Operational design domain

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Operational design domain (ODD) is a term for a particular operating context for an automated system, often used in the field of autonomous vehicles. The context is defined by a set of conditions, including environmental, geographical, time of day, and other conditions. For vehicles, traffic and roadway characteristics are included. Manufacturers use ODD to indicate where/how their product operates safely. A given system may operate differently according to the immediate ODD. [1]

Contents

The concept presumes that automated systems have limitations. [2] Relating system function to the ODDs it supports is important for developers and regulators to establish and communicate safe operating conditions. Systems should operate within those limitations. Some systems recognize the ODD and modify their behavior accordingly. For example, an autonomous car might recognize that traffic is heavy and disable its automated lane change feature. [2]

ODD is used for cars, for ships, [3] trains, [4] agricultural robots, [5] and other robots.

Definitions

Various regulators have offered definitions of related terms:

DefinitionSource
"operating conditions under which a given driving automation system ... or feature thereof is specifically designed to function"ISO/TS 14812:2022(en), 3.7.3.2 [6]
"operating conditions under which a given automated driving system ... or feature thereof is specifically designed to function, including, but not limited to, environmental, geographical, and time-of-day restrictions, and/or the requisite presence or absence of certain traffic or roadway characteristics"ISO/TR 4804:2020(en), 3.37 [7]
"operating conditions under which a given driving automation system or feature thereof is specifically designed to function, including, but not limited to, environmental, geographical, and time-of-day restrictions, and/or the requisite presence or absence of certain traffic or roadway characteristics"ISO 34501:2022(en), 3.26 [8]
"specific conditions under which a given driving automation system is designed to function"ISO 21448:2022(en), 3.21 [9]
"operating conditions under which a given driving automation system or feature thereof is specifically designed to function"BSI PAS 1883 [10]
"set of environments and situations the item is to operate within"ANSI/UL 4600 [11]
"environmental, geographic, time-of-day, traffic, infrastructure, weather and other conditions under which an automated driving system is specifically designed to function"Global Forum for Road Traffic Safety (WP.1) resolution on the deployment of highly and fully automated vehicles in road traffic [12]
"For the assessment of the vehicle safety, the vehicle manufacturers should document the [ODD] available on their vehicles and the functionality of the vehicle within the prescribed [ODD]. The [ODD] should describe the specific conditions under which the automated vehicle is intended to drive in the automated mode. The [ODD] should include the following information at a minimum: roadway types; geographic area; speed range; environmental conditions (weather as well as day/night time); and other domain constraints."Revised Framework document on automated/autonomous vehicles (WP.29) [13]
An "automated lane keeping system defines the specific operating conditions (e.g. environmental, geographic, time-of-day, traffic, infrastructure, speed range, weather and other conditions) within the boundaries fixed by this regulation under which the automated lane keeping system is designed to operate without any intervention by the driver."UN Regulation No 157 – Uniform provisions concerning the approval of vehicles with regards to Automated Lane Keeping Systems [2021/389] [14]
An ODD is defined in terms of physical infrastructure, operational constraints, objects, connectivity, environmental conditions, and zones.

Physical infrastructure includes roadway types, surfaces, edges and geometry. Operational constraints include speed limits and traffic conditions. Environmental conditions include weather, illumination, etc. Zones include regions, states, school areas, and construction sites.

US Department of Transportation report [15]

Examples

In 2022, Mercedes-Benz announced a product with an ODD of Level 3 autonomous driving at 130 km/h. [16]

See also

Related Research Articles

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<span class="mw-page-title-main">Advanced driver-assistance system</span> Electronic systems that help a vehicle driver while driving or parking

An advanced driver-assistance system (ADAS) includes technologies that assist drivers with the safe operation of a vehicle. Through a human-machine interface, ADAS increases car and road safety. ADAS uses automated technology, such as sensors and cameras, to detect nearby obstacles or driver errors, and respond accordingly. ADAS can enable various levels of autonomous driving.

Automatic train operation (ATO) is a method of operating trains automatically where the driver is not required or required for supervision at most. Alternatively, ATO can be defined as a subsystem within the automatic train control, which performs any or all of functions like programmed stopping, speed adjusting, door operation, and similar otherwise assigned to the train operator.

<span class="mw-page-title-main">Vienna Convention on Road Traffic</span> International treaty

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<span class="mw-page-title-main">Vehicular automation</span> Automation for various purposes of vehicles

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<span class="mw-page-title-main">History of self-driving cars</span> Overview of the history of self-driving cars

Experiments have been conducted on self-driving cars since 1939; promising trials took place in the 1950s and work has proceeded since then. The first self-sufficient and truly autonomous cars appeared in the 1980s, with Carnegie Mellon University's Navlab and ALV projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's Eureka Prometheus Project in 1987. Since then, numerous major companies and research organizations have developed working autonomous vehicles including Mercedes-Benz, General Motors, Continental Automotive Systems, Autoliv Inc., Bosch, Nissan, Toyota, Audi, Volvo, Vislab from University of Parma, Oxford University and Google. In July 2013, Vislab demonstrated BRAiVE, a vehicle that moved autonomously on a mixed traffic route open to public traffic.

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<span class="mw-page-title-main">Self-driving truck</span> Type of autonomous vehicle

A self-driving truck, also known as an autonomous truck or robo-truck, is an application of self-driving technology aiming to create trucks that can operate without human input. Alongside light, medium, and heavy-duty trucks, many companies are developing self-driving technology in semi trucks to automate highway driving in the delivery process.

The impact of self-driving cars is anticipated to be wide-ranging in many areas of daily life. Self-driving cars have been the subject of significant research on their environmental, practical, and lifestyle consequences.

Automated lane keeping systems (ALKS), also described as traffic jam chauffeurs, is an autonomous driving system that doesn't require driver supervision on motorways. ALKS is an international standard set out in UN-ECE regulation 157 and amounts to Level 3 vehicle automation. It is essentially a more robust combination of adaptive cruise control (ACC) and lane centering assist (LCA). When activated, it allows the driver to do non-driving tasks until alerted otherwise.

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In the field of vehicular automation a scenario denotes a sequence of snapshots of the environment and the actions of a vehicle. Scenarios are created to represent real-world situations and are used for development, testing, and validation purposes.

References

  1. ↑ Lee, Chung Won; Nayeer, Nasif; Garcia, Danson Evan; Agrawal, Ankur; Liu, Bingbing (October 2020). "Identifying the Operational Design Domain for an Automated Driving System through Assessed Risk". 2020 IEEE Intelligent Vehicles Symposium (IV). pp. 1317–1322. doi:10.1109/IV47402.2020.9304552. ISBN   978-1-7281-6673-5. S2CID   231599295.
  2. 1 2 Erz, Jannis; Schütt, Barbara; Braun, Thilo; Guissouma, Houssem; Sax, Eric (April 2022). "Towards an Ontology That Reconciles the Operational Design Domain, Scenario-based Testing, and Automated Vehicle Architectures". 2022 IEEE International Systems Conference (SysCon). pp. 1–8. doi:10.1109/SysCon53536.2022.9773840. ISBN   978-1-6654-3992-3. S2CID   248850678.
  3. ↑ Yamada, Tomoaki; Sato, Makoto; Kuranobu, Rikiya; Watanabe, Ryo; Itoh, Hiroko; Shiokari, Megumi; Yuzui, Tomohiro (1 July 2022). "Evaluation of effectiveness of the STAMP / STPA in risk analysis of autonomous ship systems". Journal of Physics: Conference Series. 2311 (1): 012021. doi: 10.1088/1742-6596/2311/1/012021 . S2CID   251344689.
  4. ↑ Meng, Zicong; Tang, Tao; Wei, Guodong; Yuan, Lei (January 2021). "Analysis of ATO System Operation Scenarios Based on UPPAAL and the Operational Design Domain". Electronics. 10 (4): 503. doi: 10.3390/electronics10040503 . ISSN   2079-9292.
  5. ↑ Krank, Joshua (2020). "Robo-Crop: The Imminence of Autonomous Technology in Agriculture". Drake Journal of Agricultural Law. 25: 473.
  6. ↑ "3.7.3.2". ISO/TS 14812:2022, Intelligent transport systems — Vocabulary. ISO. 2022. Retrieved 11 June 2023.
  7. ↑ "3.22". ISO/TR 4804:2020, Road vehicles — Safety and cybersecurity for automated driving systems — Design, verification and validation. ISO. 2020. Retrieved 11 June 2023.
  8. ↑ "3.26". ISO 34501:2022, Road vehicles — Test scenarios for automated driving systems — Vocabulary. ISO. 2022. Retrieved 11 June 2023.
  9. ↑ "3.21". ISO 21448:2022, Road vehicles — Safety of the intended functionality. ISO. 2022. Retrieved 11 June 2023.
  10. ↑ "PAS 1883:2020" (PDF). BSI Group . Retrieved 11 June 2023.
  11. ↑ Peleska, Jan; Haxthausen, Anne E.; Lecomte, Thierry (2022). "Standardisation Considerations for Autonomous Train Control". Leveraging Applications of Formal Methods, Verification and Validation. Practice. Lecture Notes in Computer Science. Springer Nature Switzerland. 13704: 286–307. doi: 10.1007/978-3-031-19762-8_22 . ISBN   978-3-031-19761-1.
  12. ↑ "Resolution on the Deployment of Highly and Fully Automated Vehicles in Road Traffic | UNECE". unece.org. UNECE. September 2018. Retrieved 11 June 2023.
  13. ↑ "Framework Document for Automated/Autonomous Vehicles (UPDATED) | UNECE". unece.org. UNECE. February 2022. Retrieved 11 June 2023.
  14. ↑ UN Regulation No 157
  15. ↑ Thorn, Eric; Kimmel, Shawn C.; Chaka, Michelle (1 September 2018). "A Framework for Automated Driving System Testable Cases and Scenarios" . Retrieved 11 June 2023.
  16. ↑ Rocco, Nicolas La (12 August 2022). "Level-3-Fahren mit 130 km/h: Mercedes gestaltet nächste ODD für Drive Pilot aus". ComputerBase (in German). Retrieved 11 June 2023.
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