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, CO2 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.
Highlights
Artificial intelligence (AI) is a broad area of computer science that makes machines function like a human brain
It can help the authorities to make a decision on whether to add new infrastructures or expanding lanes, a decision on what route to take during an incident or severe weather conditions and decision on the amount of money required for maintenance and rehabilitation
This paper presents an overview of the applications of AI to a variety of transport-related problems
Summary
Artificial intelligence (AI) is a broad area of computer science that makes machines function like a human brain. The CNN performs better for image processing tasks while RNN Processes a sequence for the input data to become well-suited for many application such as; language, writing and text recognition They are often referred to as Deep Learning Techniques due to the multiple hidden layers structured in their architectures. (i) The use of AI in corporate decision making, planning, and managing This is important to overcome the issue of a continuously rising demand with limited road supply. This section is subdivided into the application of AI for planning, designing and decision making, public transportation, intelligent self-driving cars. It illustrates real-time incident detection and future traffic state prediction.
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