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Introduction to Explainable AI and Intelligent Transportation

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Explainable Artificial Intelligence for Intelligent Transportation Systems

Abstract

Artificial Intelligence (AI) has gained significant traction in recent years, and if properly handled, it has the potential to exceed expectations in a wide range of application areas throughout the world. The current AI applications lack explainability/transparency. The principles underpinning this difficulty found in explainable AI (XAI) are generally recognised as critical for the practical deployment of AI models in practice. The effective use of AI requires a thorough knowledge of the interactions between AI and data on the one hand and the features and factors of the transportation system on the other. Furthermore, transportation authorities need to determine the best way to use these technologies to create a rapid improvement in congestion relief, make travel time more reliable for their customers, and improve their critical assets’ economics and productivity, among other things. This chapter presents an overview of the global artificial intelligence approaches to handling transportation challenges: traffic management, traffic safety, public transit, and urban mobility.

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Authors and Affiliations

  1. Amity International Business School, Amity University, Noida, India

    Loveleen Gaur

  2. School of Computing and IT, Manipal University Jaipur, Jaipur, India

    Biswa Mohan Sahoo

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  1. Loveleen Gaur
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Gaur, L., Sahoo, B.M. (2022). Introduction to Explainable AI and Intelligent Transportation. In: Explainable Artificial Intelligence for Intelligent Transportation Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-09644-0_1

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  • DOI: https://doi.org/10.1007/978-3-031-09644-0_1

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