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Autonomous Driving

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Handbook of Driver Assistance Systems

Abstract

In this chapter, a survey of the current state of research on autonomous driving is given and is set in the context of the requirements of an autonomous vehicle following the vision of an automated taxi. The overview is based on (scientific) publications and self-reports of the developing teams. Aspects of interest for this summary are approaches on environmental perception, self-perception, mission accomplishment, localization, cooperation, map usage, and functional safety.

Typically, emphasis is given to reliance on global satellite systems (e.g., GPS) and map data. Only a few approaches focus on environmental perception and scene understanding. Even though impressive demonstrations of autonomous driving have been presented in recent decades, this overview concludes that many aspects still remain only partially solved or even unsolved, especially when driving autonomously in public road traffic.

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References

  • Aeberhard M, Paul S, Kaempchen N, Bertram T (2011) Object existence probability fusion using dempster-shafer theory in a high-level sensor data fusion architecture. In: Intelligent vehicles symposium, IEEE, pp 770–775

    Google Scholar 

  • Ardelt M, Waldmann P (2011) Hybrides Steuerungs- und Regelungskonzept für das hochautomatisierte Fahren auf Autobahnen (Hybrid open- and closed-loop control concept for highly automated driving on highways). Automatisierungstechnik 59(12):738–750

    Article  Google Scholar 

  • Ardelt M, Coester C, Kaempchen N (2012) Highly automated driving on freeways in real traffic using a probabilistic framework. IEEE Trans Intell Transp Syst 13(4):1576–1585

    Article  Google Scholar 

  • Bacha A, Bauman C, Faruque R, Fleming M, Terwelp C, Reinholtz C, Hong D, Wicks A, Alberi T, Anderson D (2008) Odin: Team VictorTango’s entry in the DARPA Urban Challenge. J Field Robot 25(8):467–492

    Article  Google Scholar 

  • Bar Hillel A, Lerner R, Levi D, Raz G (2012) Recent progress in road and lane detection: a survey. Mach Vis Appl 25(3):727–745

    Article  Google Scholar 

  • Becker C, Dürr F (2005) On location models for ubiquitous computing. Pers Ubiquit Comput 9:20–31, Springer

    Article  Google Scholar 

  • Bertozzi M, Broggi A, Coati A, Fedriga RI (2013) A 13,000 km intercontinental trip with driverless vehicles: the VIAC experiment. Intell Transp Syst Mag 5(1):28–41

    Article  Google Scholar 

  • Bley O, Kutzner R, Friedrich B, Saust F, Wille J M, Maurer M, Wolf F, Naumann S, Junge M, Langenberg J, Niebel W, Schüler T, Bogenberger K (2011) Kooperative Optimierung von Lichtsignalsteuerung und Fahrzeugführung (Cooperative and optimised traffic signalling in urban networks). In: AAET 2011 – Automatisierungssysteme, Assistenzsysteme und eingebettete Systeme für Transportmittel (Automation systems, driver assistance systems and embedded systems for transport technologies), pp 57–77

    Google Scholar 

  • Broggi A, Bertozzi M, Fascioli A (1999) ARGO and the MilleMiglia in Automatico tour. IEEE Intell Syst Appl 14(1):55–64

    Article  Google Scholar 

  • Broggi A, Buzzoni M, Debattisti S, Grisleri P, Laghi MC, Medici P, Versari P (2013) Extensive tests of autonomous driving technologies. IEEE Trans Intell Transp Syst 14(3):1403–1415

    Article  Google Scholar 

  • Brown PJ (1996) The stick-e document: a framework for creating context-aware applications. Electron Publ Chichester 8:259–272

    Google Scholar 

  • Buschardt B, Donner E, Graab B, Hörauf U, Winkle T (2006) Analyse von Verkehrsunfällen mit FAS Potenzialeinschätzung am Beispiel des FAS Lane Departure Warning (Analysis of traffic accidents with ADAS potential estimation on the example of the ADAS lane departure warning) In: Tagung Aktive Sicherheit 2006. Technische Universität München, Lehrstuhl für Fahrzeugtechnik, München

    Google Scholar 

  • Chatila R, Laumond J (1985) Position referencing and consistent world modeling for mobile robots. Proc IEEE Int Conf Robot Autom 2:138–145

    Google Scholar 

  • Chiellino U, Winkle T, Graab B, Ernstberger A, Donner E, Nerlich M (2010) Was können Fahrerassistenzsysteme im Unfallgeschehen leisten? (What can driver assistance systems do in the event of an accident?). Zeitschrift für die gesamte Wertschöpfungskette Automobilwirtschaft 3:131–137, TÜV Media GmbH, Köln

    Google Scholar 

  • DARPA – Defense Advanced Research Projects Agency (2007) Urban challenge – route network definition file (RNDF) and mission data file (MDF) formats. http://archive.darpa.mil/grandchallenge/docs/RNDF_MDF_Formats_031407.pdf

  • Dickmanns ED, Behringer R, Hildebrandt T, Maurer M, Thomanek F, Schiehlen J (1994) The seeing passenger car ‘VaMoRs-P’. In: Intelligent vehicles symposium, IEEE, pp 68–73

    Google Scholar 

  • Dickmanns ED (2007) Dynamic vision for perception and control of motion. Springer

    Google Scholar 

  • Dickmanns ED (2015) Personal communication

    Google Scholar 

  • Donges E (1999) A conceptual framework for active safety in road traffic. Veh Syst Dyn 32(2–3):113–128

    Article  Google Scholar 

  • Eskandarian A (ed) (2012) Handbook of intelligent vehicles. Springer

    Google Scholar 

  • Fenton R (1970) Automatic vehicle guidance and control – a state of the art survey. IEEE Trans Veh Technol 19(1):153–161

    Article  Google Scholar 

  • Flament M, Otto HU, Alksic M, Guarise A, Löwenau J, Beuk L, Meier J, Sabel H (2005) ActMAP final report/Ertico. Forschungsbericht, D1.2

    Google Scholar 

  • Fries C, Luettel T, Wuensche HJ (2013) Combining model-and template-based vehicle tracking for autonomous convoy driving. In: Intelligent vehicles symposium, IEEE, pp 1022–1027

    Google Scholar 

  • Funke J, Theodosis P, Hindiyeh R, Stanek G, Kritatakirana K, Gerdes C, Langer D, Hernandez M, Muller-Bessler B, Huhnke B (2012) Up to the limits: autonomous Audi TTS. In: Intelligent vehicles symposium, IEEE, pp 541–547

    Google Scholar 

  • Gasser TM, Arzt C, Ayoubi M, Bartels A, Bürkle L, Eier J, Flemisch F, Häcker D, Hesse T, Huber W, Lotz C, Maurer M, Ruth-Schumacher S, Schwarz J, Vogt W (2012) Rechtsfolgen zunehmender Fahrzeugautomatisierung (Legal consequences of increasing levels of vehicle automation). Berichte der Bundesanstalt für Straßenwesen F83. Wirtschaftsverlag NW, Bergisch Gladbach

    Google Scholar 

  • Geiger A, Lauer M, Moosmann F, Ranft B, Rapp H, Stiller C, Ziegler J (2012) Team AnnieWAY’s entry to the grand cooperative driving challenge 2011. IEEE Trans Intell Transp Syst 13(3):1008–1017

    Article  Google Scholar 

  • Ghosh D, Sharman R, Raghav Rao H, Upadhyaya S (2007) Self-healing systems – survey and synthesis. Decis Support Syst Emerg Econ 42(4):2164–2185

    Article  Google Scholar 

  • Goebl M, Althoff M, Buss M, Färber G, Hecker F, Heißing B, Kraus S, Nagel R, León FP, Rattei F, Russ M, Schweitzer M, Thuy M, Wang C, Wünsche HJ (2008) Design and capabilities of the Munich cognitive automobile. In: Intelligent vehicles symposium, IEEE, pp 1101–1107

    Google Scholar 

  • Goldhammer M, Strigel E, Meissner D, Brunsmann U, Doll K, Dietmayer K (2012) Cooperative multi sensor network for traffic safety applications at intersections. In: Intelligent transportation systems conference, IEEE, pp 1178–1183

    Google Scholar 

  • Gregor R (2002) Fähigkeiten zur Missionsdurchführung und Landmarkennavigation (Abilities for mission execution and landmark navigation). Dissertation, Universität der Bundeswehr

    Google Scholar 

  • Himmelsbach M, Wünsche HJ (2012) Tracking and classification of arbitrary objects with bottom-up/top-down detection. In: Intelligent vehicles symposium, IEEE, pp 577–582

    Google Scholar 

  • Hitchcock A (1995) Intelligent vehicle/highway system safety: multiple collisions in automated highway systems. Forschungsbericht, University of California

    Google Scholar 

  • Hock CJL (1994) Wissensbasierte Fahrzeugführung mit Landmarken für autonome Roboter (Knowledge-based vehicle guidance with landmarks for autonomous robots). Dissertation, Universität der Bundeswehr

    Google Scholar 

  • Homm F, Kaempchen N, Burschka D (2011) Fusion of laserscannner and video based lanemarking detection for robust lateral vehicle control and lane change maneuvers. In: Intelligent vehicles symposium, IEEE, pp 969–974

    Google Scholar 

  • Hörwick M, Siedersberger, KH (2010a) Aktionspläne zur Erlangung eines sicheren Zustandes bei einem autonomen Stauassistenten (Action plans for achieving a safe state for an autonomous traffic jam assistance system) In: 4. Tagung Fahrerassistenz

    Google Scholar 

  • Hörwick M, Siedersberger KH (2010b) Strategy and architecture of a safety concept for fully automatic and autonomous driving assistance systems. In: Intelligent vehicles symposium, IEEE, pp 955–960

    Google Scholar 

  • Huang AS, Moore D, Antone M, Olson E, Teller S (2009) Finding multiple lanes in urban road networks with vision and lidar. Auton Robot 26(2–3):103–122

    Article  Google Scholar 

  • Hundelshausen Fv, Himmelsbach M, Hecker F, Müller A, Wünsche H-J (2009) Driving with tentacles – integral structures for sensing and motion. Springer Tracts Adv Robot 56:393–440

    Google Scholar 

  • Isermann R (2006) Fault-diagnosis systems: an introduction from fault detection to fault tolerance. Springer, Berlin/Heidelberg

    Book  Google Scholar 

  • Isermann R, Schwarz R, Stölzl S (2002) Fault-tolerant drive-by-wire systems. IEEE Control Syst 22(5):64–81

    Article  Google Scholar 

  • Kammel S, Ziegler J, Pitzer B, Werling M, Gindele T, Jagzent D, Schröder J, Thuy M, Goebl M, Hundelshausen Fv, Pink O, Frese C, Stiller C (2008) Team AnnieWAY’s autonomous system for the 2007 DARPA Urban Challenge. J Field Robot 25(9):615–639

    Google Scholar 

  • Kim J, Rajkumar R, Jochim M (2013) Towards dependable autonomous driving vehicles: a system-level approach. SIGBED 10:29–32

    Article  Google Scholar 

  • Knapp A, Neumann M, Brockmann M, Walz R, Winkle T (2009) Code of practice for the design and evaluation of ADAS. Preventive and Active Safety Applications, eSafety for road and air transport, European Commission Integrated Project, Response 3

    Google Scholar 

  • Lategahn H, Stiller C (2012) Experimente zur hochpräzisen landmarkenbasierten Eigenlokalisierung in unsicherheitsbehafteten digitalen Karten (Experiments for highly precise landmark-based self-localization in uncertain digital maps). In: Workshop Fahrerassistenzsysteme Walting

    Google Scholar 

  • Laurgeau C (2012) Intelligent vehicle potential and benefits. In: Eskandarian A (ed) Handbook of intelligent vehicles. Springer, London, pp 1537–1551

    Chapter  Google Scholar 

  • Leonard J, How J, Teller S, Berger M, Campbell S, Fiore G, Fletcher L, Frazzoli E, Huang A, Karaman S (2008) A perception-driven autonomous urban vehicle. J Field Robot 25(10):727–774

    Article  Google Scholar 

  • Levinson JS (2011) Automatic laser calibration, mapping, and localization for autonomous vehicles. Dissertation, Stanford University

    Google Scholar 

  • Levinson J, Askeland J, Becker J, Dolson J, Held D, Kammel S, Kolter JZ, Langer D, Pink O, Pratt V, Sokolsky M, Stanek G, Stavens D, Teichman A, Werling M, Thrun S (2011) Towards fully autonomous driving: systems and algorithms. In: IEEE Intelligent vehicles symposium, IEEE, pp 163–168

    Google Scholar 

  • Luettel T, Himmelsbach M, Hundelshausen F, Manz M, Mueller A, Wuensche HJ (2009) Autonomous offroad navigation under poor GPS conditions. In: Planning, perception and navigation for intelligent vehicles, p 56

    Google Scholar 

  • Luettel T, Himmelsbach M, Manz M, Mueller A, Hundelshausen F, Wuensche HJ (2011) Combining multiple robot behaviors for complex off-road missions. In: Intelligent transportation systems conference, IEEE, pp 674–680

    Google Scholar 

  • Luettel T, Himmelsbach M, Wuensche HJ (2012) Autonomous ground vehicles’ concepts and a path to the future. Proc IEEE 100(13):1831–1839

    Article  Google Scholar 

  • Manz M (2013) Modellbasierte visuelle Wahrnehmung zur autonomen Fahrzeugführung (Model-based visual perception for autonomous vehicle guidance). Dissertation, Universität der Bundeswehr München

    Google Scholar 

  • Manz M, Himmelsbach M, Luettel T, Wuensche HJ (2011) Detection and tracking of road networks in rural terrain by fusing vision and LIDAR. In: Intelligent robots and systems, IEEE/RSJ, pp 4562–4568

    Google Scholar 

  • Matthaei R (2015) Wahrnehmungsgestützte Lokalisierung in fahrstreifengenauen Karten für Assistenzsysteme und autonomes Fahren (Perception-based localization in lane-level maps for ADAS and autonomous driving). Dissertation, Braunschweig, accepted/forthcoming

    Google Scholar 

  • Matthaei R, Maurer M (2015) Autonomous driving – a top-down approach. Automatisierungstechnik 63(4):155–167 accepted

    Google Scholar 

  • Matthaei R, Bagschik G, Maurer M (2014a) Map-relative localization in lane-level maps for ADAS and autonomous driving. In: Intelligent vehicles symposium, IEEE, pp 49–55

    Google Scholar 

  • Matthaei R, Bagschik G, Rieken J, Maurer M (2014b) Stationary urban environment modeling using multi-layer-grids. In: Proceedings of the 17th international conference on information fusion

    Google Scholar 

  • Matthaei R, Reschka A, Bagschik G, Escher M, Menzel T, Rieken J, Scheide T, Schuldt F, Ulbrich S, Wendler JT, Hecker P, Maurer M (2015) Das Projekt Stadtpilot – Automatisiertes Fahren an der TU Braunschweig (The project Stadtpilot – automated driving at TU Braunschweig). Z Gesamte Wertschöpfungskette Automobilwirtschaft 18(1):12–22

    Google Scholar 

  • Maurer M (2000) Flexible Automatisierung von Straßenfahrzeugen mit Rechnersehen (Flexible automation of road vehicles with computer vision). VDI-Verlag, Düsseldorf

    Google Scholar 

  • Maurer M (2013) Autonome Automobile – Wer steuert das Fahrzeug der Zukunft? (Who drives the vehicle of the future?) Daimler und Benz Stiftung, Vortrag Forschungsprojekt „Villa Ladenburg“, Untertürkheim. https://www.daimler-benz-stiftung.de/cms/images/dbs-bilder/foerderprojekte/villa-ladenburg/Dialog_im_Museum_Vortrag_Prof_Maurer.pdf

  • Miller I, Campbell M, Huttenlocher D, Kline FR, Nathan A, Lupashin S, Catlin J, Schimpf B, Moran P, Zych N, Garcia E, Kurdziel M, Fujishima H (2008) Team Cornell’s Skynet: Robust perception and planning in an urban environment. J Field Robot 25(8):493–527

    Article  Google Scholar 

  • Montemerlo M, Becker J, Bhat S, Dahlkamp H, Dolgov D, Ettinger S, Haehnel D, Hilden T, Hoffmann G, Huhnke B, Johnston D, Klumpp S, Langer D, Levandowski A, Levinson J, Marcil J, Orenstein D, Paefgen J, Penny I, Petrovskaya A, Pflueger M, Stanek G, Stavens D, Vogt A, Thrun S (2008) Junior: the Stanford entry in the Urban Challenge. J Field Robot 25(9):569–597

    Article  Google Scholar 

  • Moore DC, Huang AS, Walter M, Olson E, Fletcher L, Leonard J, Teller S (2009) Simultaneous local and global state estimation for robotic navigation. In: International conference on robotics and automation, IEEE, pp 3794–3799

    Google Scholar 

  • Müller A, Himmelsbach M, Lüttel T, Hundelshausen Fv, Wünsche HJ (2011) GIS-based topological robot localization through LIDAR crossroad detection. In: Intelligent transportation systems conference, IEEE, pp 2001–2008

    Google Scholar 

  • NDMV – Nevada Department of Motor Vehicles (2012) Adopted regulation of the Department of Motor Vehicles LCB File No R084-11

    Google Scholar 

  • Nilsson JO, Zachariah D, Skog I (2012) Global navigation satellite systems: an enabler for in-vehicle navigation. In: Eskandarian A (ed) Handbook of intelligent vehicles. Springer, London, pp 311–342

    Chapter  Google Scholar 

  • Nothdurft T, Hecker P, Ohl S, Saust F, Maurer M, Reschka A, Böhmer JR (2011a) Stadtpilot: first fully autonomous test drives in urban traffic. In: Intelligent transportation systems conference, IEEE, pp 919–924

    Google Scholar 

  • Nothdurft T, Hecker P, Frankiewicz T, Gacnik J, Köster F (2011b) Reliable information aggregation and exchange for autonomous vehicles. In: Vehicular technology conference, IEEE, pp 1–5

    Google Scholar 

  • Nunen Ev, Kwakkernaat R, Ploeg J, Netten B (2012) Cooperative competition for future mobility. IEEE Trans Intell Transp Syst 13(3):1018–1025

    Google Scholar 

  • Pellkofer M (2003) Verhaltensentscheidung für autonome Fahrzeuge mit Blickrichtungssteuerung (Behavior decision-making for autonomous vehicles with gaze control). Dissertation, Universität der Bundeswehr München

    Google Scholar 

  • Pomerleau D, Jochem T (1996) Rapidly adapting machine vision for automated vehicle steering. IEEE Expert 11(2):19–27

    Article  Google Scholar 

  • Rauch A, Maier S, Klanner F, Dietmayer K (2013) Inter-vehicle object association for cooperative perception systems. In: Intelligent transportation systems conference, IEEE, pp 893–898

    Google Scholar 

  • Rauskolb FW, Berger K, Lipski C, Magnor M, Cornelsen K, Effertz J, Form T, Graefe F, Ohl S, Schumacher W, Wille JM, Hecker P, Nothdurft T, Doering M, Homeier K, Morgenroth J, Wolf L, Basarke C, Berger C, Gülke T, Klose F, Rumpe B (2008) Caroline: an autonomously driving vehicle for urban environments. J Field Robot 25(9):674–724

    Article  Google Scholar 

  • Reschka A (2015) Safety concept for autonomous vehicles. In: Maurer M, Gerdes JC, Lenz B, Winner H (eds) Autonomous driving. Springer Vieweg, forthcoming, Springer-Verlag GmbH Berlin Heidelberg, Berlin Heidelberg

    Google Scholar 

  • Reschka A, Böhmer JR, Nothdurft T, Hecker P, Lichte B, Maurer M (2012a) A surveillance and safety system based on performance criteria and functional degradation for an autonomous vehicle. In: Intelligent transportation systems conference, IEEE, pp 237–242

    Google Scholar 

  • Reschka A, Böhmer, JR, Saust F, Lichte B, Maurer M (2012b) Safe, dynamic and comfortable longitudinal control for an autonomous vehicle. In: Intelligent vehicles symposium, IEEE, pp 346–351

    Google Scholar 

  • Rosenblatt J (1997) DAMN: a distributed architecture for mobile navigation. Dissertation, Robotics Institute, Carnegie Mellon University

    Google Scholar 

  • SAE – Society of Automotive Engineers (2014) Taxonomy and definitions for terms related to on-road motor vehicle automated driving system. SAE International, Warrendale

    Google Scholar 

  • Saust F, Bley O, Kutzner R, Wille JM, Friedrich B, Maurer M (2010) Exploitability of vehicle related sensor data in cooperative systems. In: Intelligent transportation systems conference, IEEE, pp 1724–1729

    Google Scholar 

  • Saust F, Wille JM, Maurer M (2012) Energy-optimized driving with an autonomous vehicle in urban environments. In: Vehicular technology conference, IEEE, pp 1–5

    Google Scholar 

  • Shladover S (2007) PATH at 20 – history and major milestones. IEEE Trans Intell Transp Syst 8(4):584–592

    Article  Google Scholar 

  • Siedersberger KH (2003) Komponenten zur automatischen Fahrzeugführung in sehenden (semi-)autonomen Fahrzeugen (Components for automated vehicle guidance in perceiving (semi-)autonomous vehicles). Dissertation, Universität der Bundeswehr München

    Google Scholar 

  • Singh, S (ed) (2006) Special Issue on the DARPA Grand Challenge, Part 2. J Field Robot 23(9):655–835. Wiley Subscription Services, Inc., 2008

    Google Scholar 

  • Singh, S (ed) (2008a) Special Issue on the 2007 DARPA Urban Challenge Part I. J Field Robot 25(8):432–566. Wiley Subscription Services, Inc., 2008

    Google Scholar 

  • Singh, S (ed) (2008b) Special Issue on the 2007 DARPA Urban Challenge Part II. J Field Robot 25(9):567–724. Wiley Subscription Services, Inc., 2008

    Google Scholar 

  • Singh, S (ed) (2008c) Special Issue on the 2007 DARPA Urban Challenge Part III. J Field Robot 25(10):725–860. Wiley Subscription Services, Inc., 2008

    Google Scholar 

  • Smith BW (2014) Lawyers and engineers can speak the same robot language. In: Robot law. Forthcoming, Edward Elgar Publishing Ltd., Cheltenham, UK

    Google Scholar 

  • Spieß E (2014) Kooperation. In: Wirtz MA (ed) Dorsch – Lexikon der Psychologie (Dorsch – Lexicon of psychology). https://portal.hogrefe.com/dorsch/kooperation/. Accessed 05 Dec 2014

  • Stanek G, Langer D, Müller-Bessler B, Huhnke B (2010) Junior 3: a test platform for advanced driver assistance systems. In: Intelligent vehicles symposium, IEEE, pp 143–149

    Google Scholar 

  • Stiller C, Burgard W, Deml B, Eckstein L, Flemisch F, Köster F, Maurer M, Wanielik G (2013) Kooperativ interagierende Automobile (Cooperative interacting automobiles). Schwerpunktprogramm der Deutschen Forschungsgemeinschaft (DFG priority program)

    Google Scholar 

  • Strang T, Linnhoff-Popien C (2004) A context modeling survey. In: Workshop on advanced context modeling, reasoning and management, 6th international conference on ubiquitous computing, pp 1–8

    Google Scholar 

  • Thorpe C, Jochem T, Pomerleau D (1997) The 1997 automated highway free agent demonstration. In: Intelligent transportation system conference, IEEE, pp 496–501

    Google Scholar 

  • Thrun S, Montemerlo M, Dahlkamp H, Stavens D, Aron A, Diebel J, Fong P, Gale J, Halpenny M, Hoffmann G, Lau K, Oakley C, Palatucci M, Pratt V, Stang P, Strohband S, Dupont C, Jendrossek L-E, Koelen C, Markey C, Rummel C, Niekerk Jv, Jensen E, Alessandrini P, Bradski G, Davies B, Ettinger S, Kaehler A, Nefian A, Mahoney P (2006) Stanley: the robot that won the DARPA Grand Challenge. J Field Robot 23(9):661–692

    Google Scholar 

  • Tsugawa S (1993) Vision-based vehicles in Japan: the machine vision systems and driving control systems. In: IEEE international symposium on industrial electronics. Conference proceedings, ISIE’93 – Budapest, pp 278–285

    Google Scholar 

  • Tsugawa S (1994) Vision-based vehicles in Japan: machine vision systems and driving control systems. IEEE Trans Ind Electron 41(32):398–405

    Article  Google Scholar 

  • Ulbrich S, Maurer M (2013) Probabilistic online POMDP decision making for lane changes in fully automated driving. In: Intelligent transportation systems, IEEE, pp 2063–2067

    Google Scholar 

  • Ulmer B (1992) VITA-an autonomous road vehicle (ARV) for collision avoidance in traffic. In: Intelligent vehicles symposium, IEEE, pp 36–41

    Google Scholar 

  • Ulmer B (1994) VITA II-active collision avoidance in real traffic. In: Intelligent vehicles symposium, IEEE, pp 1–6

    Google Scholar 

  • Urmson C, Anhalt J, Bagnell D, Baker C, Bittner R, Clark MN, Dolan J, Duggins D, Galatali T, Geyer C, Gittleman M, Harbaugh S, Hebert M, Howard TM, Kolski S, Kelly A, Likhachev M, McNaughton M, Miller N, Peterson K, Pilnick B, Rajkumar R, Rybski P, Salesky B, Seo Y-W, Singh S, Snider J, Stentz A, Whittaker WR, Wolkowicki Z, Ziglar J, Bae H, Brown T, Demitrish D, Litkouhi B, Nickolaou J, Sadekar V, Zhang W, Struble J, Taylor M, Darms M, Ferguson D (2008) Autonomous driving in urban environments: Boss and the Urban Challenge. J Field Robot 25(8):425–466

    Article  Google Scholar 

  • Visintainer F, Darin M (2008) Final requirements and strategies for map feedback/Ertico. Forschungsbericht, D2.2

    Google Scholar 

  • Wachenfeld W, Winner H, Gerdes C, Lenz B, Maurer M, Beiker S, Fraedrich E, Winkle T (2015) Use cases for autonomous driving. In: Autonomous driving – technical, legal and social aspects. Springer, Berlin/Heidelberg

    Google Scholar 

  • Wei J, Dolan JM, Litkouhi B (2010) A prediction- and cost function-based algorithm for robust autonomous freeway driving. In: 2010 I.E. intelligent vehicles symposium, IEEE, pp 512–517

    Google Scholar 

  • Wei J, Dolan JM, Snider JM, Litkouhi B (2011) A point-based MDP for robust single-lane autonomous driving behavior under uncertainties. In: International conference on robotics and automation, IEEE, pp 2586–2592

    Google Scholar 

  • Werling M, Ziegler J, Kammel S, Thrun S (2010) Optimal trajectory generation for dynamic street scenarios in a frenèt frame. In: International conference on robotics and automation, IEEE, pp 987–993

    Google Scholar 

  • Wille JM (2012) Manöverübergreifende autonome Fahrzeugführung in innerstädtischen Szenarien am Beispiel des Stadtpilotprojekts (Maneuver-comprehensive autonomous vehicle guidance in urban scenarios exemplified by the Stadtpilot-project). Dissertation, Technische Universität Braunschweig

    Google Scholar 

  • Winkle T (2015a) Safety benefits of automated vehicles: extended findings from accident research for development, validation and testing. In: Maurer M, Gerdes C, Lenz B, Winner H (eds) Autonomous driving – technical, legal and social aspects. Springer, Berlin/Heidelberg

    Google Scholar 

  • Winkle T (2015b) Development and approval of automated vehicles: considerations of technical, legal and economic risks. In: Maurer M, Gerdes C, Lenz B, Winner H (eds) Autonomous driving – technical legal and social aspects. Springer, Berlin/Heidelberg

    Google Scholar 

  • Zapp A (1988) Automatische Straßenfahrzeugführung durch Rechnersehen (Automated road vehicle guidance with computer vision). Dissertation, Universität der Bundeswehr München

    Google Scholar 

  • Zhang W-B, Parsons RE, West T (1990) An intelligent roadway reference system for vehicle lateral guidance/control. In: American control conference, pp 281–286

    Google Scholar 

  • Ziegler J, Bender P, Lategahn H, Schreiber M, Strauß T, Stiller C (2014) Kartengestütztes automatisiertes Fahren auf der Bertha-Benz-Route von Mannheim nach Pforzheim (Map-supported automated driving on the Bertha-Benz-Route from Mannheim to Pforzheim). In: Workshop Fahrerassistenzsysteme Walting

    Google Scholar 

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Correspondence to Richard Matthaei .

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Appendix: Questionnaire on “Autonomous Vehicles”

Appendix: Questionnaire on “Autonomous Vehicles”

1.1 Project Organization and Objective

This section addresses general and organizational aspects of your project.

  1. 1.

    What is the name of the project?

  2. 2.

    With which universities and/or industrial partners do you cooperate in this project?

  3. 3.

    When was the project started/how long have you been working on the project now?

  4. 4.

    What is the objective of the project?

  5. 5.

    What are the assumptions, constraints, and restrictions in the project?

  6. 6.

    Was the system demonstrated on public roads? If so, which capabilities were publicly demonstrated in which domains?

1.2 Perception

This section addresses the perception and localization of your system as well as its environment representation.

  1. 1.

    Please describe briefly the perception architecture of the system.

  2. 2.

    What sensor technologies (and which devices) are used?

  3. 3.

    How are dynamic objects perceived and represented by the system? What kind of dynamic objects are perceived?

  4. 4.

    How are static objects and road boundaries perceived and represented by the system?

  5. 5.

    Is the system capable of perceiving the state of traffic lights? How is this done?

  6. 6.

    What kind of traffic signs are perceived by the system?

  7. 7.

    Does your system perceive pedestrians and cyclists? If so, under which conditions and by the use of which sensors and algorithms?

  8. 8.

    How are lanes perceived? Which conditions must be fulfilled by a lane?

  9. 9.

    What are the requirements for perceiving lateral traffic at intersections? Does the system identify the right of way?

  10. 10.

    Is the system capable of determining the topology of intersections from perceived data? How is this done?

  11. 11.

    Which intentions of other road users can be perceived by the system? Which conditions must be fulfilled therefore?

  12. 12.

    How are the overall and the current capabilities of the system represented and monitored? How do the current capabilities determine the behavior of the system?

  13. 13.

    How is the relative position of the vehicle with respect to the lane perceived? Which conditions (e.g., lane markings, geometric models) must be fulfilled therefore?

  14. 14.

    Is information from digital maps used? How accurate are these maps?

  15. 15.

    Is the localization in digital maps solely based on satellite-based positioning or are other sensors used additionally? If so, which additional sensors and algorithms are used for localization?

  16. 16.

    Is the system capable of communicating with other road users or the road infrastructure (i.e., Car2x technologies)?

  17. 17.

    Are perceived features (e.g., objects, lanes, road boundaries) combined into a generic environment model? If so, please give a brief description of this model.

1.3 Function

This section addresses functions and maneuvers implemented in your test vehicle.

  1. 1.

    Is the system capable of autonomously executing lane-change maneuvers without any support of the driver? How is this maneuver implemented? In which domains (highway, rural roads, and urban environment) can it be executed?

  2. 2.

    How does the system react to the state of traffic lights?

  3. 3.

    What kind of turn maneuvers are implemented? Is the system capable of executing a turning maneuver into moving traffic?

  4. 4.

    How does the system deal with intersections without traffic lights?

  5. 5.

    Is the system capable of merging into traffic on rural roads and/or highways? How is this maneuver implemented?

  6. 6.

    What kind of emergency situations are considered by the system (e.g., emergency braking of the vehicle in front, pedestrian crossing the street)? How does the system react to these situations?

  7. 7.

    What concepts are implemented for keeping the vehicle in the current lane?

  8. 8.

    Are there any implicit and/or explicit mechanisms for cooperating with other road users?

  9. 9.

    How is the mission planning implemented? Is it done online or is the mission plan precomputed?

  10. 10.

    How does the system react to interventions of the driver?

  11. 11.

    Are there any further, not yet addressed, capabilities or maneuvers implemented?

  12. 12.

    Is the system capable of traversing from one domain to another (e.g., exiting the highway onto an urban street)? Which transitions are possible?

1.4 Safety Concept

  1. 1.

    Please describe briefly the safety concept for driving on public roads.

  2. 2.

    How do you verify that the functions discussed above work as expected? What is the test procedure?

  3. 3.

    How does the system react to the loss of one or more components or capabilities? What is the degradation concept?

1.5 System Architecture

Please describe the architecture of the system (functional, hardware, software) and the main design criteria.

1.6 Something Is Missing?

If there are any further system characteristics or features worth mentioning, please note them here.

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© 2016 Springer International Publishing Switzerland

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Matthaei, R. et al. (2016). Autonomous Driving. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds) Handbook of Driver Assistance Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-12352-3_61

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