Applications of Artificial Intelligence in Transport: An Overview

Rusul Abduljabbar, Hussein Dia, Sohani Liyanage and Saeed Asadi Bagloee
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Rusul Abduljabbar: Department of Civil and Construction Engineering; Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Hussein Dia: Department of Civil and Construction Engineering; Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Sohani Liyanage: Department of Civil and Construction Engineering; Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Saeed Asadi Bagloee: Department of Civil and Construction Engineering; Swinburne University of Technology, Hawthorn, VIC 3122, Australia

Sustainability, 2019, vol. 11, issue 1, 1-24

Abstract: The rapid pace of developments in Artificial Intelligence (AI) is providing unprecedented opportunities to enhance the performance of different industries and businesses, including the transport sector. The innovations introduced by AI include highly advanced computational methods that mimic the way the human brain works. The application of AI in the transport field is aimed at overcoming the challenges of an increasing travel demand, CO 2 emissions, safety concerns, and environmental degradation. In light of the availability of a huge amount of quantitative and qualitative data and AI in this digital age, addressing these concerns in a more efficient and effective fashion has become more plausible. Examples of AI methods that are finding their way to the transport field include Artificial Neural Networks (ANN), Genetic algorithms (GA), Simulated Annealing (SA), Artificial Immune system (AIS), Ant Colony Optimiser (ACO) and Bee Colony Optimization (BCO) and Fuzzy Logic Model (FLM) The successful application of AI requires a good understanding of the relationships between AI and data on one hand, and transportation system characteristics and variables on the other hand. Moreover, it is promising for transport authorities to determine the way to use these technologies to create a rapid improvement in relieving congestion, making travel time more reliable to their customers and improve the economics and productivity of their vital assets. This paper provides an overview of the AI techniques applied worldwide to address transportation problems mainly in traffic management, traffic safety, public transportation, and urban mobility. The overview concludes by addressing the challenges and limitations of AI applications in transport.

Keywords: Artificial Intelligence; Genetic algorithms; Simulated Annealing; Artificial Immune system; Ant Colony Optimiser; Bee Colony Optimization; public transport; Auto Urban Mobility; traffic management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

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