In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

Mauro Vallati; Lukáš Chrpa

doi:10.1109/ITSC57777.2023.10422348

In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

Mauro Vallati, Lukáš Chrpa

Czech Technical University in Prague

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real world applications.

This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated.

Original language	English
Title of host publication	Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems
Subtitle of host publication	ITSC 2023
Publisher	IEEE
Pages	4913-4918
Number of pages	6
ISBN (Electronic)	9798350399462
ISBN (Print)	9798350399479
DOIs	https://doi.org/10.1109/ITSC57777.2023.10422348
Publication status	Published - 13 Feb 2024
Event	26th IEEE International Conference on Intelligent Transportation Systems - Bilbao, Spain Duration: 24 Sept 2023 → 28 Sept 2023 Conference number: 26 https://2023.ieee-itsc.org/

Publication series

Name	International Conference on Intelligent Transportation Systems (ITSC)
Publisher	IEEE
ISSN (Print)	2153-0009
ISSN (Electronic)	2153-0017

Conference

Conference	26th IEEE International Conference on Intelligent Transportation Systems
Abbreviated title	ITSC 2023
Country/Territory	Spain
City	Bilbao
Period	24/09/23 → 28/09/23
Internet address	https://2023.ieee-itsc.org/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

Access to Document

10.1109/ITSC57777.2023.10422348Licence: Unspecified

ITSC_23_Planning_vs_MLAccepted author manuscript, 173 KBLicence: Unspecified

Cite this

Vallati, M., & Chrpa, L. (2024). In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems. In Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems: ITSC 2023 (pp. 4913-4918). Article 10422348 (International Conference on Intelligent Transportation Systems (ITSC)). IEEE. https://doi.org/10.1109/ITSC57777.2023.10422348

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title = "In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems",

abstract = "In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real world applications. This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated. ",

keywords = "Artificial Intelligence, Intelligent Transportation Systems (ITS), Black-box systems",

author = "Mauro Vallati and Luk{\'a}{\v s} Chrpa",

note = "Funding Information: 1Mauro Vallati is with the University of Huddersfield, Huddersfield, UK. Mauro Vallati was supported by a UKRI Future Leaders Fellowship [grant number MR/T041196/1]. [email protected] 2Luk{\'a}sˇ Chrpa is with the Czech Technical University in Prague, Prague, Czechia. Luk{\'a}sˇ is supported by Czech Science Foundation project no. 23-05575S. Publisher Copyright: {\textcopyright} 2023 IEEE.; 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 ; Conference date: 24-09-2023 Through 28-09-2023",

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language = "English",

isbn = "9798350399479",

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Vallati, M & Chrpa, L 2024, In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems. in Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems: ITSC 2023., 10422348, International Conference on Intelligent Transportation Systems (ITSC), IEEE, pp. 4913-4918, 26th IEEE International Conference on Intelligent Transportation Systems, Bilbao, Spain, 24/09/23. https://doi.org/10.1109/ITSC57777.2023.10422348

In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems. / Vallati, Mauro; Chrpa, Lukáš.
Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems: ITSC 2023. IEEE, 2024. p. 4913-4918 10422348 (International Conference on Intelligent Transportation Systems (ITSC)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

AU - Vallati, Mauro

AU - Chrpa, Lukáš

N1 - Conference code: 26

PY - 2024/2/13

Y1 - 2024/2/13

N2 - In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real world applications. This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated.

AB - In recent years, Artificial Intelligence (AI) has been increasingly used in traffic management and control, particularly in the smart city context. However, the vast majority of recent AI-based approaches rely on data-driven black-box models that hinder the ability to understand the behaviour and dynamics that lead to a given output. On the contrary, Good Old-Fashioned Artificial Intelligence approaches that are based on symbolic models, such as automated planning, can provide the transparency and explainability needed in real world applications. This paper focuses on the benefits of using automated planning techniques in Intelligent Transportation Systems (ITS), with a focus on explainability. A case study is presented to demonstrate how the components of an automated planning system can support explainability, the types of explanations that can be obtained, and the way in which such explanations can be generated.

KW - Artificial Intelligence

KW - Intelligent Transportation Systems (ITS)

KW - Black-box systems

UR - https://www.scopus.com/pages/publications/85180627102

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T3 - International Conference on Intelligent Transportation Systems (ITSC)

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BT - Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems

PB - IEEE

T2 - 26th IEEE International Conference on Intelligent Transportation Systems

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Vallati M, Chrpa L. In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems. In Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems: ITSC 2023. IEEE. 2024. p. 4913-4918. 10422348. (International Conference on Intelligent Transportation Systems (ITSC)). doi: 10.1109/ITSC57777.2023.10422348

In Defence of Good Old-Fashioned Artificial Intelligence Approaches in Intelligent Transportation Systems

Abstract

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UN SDGs

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