ABSTRACT
The usage of vehicles has been increased over the past two decades due to increase in world population which leads traffic jamming, travel delays, road accidents and energy consumption. To solve this issue, intelligent transport system needs to be developed using powerful predictive model.
This chapter focuses on smart statistical AI models to address the issues of transport infrastructure development, traffic forecasting and driver behavior detection that avoids traffic congestion and accident. Neural network and artificial intelligence (AI) models provide an impact in the design of intelligent transportation model. The artificial neural networks (ANNs) are used to extract the patterns to develop transportation infrastructure systems (TIS). GNN ensures the estimated time of arrival by analyzing the traffic congestion to overcome traffic jams. Deep 146Convolution Neural Network is used to detect the behavior of driver based on the characteristics like acceleration, gravity, throttle, and revs per minute (RPM) to reduce accidental risks. All these AI and neural network models bring safety to the civic, cost-effective, and reliable transportation system.
