![]() Using a direct numerical resolution technique, traffic density, waiting queue lengths, travel times and delays are predicted. The proposed models have the twofold benefit of modelling and predicting traffic. In this context, we develop in this thesis stochastic Markov chain models based on real vehicle traces collected by RSUs using V2X communication to emulate vehicular behaviour in both urban and highway roads. Consequently, it is compulsory to include all these features in a mobility model for accurate results. The traffic behaviour is influenced by several factors such as road layout, speed limits, traffic rules and individual vehicle’s behaviour. ![]() ![]() Although faithful mobility models are found in the literature, they fail to accurately capture some aspects of vehicular mobility. Hence, a good understanding of mobility will allow the design and evaluation of channel access methods that are efficient and robust even in a mobile environment. However, conventional TDMA-based protocols might encounter difficulties in a dynamic networks such as access collision and unfair use of resources. TDMA has been proven the most suitable access technique for VANET as it allows a single node to access the channel at any time slot. In this thesis, we address specifically channel access methods for VANET that are based on TDMA method. This has negative effects on the network performance which does not allow to cater safety applications requirements. The particular feature of this network is the highly dynamic mobility which results in frequent changes in the topology and density of the network. VANET were designed specifically to provide a wireless communication infrastructure to allow vehicles and road equipment to exchange traffic data. One of the most stringent requirements of these applications is an error-free and reliable transmission of data packets. These systems rely on the most advanced technologies to provide intelligent and robust safety services that seek to prevent road incident that may threaten the life of passengers. ITS have grown in importance as a promising solution to the congestion issue. This calls for an upgrade of the transport system in order to ensure road users safety and effectively enhance the transportation infrastructure. The growing number of traffic accidents, the environmental footprint of transport, commercial speed of public transportation and traffic jams are few examples of the adverse consequences of congestion. The ever-growing traffic congestion is becoming a serious issue that needs to be urgently addressed. It can organize the transportation activities of electric locomotive robots scientifically, safely and efficiently, ensure the orderly distribution work and improve the intelligent degree of transportation system. The research shows that the scheduling strategy improves the transportation efficiency by 47.6 % compared with manual scheduling. Finally, the practicability of the scheduling strategy is verified by experiments. Then the scheduling parameters are optimized by simulation under the scheduling rules of electric locomotive robots. The scheduling model is proved to be conflict-free by theory. Then, according to the planning route, the scheduling parameters are set, and the transportation mode of electric locomotive robots is determined as interlaced transportation. Firstly, the cooperative operation routes of different types of electric locomotive robots are planned based on deadlock-free and collision rules. In order to improve the working efficiency of underground electric locomotive robots in complex geological coal mines and realize the automation of underground scheduling system, the scheduling model of electric locomotive robots is established based on the underground track layout.
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