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Intelligent Vehicles

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Springer Handbook of Robotics

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Abstract

This chapter describes the emerging robotics application field of intelligent vehicles – motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows. Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology. Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure. Section 62.3 describes the challenges and solutions associated with road scene understanding – a key capability for all intelligent vehicles. Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance. Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment. Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed. The chapter is concluded in Sect. 62.7 with a discussion of future prospects, while Sect. 62.8 provides references to further reading and additional resources.

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Abbreviations

3-D:

three-dimensional

ABRT:

automated bus rapid transit

ACC:

adaptive cruise control

ADAS:

advanced driving assistance system

AHS:

advanced highway system

automated highway system

AIST:

Institute of Advanced Industrial Science and Technology

BRT:

bus rapid transit

CACC:

cooperative adaptive cruise control

CALM:

communication access for land mobiles

CD:

compact disc

CIE:

International Commission on Illumination

CVIS:

cooperative vehicle infrastructure system

DARPA:

Defense Advanced Research Projects Agency

DGPS:

differential global positioning system

DSRC:

dedicated short-range communications

ECG:

electrocardiogram

GCDC:

Grand Cooperative Driving Challenge

GID:

geometric intersection data

GLS:

global navigation satellite system

GPRS:

general packet radio service

GPS:

global positioning system

HTAS:

high tech automotive system

IETF:

internet engineering task force

IMTS:

intelligent multimode transit system

IMU:

inertial measurement unit

IP:

internet protocol

IST:

Information Society Technologies

LED:

light-emitting diode

MEL:

Mechanical Engineering Laboratory

MHT:

multihypothesis tracking

NEMO:

network mobility

OBU:

on board unit

OECD:

Organization for Economic Cooperation and Development

PC:

personal computer

RALPH:

rapidly adapting lane position handler

RFID:

radio frequency identification

RSU:

road side unit

SLAM:

simultaneous localization and mapping

SMS:

short message service

SPaT:

signal phase and timing

TRC:

Transportation Research Center

UBM:

Universität der Bundeswehr Munich

WAVE:

wireless access in vehicular environments

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Authors and Affiliations

  1. Department of Information Technology, University of Parma, Viale delle Scienze 181A, 43100, Parma, Italy

    Alberto Broggi

  2. DST Group Headquarters, Department of Defence, 72-2-03, 24 Scherger Drive, ACT 2609, Canberra, Australia

    Alex Zelinsky

  3. Department of Electrical and Computer Engineering, Ohio State University, 2015 Neil Avenue, OH 43210, Columbus, USA

    Ümit Özgüner

  4. INRIA Grenoble Rhône-Alpes, 655 Avenue de l’Europe, 38334, Saint Ismier, France

    Christian Laugier

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  4. Christian Laugier
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Corresponding author

Correspondence to Alberto Broggi .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy

    Bruno Siciliano

  2. Department of Computer Sciences, Artificial Intelligence Laboratory, Stanford University, 450 Serra Mall, CA 94305, Stanford, USA

    Oussama Khatib

Video-References

Video-References

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PROUD2013 – Inside VisLab’s driverless car available from http://handbookofrobotics.org/view-chapter/62/videodetails/178

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VIAC: The VisLab Intercontinental Autonomous Challenge available from http://handbookofrobotics.org/view-chapter/62/videodetails/179

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Motion prediction using the Bayesian occupancy filter approach (Inria) available from http://handbookofrobotics.org/view-chapter/62/videodetails/420

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Cybercars and the city of tomorrow available from http://handbookofrobotics.org/view-chapter/62/videodetails/429

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Bayesian embedded perception in Inria/Toyota instrumented platform available from http://handbookofrobotics.org/view-chapter/62/videodetails/566

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Inria/Ligier automated parallel parking demo in an open parking area available from http://handbookofrobotics.org/view-chapter/62/videodetails/567

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Collision avoidance at blind intersections using V2V and intention / expectation approach (Inria & Renault) available from http://handbookofrobotics.org/view-chapter/62/videodetails/822

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Lane tracking available from http://handbookofrobotics.org/view-chapter/62/videodetails/836

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Speed sign detection available from http://handbookofrobotics.org/view-chapter/62/videodetails/838

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Pedestrian detection available from http://handbookofrobotics.org/view-chapter/62/videodetails/839

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Driver fatigue and inattention available from http://handbookofrobotics.org/view-chapter/62/videodetails/839

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© 2016 Springer-Verlag Berlin Heidelberg

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Broggi, A., Zelinsky, A., Özgüner, Ü., Laugier, C. (2016). Intelligent Vehicles. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-32552-1_62

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  • DOI: https://doi.org/10.1007/978-3-319-32552-1_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32550-7

  • Online ISBN: 978-3-319-32552-1

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