Role and Key Applications of Artificial Intelligence & Machine Learning in Transportation

Authors

  • Memoona Shaheen
  • Mehreen Arshad
  • Owais iqbal

DOI:

https://doi.org/10.47672/ejt.632

Keywords:

Artificial Intelligence, Machine Learning, Transportation

Abstract

Purpose: The main target of this paper was to examine the significance of Artificial Intelligence and Machine Learning and their effect on the transportation business.

Methodology: This hypothesis was a survey of the significant machine learning calculations and their applications in the field of big data. This paper try to attempt to exhibit the need to remove significant data from the huge measure of enormous information as traffic data available in this day and age and recorded diverse machine learning strategies that can be utilized to separate this information needed to encourage better dynamic for transportation applications.

Findings: This paper present an investigation of the different Artificial Intelligence (AI) methods that have been actualized to improve Intelligent Transportation Systems (ITS). Specifically, this paper assembled them into three main territories relying upon the main field where they were applied: Vehicle control, Traffic control and prediction, and Road security and accident prediction. The aftereffects of this examination uncover that the mix of various AI methodologies is by all accounts promising, particularly to oversee and investigate the huge measure of data created in transportation

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Author Biographies

Memoona Shaheen

  Ph.D. Scholar, Institute of Management Sciences, University of Balochistan, Quetta.

Institute of Management Sciences, University of Balochistan, Quetta Sariab Road, Quetta.

 

Mehreen Arshad

School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology, Islamabad, Pakistan

Owais iqbal

NED University of Engineering & Technology

 

References

Abraham, A. (2005). Artificial Neural Networks. Handbook of Measuring System Design; Sydenham, P.H., Thorn, R., Eds.; John Wiley & Sons, Ltd.: Hoboken, NJ, USA.

Bhadeshia H. K. D. H. (1999). Neural Networks in Materials Science. ISIJ International. 39 (10): 966-979. doi:10.2355/isijinternational.39.966.

Donepudi, P.K. (2015). Crossing point of Artificial Intelligence in cybersecurity. American journal of trade and policy, 2(3), pages: 121-128

Donepudi, P.K. (2018). AI and Machine learning in pharmacy: Systematic review of related literature, ABC journal of advanced research, 7 (2), 109-112.

Fogue, M., Garrido, P., Martinez, F. J., Cano, J.-C., Calafate, C. T., and Manzoni, P. (2014). A system for automatic notification and severity estimation of automotive accidents, IEEE Transactions on Mobile Computing, vol. 13, no. 5, pp. 948-963.

Hidas, P. (2002). Modeling Lane Changing and Merging in Microscopic Traffic Simulation. Transportation Research Part C., 10, 351-371.

Lv, Y., Duan, Y., Kang, W., et al. (2015). Traffic flow prediction with big data: a deep learning approach, IEEE Trans. Intell. Transp. Syst., 16, (2), pp. 865-873.

Patterson, D. (1990). Introduction to Artificial Intelligence and Expert Systems, Prentice-Hall, Inc.: Upper Saddle River, NJ, USA.

Qianchuan, Z. & Krogh, B.H. (2006). Formal verification of statecharts using finite-state model checkers. Control Systems Technology, IEEE Transactions, 14(5): p. 943-950.

Sadek, A. (2007). Artificial Intelligence in Transportation, Transp. Res. Circ., E-C113, 72-79.

Smith, R. (1985). Knowledge-Based Systems Concepts, Techniques, Examples. reidgsmith.com. Schlumberger-Doll Research. Retrieved 9 November 2013.

Tobias, R., and C. Hofmann (2003). Evaluation of Free Java-Libraries for Social-Scientific Agent-Based Simulation. Journal of Artificial Societies and Social Simulation, 7(1). http://jasss.soc.surrey.ac.uk/7/1/6.html.

Transportation Research Board (2003a). A Guidebook for Developing a Transit Performance-Measurement System. Transit Cooperative Research Program. Report 88. Washington, D.C.

Veres, S.M. (2007). Autonomous and adaptive control of vehicles in formation - Editorial to special issue. Int. J. Adapt. Control Signal Process, 21(2-3): p. 93-94.

Wakimin N., Azlinaa A., Hazman S. (2018). Tourism demand in Asean-5 countries: Evidence from panel data analysis. Manag. Sci. Lett. 8,677-690. doi: 10.5267/j.msl.2018.4.023.

Yegnanarayana, B. (1999). Artificial Neural Networks, PHI Learning Pvt. Ltd.: New Delhi, India, p. 476.

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Published

2020-12-31

How to Cite

Shaheen, M. ., Arshad, M. ., & Iqbal, O. . (2020). Role and Key Applications of Artificial Intelligence & Machine Learning in Transportation. European Journal of Technology, 4(1), 47–59. https://doi.org/10.47672/ejt.632

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Section

Articles