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Reference Architectures for Highly Automated Driving
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems.ORCID iD: 0000-0002-8629-0402
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. , xviii, 50 p.
Series
TRITA-MMK, ISSN 1400-1179 ; 2105:09
Keyword [en]
Autonomous driving, E/E Architecture, Systems Engineering
National Category
Embedded Systems
Research subject
Machine Design
Identifiers
URN: urn:nbn:se:kth:diva-179306ISBN: 978-91-7595-757-9 (print)OAI: oai:DiVA.org:kth-179306DiVA: diva2:882479
Public defence
2016-01-22, Kollegiesalen, Brinellvägen 8, Stockholm, 09:00 (English)
Opponent
Supervisors
Note

QC 20151216

Available from: 2015-12-16 Created: 2015-12-15 Last updated: 2016-01-25Bibliographically approved
List of papers
1. Architecture challenges for intelligent autonomous machines: An industrial perspective
Open this publication in new window or tab >>Architecture challenges for intelligent autonomous machines: An industrial perspective
2016 (English)In: 13th International conference on Intelligent Autonomous Systems (IAS-13), Springer, 2016, Vol. 302, 1669-1681 p.Conference paper, Published paper (Refereed)
Abstract [en]

Machines are displaying a trend of increasing autonomy. This has a far reaching impact on the architectures of the embedded systems within the machine. The impact needs to be clearly understood and the main obstacles to autonomy need to be identified. The obstacles, especially from an industrial perspective, are not just technological butalso relate to system aspects like certification, development processes and product safety. In this paper, we identify and discuss some of the main obstacles to autonomy from the viewpoint of technical specialists working on advanced industrial product development. The identified obstacles cover topics like world modeling, user interaction, complexity and system safety.

Place, publisher, year, edition, pages
Springer, 2016
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 302
Keyword
Autonomy, Architecture, Embedded Systems
National Category
Embedded Systems
Research subject
Vehicle and Maritime Engineering
Identifiers
urn:nbn:se:kth:diva-152534 (URN)10.1007/978-3-319-08338-4_120 (DOI)000377956900120 ()2-s2.0-84945905859 (Scopus ID)978-331908337-7 (ISBN)
Conference
13th International conference on Intelligent Autonomous Systems (IAS-13),Padova 15-19 July 2014
Funder
VINNOVA
Note

QC 20140930

Available from: 2014-09-26 Created: 2014-09-26 Last updated: 2016-07-18Bibliographically approved
2. The development of a cooperative heavy-duty vehicle for the GCDC 2011: Team Scoop
Open this publication in new window or tab >>The development of a cooperative heavy-duty vehicle for the GCDC 2011: Team Scoop
Show others...
2012 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 13, no 3, 1033-1049 p.Article in journal (Refereed) Published
Abstract [en]

The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios.

Place, publisher, year, edition, pages
IEEE Press, 2012
Keyword
Communication networks, cooperative systems, intelligent vehicles, motion control, software architecture, state estimation
National Category
Control Engineering Embedded Systems Communication Systems Signal Processing
Identifiers
urn:nbn:se:kth:diva-102846 (URN)10.1109/TITS.2012.2204876 (DOI)000312805000006 ()
Funder
TrenOp, Transport Research Environment with Novel PerspectivesICT - The Next Generation
Note

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

QC20120927

Available from: 2012-09-27 Created: 2012-09-26 Last updated: 2017-12-07Bibliographically approved
3. A reference architecture for cooperative driving
Open this publication in new window or tab >>A reference architecture for cooperative driving
2013 (English)In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 59, no 10: Part C, 1095-1112 p.Article in journal (Refereed) Published
Abstract [en]

Cooperative driving systems enable vehicles to adapt their motion to the surrounding traffic situation by utilizing information communicated by other vehicles and infrastructure in the vicinity. How should these systems be designed and integrated into the modern automobile? What are the needed functions, key architectural elements and their relationships? We created a reference architecture that systematically answers these questions and validated it in real world usage scenarios. Key findings concern required services and enabling them via the architecture. We present the reference architecture and discuss how it can influence the design and implementation of such features in automotive systems.

Keyword
Automotive embedded application, Autonomous systems, Cooperative driving, Intelligent transportation systems, Reference architecture
National Category
Embedded Systems Computer Systems Control Engineering
Identifiers
urn:nbn:se:kth:diva-120592 (URN)10.1016/j.sysarc.2013.05.014 (DOI)000330090400007 ()2-s2.0-84888310995 (Scopus ID)
Projects
DFEA2020
Note

Updated from "Submitted" to "Published". QC 20140120

Available from: 2013-04-12 Created: 2013-04-12 Last updated: 2017-12-06Bibliographically approved
4. A Functional Reference Architecture for Autonomous Driving
Open this publication in new window or tab >>A Functional Reference Architecture for Autonomous Driving
2016 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 73, 136-150 p.Article in journal (Refereed) Published
Abstract [en]

Context

As autonomous driving technology matures towards series production, it is necessary to take a deeper look at various aspects of electrical/electronic (E/E) architectures for autonomous driving.

Objective

This paper describes a functional architecture for autonomous driving, along with various considerations that influence such an architecture. The functionality is described at the logical level, without dependence on specific implementation technologies.

Method

Engineering design has been used as the research method, which focuses on creating solutions intended for practical application. The architecture has been refined and applied over a five year period to the construction of protoype autonomous vehicles in three different categories, with both academic and industrial stakeholders.

Results

The architectural components are divided into categories pertaining to (i) perception, (ii) decision and control, and (iii) vehicle platform manipulation. The architecture itself is divided into two layers comprising the vehicle platform and a cognitive driving intelligence. The distribution of components among the architectural layers considers two extremes: one where the vehicle platform is as "dumb" as possible, and the other, where the vehicle platform can be treated as an autonomous system with limited intelligence. We recommend a clean split between the driving intelligence and the vehicle platform. The architecture description includes identification of stakeholder concerns, which are grouped under the business and engineering categories. A comparison with similar architectures is also made, wherein we claim that the presence of explicit components for world modeling, semantic understanding, and vehicle platform abstraction seem unique to our architecture.

Conclusion

The concluding discussion examines the influences of implementation technologies on functional architectures and how an architecture is affected when a human driver is replaced by a computer. The discussion also proposes that reduction and acceleration of testing, verification, and validation processes is the key to incorporating continuous deployment processes.

Place, publisher, year, edition, pages
Elsevier, 2016
National Category
Embedded Systems
Identifiers
urn:nbn:se:kth:diva-179222 (URN)10.1016/j.infsof.2015.12.008 (DOI)000373537400011 ()2-s2.0-84954271784 (Scopus ID)
Note

QC 20160504

Available from: 2015-12-14 Created: 2015-12-14 Last updated: 2017-12-01Bibliographically approved
5. Systems Engineering and Architecting for Intelligent Autonomous Systems
Open this publication in new window or tab >>Systems Engineering and Architecting for Intelligent Autonomous Systems
2016 (English)Manuscript (preprint) (Other academic)
Abstract [en]

This chapter provides insights into architecture and systems engineering for autonomous driving systems, through a set of complementary perspectives. For practitioners, a short term perspective uses the state of the art to define a three layered functional architecture for autonomous driving, consisting of a vehicle platform, a cognitive driving intelligence, and off-board supervisory and monitoring services. The architecture is placed within a broader context of model based systems engineering (MBSE), for which we define four classes of models: Concept of Operations, Logical Architecture, Application Software Components, and Platform Components. These classes aid an immediate or subsequent MBSE methodology for concrete projects. Also for concrete projects, we propose an implementation setup and technologies that combine simulation and implementation for rapid testing of autonomous driving functionality in physical and virtual environments. Future evolution of autonomous driving systems is explored with a long term perspective looking at stronger concepts of autonomy like machine consciousness and self-awareness. Contrasting these concepts with current engineering practices shows that scaling to more complex systems may require incorporating elements of so-called \emph{constructivist} architectures. The impact of autonomy on systems engineering is expected to be mainly around testing and verification, while implementations shall continue experiencing an influx of technologies from non-automotive domains.

National Category
Embedded Systems
Identifiers
urn:nbn:se:kth:diva-179225 (URN)
Note

QS 2015

Available from: 2015-12-14 Created: 2015-12-14 Last updated: 2015-12-16Bibliographically approved
6. A Functional Brake Architecture for Autonomous Heavy Commercial Vehicles
Open this publication in new window or tab >>A Functional Brake Architecture for Autonomous Heavy Commercial Vehicles
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Heavy commercial vehicles constitute the dominant form of inland freight transport. There is a strong interest in making such vehicles autonomous (self-­‐driving), in order to improve safety and the economics of fleet operation. Autonomy concerns affect a number of key systems within the vehicle. One such key system is brakes, which need to remain continuously available throughout vehicle operation. This paper presents a fail-­‐operational functional brake architecture for autonomous heavy commercial vehicles. The architecture is based on a reconfiguration of the existing brake systems in a typical vehicle, in order to attain dynamic, diversified redundancy along with desired brake performance. Specifically, the parking brake is modified to act as a secondary brake with capabilities for monitoring and intervention of the primary brake system. A basic fault tree analysis of the architecture indicates absence of single points of failure, and a reliability analysis shows that it is reasonable to expect about an order of magnitude improvement in overall system reliability.

National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-179228 (URN)
Note

QS 2015

Available from: 2015-12-14 Created: 2015-12-14 Last updated: 2015-12-16Bibliographically approved
7. Architecture support for automobile autonomy:A state of the art survey
Open this publication in new window or tab >>Architecture support for automobile autonomy:A state of the art survey
2012 (English)Report (Other academic)
Publisher
28 p.
Series
TRITA-MMK, ISSN 1400-1179 ; 12:12
National Category
Embedded Systems
Identifiers
urn:nbn:se:kth:diva-179302 (URN)KTH/MMK/R--12/12--SE (ISRN)
Note

QC 20151215

Available from: 2015-12-15 Created: 2015-12-15 Last updated: 2015-12-16Bibliographically approved

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
  • rtf