Abstract
Traffic congestion is caused by inefficient road operations and by excess demand of the travelers. Various researchers have submitted different recommendations for resolving the traffic congestions and for providing optimum routes to travel from a particular origin to the specified destination with less time and less fuel consumption. Historical traffic data has been used in traffic recommendation systems to present optimum travel routes to road users. The process of finding the optimum navigational path for a particular route is the personalization of the transportation system. The personalization makes the transportation into an intelligent transportation system (ITS). The intelligent transportation system stores the frequent traveler’s optimal path to travel from any source to the destination on a particular day at a particular time in the database. The artificial neural network (ANN) is then used for data analysis for making predications in various domains. The optimum path is the path which takes the least travel time with least fuel consumption. The personalized intelligent system assists travelers with the optimum path using the PrefixSpan algorithm.
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Muruganandam, S., Ananthapadmanaban, K.R., Srinivasan, S. (2022). An Intelligent Road Transportation System. In: Manogaran, G., Shanthini, A., Vadivu, G. (eds) Proceedings of International Conference on Deep Learning, Computing and Intelligence. Advances in Intelligent Systems and Computing, vol 1396. Springer, Singapore. https://doi.org/10.1007/978-981-16-5652-1_4
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