaknesses, beyond the modelled technological components, that required modification to improve overall system design. The Systems Design Framework has been successfully applied to assist Systems Engineers with a foundation to design and conduct research into the human factors implications of different levels of automation within driving.
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Krampell, Martin. "Accelerated Behavioural Adaptation through Targeted Training Programs : the Case of Highly Automated Driving." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-129626.

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A prominent issue in the field of automotive research is the apparent lack of consideration given to the potentially safety-critical differences between novice and experienced users of Advanced Driver Assistance System (ADAS). Conducting experiments with novices only often results in the generation of unrepresentative findings, as these new systems often come with a lengthy adaptation period following their introduction. Running experiments with experienced drivers, however, is difficult, as these are often few and far between, if they even exist. To alleviate this discrepancy, and to help researchers acquire participants more akin to experienced drivers, even before a system has been launched, the approach of AcceLerated Behavioural Adaptation through Targeted tRaining prOgramS (ALBATROS) is proposed. It aims at training drivers in the use of the system, ideally giving them a level of experience similar to experienced users of said systems. A framework for the ALBATROS approach is presented, as is the development of a proof-of-concept training program following this approach. Likewise, a mock-up ADAS, that provides drivers with both longitudinal and lateral support of the vehicle, dubbed the Driver Assist (DA), is presented, for which the training program (the DATP) is developed. The current study presents an experiment designed to validate the efficacy of the DATP, and ultimately, the ALBATROS approach itself. The current study concludes that DATP-trained drivers display significantly improved understanding of the DA system following training and are significantly more likely to retake control in critical situations, than are untrained drivers. Thus, the ALBATROS approach appears a viable approach in giving drivers a better understanding of an ADAS system. However, whether the DATP succeeded in creating drivers similar in experience and understanding to real experienced users of said sys- tem, and if so, exactly how similar, is still unknown. More research is needed, specifically, studies comparing experienced users with those having been trained with the ALBATROS approach.
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Stephan, Amelie [Verfasser], Dietrich [Akademischer Betreuer] Manzey, Dietrich [Gutachter] Manzey, and Mark [Gutachter] Vollrath. "Trust in highly automated driving / Amelie Stephan ; Gutachter: Dietrich Manzey, Mark Vollrath ; Betreuer: Dietrich Manzey." Berlin : Technische Universität Berlin, 2019. http://d-nb.info/1184983569/34.

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Herold, Maximilian [Verfasser], Hermann [Akademischer Betreuer] Winner, and Steffen [Akademischer Betreuer] Müller. "Redundant Steering System for Highly Automated Driving of Trucks / Maximilian Herold ; Hermann Winner, Steffen Müller." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2019. http://d-nb.info/1201820537/34.

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Basantis, Alexis Rae. "Assessing Alternate Approaches for Conveying Automated Vehicle Intentions." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/95219.

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Objectives: Research suggests the general public has a lack of faith in highly automated vehicles (HAV) stems from a lack of system transparency while in motion (e.g., the user not being informed on roadway perception or anticipated responses of the car in certain situations). This problem is particularly prevalent in public transit or ridesharing applications, where HAVs are expected to debut, and when the user has minimal training on, and control over, the vehicle. To improve user trust and their perception of comfort and safety, this study aimed to develop more detailed and tailored human-machine interfaces (HMI) aimed at relying automated vehicle intended actions (i.e., "intentions") and perceptions of the driving environment to the user. Methods: This project developed HMI systems, with a focus on visual and auditory displays, and implemented them into a HAV developed at the Virginia Tech Transportation Institute (VTTI). Volunteer participants were invited to the Smart Roads at VTTI to experience these systems in real-world driving scenarios, especially ones typically found in rideshare or public transit operations. Participant responses and opinions about the HMIs and their perceived levels of comfort, safety, trust, and situational awareness were captured via paper-based surveys administered during experimentation. Results: There was a considerable link found between HMI modality and users' reported levels of comfort, safety, trust, and situational awareness during experimentation. In addition, there were several key behavioral factors that made users more or less likely to feel comfortable in the HAV. Conclusions: Moving forward, it will be necessary for HAVs to provide ample feedback to users in an effort to increase system transparency and understanding. Feedback should consistently and accurately represent the driving landscape and clearly communicate vehicle states to users.
Master of Science
One of the greatest barriers to the entry of highly automated vehicles (HAV) into the market is the lack of user trust in the vehicle. Research has shown that this lack of faith in the system primarily stems from a lack of system transparency while in motion (e.g., the user not being told how the car will react in a certain situation) and not having an effective way to control the vehicle in the event of a system failure. This problem is particularly prevalent in public transit or ridesharing applications, where HAVs are expected to first appear and where the user has less training and control over the vehicle. To improve user trust and perceptions of comfort and safety, this study developed human-machine interface (HMI) systems, focusing on visual and auditory displays, to better relay automated vehicle "intentions" and the perceived driving environment to the user. These HMI systems were then implemented into a HAV developed at the Virginia Tech Transportation Institute (VTTI) and tested with volunteer participants on the Smart Roads.
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Books on the topic "Highly automated driving"

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Nwagboso, Christopher O. Advanced vehicles and infrastructure systems: Computer applications, control, and automation. Chichester: Wiley, 1997.

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Intelligent, Vehicles Symposium (1995 Detroit Mich ). Proceedings of the Intelligent Vehicles '95 Symposium, September 25-26, 1995, Detroit, USA. Piscataway, NJ: IEEE Service Center, 1995.

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Intelligent Vehicles '94 Symposium (1994 Paris, France). Proceedings of the Intelligent Vehicles '94 Symposium: October 24-26, 1994, Paris, France. [Piscataway, NJ: IEEE Service Center, 1994.

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IEEE Intelligent Vehicles Symposium (2002 Versailles, France). IV'2002: IEEE Intelligent Vehicle Symposium = IEEE Symposium sur les Véhicules Intelligents : proceedings : June 17-21, 2002, Versailles, France. Piscataway, N.J: IEEE, 2003.

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Chinn, George M. The machine gun: Development of full automatic machine gun systems, high rate of fire power driven cannon, and automatic grenade launchers by the United States and her allies, following World War II, Korean Police Action, and the Vietnam conflict. [: ], 1987.

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Meng Lu, ed. Cooperative Intelligent Transport Systems: Towards high-level automated driving. Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/pbtr025e.

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Reeves, Jodie. Human Factors in Automated Driving Scenarios: Assessment of Research, Technology, and Concepts. Nova Science Publishers, Incorporated, 2014.

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Gábos, András, and István György Tóth. Recession, Recovery, and Regime Change: Effects on Child Poverty in Hungary. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198797968.003.0006.

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Despite high spending on family benefits and the high poverty reduction effectiveness of cash benefits, the risk of child poverty in Hungary have been higher than the EU average since the early 1990s in which the relatively high share of children in very low work-intensity households played a significant role. The crisis period brought an even higher poverty risk for children. According to the chapter’s findings, the increase in child poverty in the first phase of the crisis was driven by labour market processes (an increasing share of children in low work-intensity households), while the automatic stabilizers reduced the magnitude of these effects. By contrast, in the second phase, labour market processes started to improve (although mainly through controversial policy tools, like public work and outward migration), though the shift towards a regressive social policy regime contributed to increased poverty rates via the reduced poverty reduction impacts of cash benefits.
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Engineers, Society of Automotive, and Future Transportation Technology Conference and Exposition (1995 : Costa Mesa, Calif.), eds. Systems and issues in ITS. Warrendale, PA: Society of Automotive Engineers, 1995.

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Engineers, Society of Automotive, and SAE International Congress & Exposition (1995 : Detroit, Mich.), eds. IVHS and advanced transportation systems. Warrendale, Pa: Society of Automotive Engineers, 1995.

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Book chapters on the topic "Highly automated driving"

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Kompass, Klaus, Markus Schratter, and Thomas Schaller. "Active Safety Towards Highly Automated Driving." In Automated Driving, 371–86. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31895-0_15.

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Paulweber, Michael. "Validation of Highly Automated Safe and Secure Systems." In Automated Driving, 437–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31895-0_18.

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Wotawa, Franz. "Testing Autonomous and Highly Configurable Systems: Challenges and Feasible Solutions." In Automated Driving, 519–32. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31895-0_22.

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Kirschbaum, Markus. "Highly automated driving for commercial vehicles." In 6th International Munich Chassis Symposium 2015, 5–15. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-09711-0_2.

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Baldwin, Carryl L., and Ian McCandliss. "Attention Management in Highly Autonomous Driving." In Human Performance in Automated and Autonomous Systems, 231–48. Boca Raton, FL : CRC Press/Taylor & Francis Group, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429458330-12.

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Galbas, Roland. "Highly Automated Driving—Disruptive Elements and Consequences." In Advanced Microsystems for Automotive Applications 2016, 141–52. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44766-7_12.

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Redzic, Ogi, and Dietmar Rabel. "A Location Cloud for Highly Automated Driving." In Road Vehicle Automation 2, 49–60. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19078-5_5.

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Jomrich, Florian, Florian Fischer, Steffen Knapp, Tobias Meuser, Björn Richerzhagen, and Ralf Steinmetz. "Enhanced Cellular Bandwidth Prediction for Highly Automated Driving." In Communications in Computer and Information Science, 328–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26633-2_16.

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Feth, Patrik, Rasmus Adler, Takeshi Fukuda, Tasuku Ishigooka, Satoshi Otsuka, Daniel Schneider, Denis Uecker, and Kentaro Yoshimura. "Multi-aspect Safety Engineering for Highly Automated Driving." In Developments in Language Theory, 59–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99130-6_5.

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Stottan, Thomas. "The automotive digitalization – The way from driving yourself to highly automated driving." In Proceedings, 639–46. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-21194-3_49.

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Conference papers on the topic "Highly automated driving"

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Richardson, Natalie Tara, Michael Sinning, Michael Fries, Sonja Stockert, and Markus Lienkamp. "Highly automated truck driving." In AutomotiveUI '15: The 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2809730.2809733.

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Merat, Natasha, and A. Hamish Jamson. "How Do Drivers Behave in a Highly Automated Car?" In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2009. http://dx.doi.org/10.17077/drivingassessment.1365.

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Dickmann, Juergen, Nils Appenrodt, Hans-Ludwig Bloecher, C. Brenk, Thomas Hackbarth, Markus Hahn, Jens Klappstein, Marc Muntzinger, and Alfons Sailer. "Radar contribution to highly automated driving." In 2014 44th European Microwave Conference (EuMC). IEEE, 2014. http://dx.doi.org/10.1109/eumc.2014.6986787.

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Dickmann, Juergen, Nils Appenrodt, Hans-Ludwig Bloecher, C. Brenk, Thomas Hackbarth, Markus Hahn, Jens Klappstein, Marc Muntzinger, and Alfons Sailer. "Radar contribution to highly automated driving." In 2014 European Radar Conference (EuRAD). IEEE, 2014. http://dx.doi.org/10.1109/eurad.2014.6991295.

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Chen, Chao, Andre Gaschler, Markus Rickert, and Alois Knoll. "Task planning for highly automated driving." In 2015 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2015. http://dx.doi.org/10.1109/ivs.2015.7225805.

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Tobias, Schmid. "Safety Analysis for Highly Automated Driving." In 2018 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW). IEEE, 2018. http://dx.doi.org/10.1109/issrew.2018.000-7.

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Dogan, Ebru, Elsa Yousfi, Thierry Bellet, Charles Tijus, and Anne Guillaume. "Manual takeover after highly automated driving." In ECCE 2021: European Conference on Cognitive Ergonomics 2021. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3452853.3452880.

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Liu, Tianbo, Nan Xu, Xiyang Liu, and Chong Xu. "Self-driving and Highly Automated Control System for Driving Simulator." In 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/mcei-16.2016.42.

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Louw, Tyron, Natasha Merat, and Hamish Jamson. "Engaging with Highly Automated Driving: To be or Not to be in the Loop?" In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2015. http://dx.doi.org/10.17077/drivingassessment.1570.

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Hergeth, Sebastian, Lutz Lorenz, Josef F. Krems, and Lars Toenert. "Effects of Take-Over Requests and Cultural Background on Automation Trust in Highly Automated Driving." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2015. http://dx.doi.org/10.17077/drivingassessment.1591.

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Reports on the topic "Highly automated driving"

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Balali, Vahid, Arash Tavakoli, and Arsalan Heydarian. A Multimodal Approach for Monitoring Driving Behavior and Emotions. Mineta Transportation Institute, July 2020. http://dx.doi.org/10.31979/mti.2020.1928.

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Studies have indicated that emotions can significantly be influenced by environmental factors; these factors can also significantly influence drivers’ emotional state and, accordingly, their driving behavior. Furthermore, as the demand for autonomous vehicles is expected to significantly increase within the next decade, a proper understanding of drivers’/passengers’ emotions, behavior, and preferences will be needed in order to create an acceptable level of trust with humans. This paper proposes a novel semi-automated approach for understanding the effect of environmental factors on drivers’ emotions and behavioral changes through a naturalistic driving study. This setup includes a frontal road and facial camera, a smart watch for tracking physiological measurements, and a Controller Area Network (CAN) serial data logger. The results suggest that the driver’s affect is highly influenced by the type of road and the weather conditions, which have the potential to change driving behaviors. For instance, when the research defines emotional metrics as valence and engagement, results reveal there exist significant differences between human emotion in different weather conditions and road types. Participants’ engagement was higher in rainy and clear weather compared to cloudy weather. More-over, engagement was higher on city streets and highways compared to one-lane roads and two-lane highways.
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Porcel Magnusson, Cristina. Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles. SAE International, January 2021. http://dx.doi.org/10.4271/epr2021002.

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Autonomous vehicles (AVs) utilize multiple devices, like high-resolution cameras and radar sensors, to interpret the driving environment and achieve full autonomy. One of these instruments—the light detection and ranging (LiDAR) sensor—utilizes pulsed infrared (IR) light, typically at wavelengths of 905 nm or 1,550 nm, to calculate object distance and position. Exterior automotive paint covers an area larger than any other exterior material. Therefore, understanding how LiDAR wavelengths interact with vehicle coatings is extremely important for the safety of future automated driving technologies. Sensing technologies and materials are two different industries that have not directly interacted in the perception and system sense. With the new applications in the AV industry, multidisciplinary approaches need to be taken to ensure reliability and safety in the future. Unsettled Topics Concerning Coating Detection by LiDAR in Autonomous Vehicles provides a transversal view of different industry segments, from pigment and coating manufacturers to LiDAR components and vehicle system development and integration. The report includes a structured decomposition of the different variables and technologies involved.
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Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS. SAE International, June 2021. http://dx.doi.org/10.4271/epr2021013.

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Current advanced driver-assistance systems (ADAS) and automated driving systems (ADS) rely on high-definition (HD) maps to enable a range of features and functions. These maps can be viewed as an additional sensor from an ADAS or ADS perspective as they impact overall system confidence, reduce system computational resource needs, help improve comfort and convenience, and ultimately contribute to system safety. However, HD mapping technology presents multiple challenges to the automotive industry. Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS identifies the current unsettled issues that need to be addressed to reach the full potential of HD maps for ADAS and ADS technology and suggests some possible solutions for initial map creation, map change detection and updates, and map safety levels.
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