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In view of the current short-term traffic flow prediction methods that fail to fully consider the spatial correlation of traffic flow, and fail to make full use of historical data features, resulting in low prediction accuracy and poor robustness. Therefore, in paper, combining Non-negative Matrix Factorization (NMF) and LSTM model Based on Attention Mechanism (AttLSTM),…

There is no doubt that a good knowledge of traffic demand has a direct impact on improving traffic management. Road traffic is strongly correlated with many factors such as day of week, time of day, season and holidays which make it suitable for prediction. In this paper, we develop a neural network model for hourly…

This research describes new traffic congestion analysis method “Traffic Congestion Triangle” based on more than one month real traffic big data analysis in India. The location of the research is one of typical economical growing cities Ahmedabad in Gujarat state of India. The traffic congestion becomes more serious issues in most developing countries and the…

Technological developments in the Internet and communications have created a vastly complex and dynamic context with diverse heterogeneous networks and fast growth of mobile devices and multimedia. As the Internet becomes the primary mode of communication for many organisations there is requirement to enhance quality of service (QoS) from heterogeneous systems and networks. Traditional networks…

This study is the extension of the previous study about “Traffic Service Quantitative Analysis Method under Developing Country” in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). In the previous study, it is introduced how to make quantitative calculation for traffic congestion by traffic parameters and its characteristics curve such as traffic…

TSN is an attractive solution for latency-critical frame transmission built upon IEEE 802 architecture. Traffic scheduling and shaping in TSN aim to achieve bounded low latency and zero congestion loss. However, the most widespread solution (i.e. Time-Aware Shaper) requires a networkwide precision clock reference and only targets on cyclical traffic flows. This paper focuses on…

Traffic road management is becoming more complex due to limited resources and an increasing number of hybrid vehicles. Currently, a number of global classical computing tools are used to manage the traffic road network. This kind of classical computing is resource intensive and expensive, and in the best case, optimizing a traffic network takes a…

On-ramping is being widely used as e method to increase the freeway operational efficiency. The main traffic parameter that must be taken in consideration for the implementation of the feedback control strategies for the on-ramp metering is density on the main section of road. In this paper is given discretized model of traffic which is…