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Runtime Monitoring of Automated Driving Systems
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Dependable Software Engineering)
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

It is the period of the World's history, where the technological progress reached a level that enables the first steps towards the development of vehicles with automated driving capabilities. The swift response from the significant portion of the industry resulted in a race, the final line set at the introduction of vehicles with full automated driving capabilities.

Vehicles with automated driving capabilities target making driving safer, more comfortable, and economically more efficient by assisting the driver or by taking responsibilities for different driving tasks. While vehicles with assistance and partial automation capabilities are already in series production, the ultimate goal is in the introduction of vehicles with full automated driving capabilities. Reaching this level of automation will require shifting all responsibilities, including the responsibility for the overall vehicle safety, from the human to the computer-based system responsible for the automated driving functionality (i.e., the Automated Driving System (ADS)). Such a shift makes the ADS highly safe-critical, requiring a safety level comparable to an aircraft system.

It is paramount to understand that ensuring such a level of safety is a complex interdisciplinary challenge. Traditional approaches for ensuring safety require the use of fault-tolerance techniques that are unproven when it comes to the automated driving domain. Moreover, existing safety assurance methods (e.g., ISO 26262) suffer from requirements incompleteness in the automated driving context. The use of artificial intelligence-based components in the ADS further complicate the matter due to their non-deterministic behavior. At present, there is no single straightforward solution for these challenges. Instead, the consensus of cross-domain experts is to use a set of complementary safety methods that together are sufficient to ensure the required level of safety.

In the context of that, runtime monitors that verify the safe operation of the ADS during execution, are a promising complementary approach for ensuring safety. However, to develop a runtime monitoring solution for ADS, one has to handle a wide range of challenges. On a conceptual level, the complex and opaque technology used in ADS often make researchers ask the question ``how should ADS be verified in order to judge it is operating safely?".

Once the initial Runtime Verification (RV) concept is developed, researchers and practitioners have to deal with research and engineering challenges encountered during the realization of the RV approaches into an actual runtime monitoring solution for ADS. These challenges range from, estimating different safety parameters of the runtime monitors, finding solutions for different technical problems, to meeting scalability and efficiency requirements.

The focus of this thesis is to propose novel runtime monitoring solutions for verifying the safe operation of ADS. This encompasses (i) defining novel RV approaches explicitly tailored for automated driving, and (ii) developing concepts, methods, and architectures for realizing the RV approaches into an actual runtime monitoring solution for ADS. Contributions to the former include defining two runtime RV approaches, namely the Computer Vision Monitor (CVM) and the Safe Driving Envelope Verification. Contributions to the latter include (i) estimating the sufficient diagnostic test interval of the runtime verification approaches (in particular the CVM), (ii) addressing the out-of-sequence measurement problem in sensor fusion-based ADS, and (iii) developing an architectural solution for improving the scalability and efficiency of the runtime monitoring solution.

Place, publisher, year, edition, pages
Västerås: Mälardalen University , 2019.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 281
Keywords [en]
Runtime Monitoring, Automated Driving Systems
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-45068ISBN: 978-91-7485-434-3 (print)OAI: oai:DiVA.org:mdh-45068DiVA, id: diva2:1345993
Presentation
2019-10-17, Delta, Mälardalens högskola, Västerås, 13:15 (English)
Opponent
Supervisors
Projects
RetNetAvailable from: 2019-08-28 Created: 2019-08-26 Last updated: 2019-09-17Bibliographically approved
List of papers
1. Improving Intelligent Vehicle Dependability By Means of Infrastructure-Induced Tests
Open this publication in new window or tab >>Improving Intelligent Vehicle Dependability By Means of Infrastructure-Induced Tests
2015 (English)In: Proceedings - 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2015, 2015, p. 147-152Conference paper, Published paper (Refereed)
Abstract [en]

Advanced driver assistance systems (ADAS) take over more and more driving responsibilities from the human operator and, therefore, evolve into safety-critical systems. Thus, the dependability of such systems is of up-most importance. While upcoming automobiles themselves will implement fault-tolerance and robustness mechanisms, it can be beneficial to also take infrastructure measures into account when assessing the overall vehicle dependability. In this paper we discuss an example of an infrastructure measure that targets to improve the dependability of an on-board computer vision system. Based on this example we outline a cyber-physical systems (CPS) architecture for intelligent vehicles and address open research directions.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-29632 (URN)10.1109/DSN-W.2015.14 (DOI)2-s2.0-84957714187 (Scopus ID)978-0-7695-5533-1 (ISBN)
Conference
45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2015; Rio de Janeiro; Brazil; 22 June 2015 through 25 June 2015; Category numberE5533; Code 117672
Projects
RetNet - The European Industrial Doctorate Programme on Future Real-Time Networks
Available from: 2015-12-10 Created: 2015-11-26 Last updated: 2019-08-26Bibliographically approved
2. System Architecture and Application-Specific Verification Method for Fault-Tolerant Automated Driving System
Open this publication in new window or tab >>System Architecture and Application-Specific Verification Method for Fault-Tolerant Automated Driving System
2019 (English)In: IEEE Intelligent Vehicles Symposium workshops IEEE IVS 2019 WS, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Automated vehicles come with promises for higher comfort and safety compared to the standard human-driven vehicles. Various demonstrator vehicles with fully automated driving capabilities have been already presented with success. Yet, there is a large number of technical challenges to be solved until the safety levels comply with those required from safety standards, and most importantly with those for public acceptance. In this paper, we introduce the technical challenges resulting from the need for fault-tolerant capabilities of automated vehicles with no fallback-ready drivers. We then propose a concrete solution to these challenges. This includes a fault-tolerant architecture for automated driving systems. Also, the safety co-pilot, that is a safety mechanism that ensures the coordinated operation of two or more redundant ADS, by means of novel application-specific verification methods. We conclude our work with experimental proof of concept results of the proposed solution.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-43943 (URN)
Conference
IEEE Intelligent Vehicles Symposium workshops IEEE IVS 2019 WS, 09 Jun 2019, Paris, France
Projects
RetNet - The European Industrial Doctorate Programme on Future Real-Time Networks
Available from: 2019-06-20 Created: 2019-06-20 Last updated: 2019-08-26Bibliographically approved
3. Improving Dependability of Vision-Based Advanced Driver Assistance Systems Using Navigation Data and Checkpoint Recognition
Open this publication in new window or tab >>Improving Dependability of Vision-Based Advanced Driver Assistance Systems Using Navigation Data and Checkpoint Recognition
Show others...
2015 (English)In: COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2015, 2015, p. 59-73Conference paper, Published paper (Refereed)
Abstract [en]

Advanced Driver Assistance Systems (ADAS), like adaptive cruise control, collision avoidance, and, ultimately, autonomous driving are increasingly evolving into safety-critical systems. These ADAS frequently rely on proper function of Computer-Vision Systems (CVS), which is hard to assess in a timely manner, due to their sensitivity to the variety of illumination conditions (e.g. weather conditions, sun brightness). On the other hand, self-awareness information is available in the vehicle, such as maps and localization data (e.g. GPS).

This paper studies how the combination of diverse environmental information can improve the overall vision-based ADAS reliability. To this extent we present a concept of a Computer-Vision Monitor (CVM) that identifies predefined landmarks in the vehicles surrounding, based on digital maps and localization data, and that checks whether the CVS correctly identifies said landmarks. We formalize and assess the reliability improvement of our solution by means of a fault-tree analysis.

Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9337
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-29630 (URN)10.1007/978-3-319-24255-2_6 (DOI)000366204300006 ()2-s2.0-84969752583 (Scopus ID)978-3-319-24254-5 (ISBN)
Conference
International Conference on Computer Safety, Reliability & Security SAFECOMP 2015, 23-25 Sep 2015, Delft, Netherlands
Projects
RetNet - The European Industrial Doctorate Programme on Future Real-Time Networks
Available from: 2015-12-10 Created: 2015-11-26 Last updated: 2019-08-26Bibliographically approved
4. Deterministic Ethernet: Addressing the Challenges of Asynchronous Sensing in Sensor Fusion Systems
Open this publication in new window or tab >>Deterministic Ethernet: Addressing the Challenges of Asynchronous Sensing in Sensor Fusion Systems
2017 (English)In: 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, DSN-W 2017; Denver; United States; 26 June 2017 through 29 June 2017, 2017, p. 22-28, article id 8023693Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we study the cause of out-of-sequence measurements (OOSM) and their effect on Kalman filter based multi-sensor fusion systems. We explore the current available solutions for handling of OOSM and pinpoint how the absence of precise measurement timestamps does not allow the correct chronological order of sensor measurements. The processing of such, out-of-order measurements, leads to negative-time measurement updates in the sensor fusion process, which in turn leads to a wrong representation of the environment.Furthermore, we present methods for achieving precise measurement timestamps. We explore the suitability of set of communication standards for improving the timestamp precision. In particular we focus on IEEE 802.1AS, IEEE 802.1Qav, Qbv and SAE AS6802 standards that enable deterministic communication over IEEE802.3 standard Ethernet. We present theoretical performance studies and comparison of the said communication standards.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-36084 (URN)10.1109/DSN-W.2017.44 (DOI)000425860600005 ()2-s2.0-85031711590 (Scopus ID)978-1-5386-2272-8 (ISBN)
Conference
The 47th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2017), 26-29 June 2017, Denver, Colorado, USA
Available from: 2017-07-10 Created: 2017-07-10 Last updated: 2019-08-26Bibliographically approved

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Available from 2019-09-26 08:00

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