Based on the full velocity difference (FVD) model, with the consideration of the effect of information about the two leading cars to the following car, an improved two_car following model of traffic flow has been deduced. The linear stable judging condition is obtained to the improved model by its stability analysis, which shows the stability range of the improved model is obviously larger than FVD model by comparing them. Numerical simulation shows that our model can avoid the disadvantage of negative velocity occurring at small reaction coefficient in FVD model by adjusting the information of the next-nearest-neighbor leading car. And there is unavoidable effect to traffic flow from the next-nearest-neighbor leading car’s information.
Starting from the full velocity difference model, an extended car-following model is proposed by considering the influence that in real traffic the driver’s forecast has an effect on car-following behavior of traffic flow. The mechanism how the stability and energy dissipation of traffic flow are in fluenced by the driver’s forecast effect is revealed by the application of the proposed new model. The linear stability condition of the new model is derived theoretically through linear stability theory. The phase diagram of linear stability condition is divided into two regions by each stability curve: the stable and unstable regions. And the corresponding stable region will be enlarged with the increase of driver’s forecast time, hence the traffic condition will be improved through considering driver’s forecast effect. By numerical simulation method, the space-time evolution relation between the velocity and headway of vehicles in car-following queue is investigated systematically under the influence of driver’s forecast. In the same time, the evolution mechanisms of the overall average energy dissipation of traffic flow and individual vehicle energy consumption with the addition of small disturbance are discussed explicitly under a periodic condition, and it is discovered that the overall average energy consumption in traffic flow and the energy dissipation of individual vehicle is accompanied by a complex critical phase transition process. Good agreement between the numerical simulation and the theoretical analysis show that by considering of driver’s forecast effect, not only the stability of traffic flow is enhanced obviously, but the energy consumption is reduced remarkably as we expect. Furthermore, it is verified that both the overall average energy consumption of the considered traffic flow and the energy consumption of an individual vehicle are reduced gradually along with the increase of driver’s forecast time. On the other hand, numerical simulation results verify that the shortcoming of negative speed appearing in the full velocity difference model with low reaction coefficient can be effectively avoided by increasing the driver’s forecast time in the improved model, which means that the dynamic characteristics of traffic flow can be described more precisely by the proposed model.
The rapid changing market is making manufacturing systems increasingly trend to multi-varieties and small-batch production. It drives that strict production operation management in detail is done. In this paper RFID tags are introduced to overcome difficulty to identity important production elements in workshop. A tag data model of production element is proposed, and the architecture and integration operation mode of corresponding production operation management system are established. Then, an information fusion model of real-time heterogeneous production data from multi-sources and implementation methods of rapidly reconfigurable production operation management system based on component are presented. The application results in a motorcycle assembly line show the production efficiency and quality are obviously improved.
The characteristics of natural radio communications and the disturbances of application environment inevitably lead to the unreliable phenomena of duplicated readings, false positive reading and false negative reading when RFID is applied to logistics tracking system, and numerous unreliable data are generated. To solve this problem, a series of evaluation indexes for evaluating RFID application reliability were put forward, and a layered data processing model was established to improve RFID application reliability, including primitive event processing layer and complex event processing layer. The former receives primitive reading events from the reader-network, cleans redundant events, and thus tidy logic reading events are obtained. And the complex event processing layer detects and corrects false positive reading and false negative reading through setting up application integrity constraint. The results of application show that the model can guarantee the correctness and integrality of the data, and improve RFID application reliability.
In the past study of issues related to autonomous platoon vehicles with little consideration of vehicles internal information factors. Thus, longitudinal vehicle model was built, the vehicle interior information external information and physical factors are fused together and the impact of vehicle interior information on the control of autonomous platoon vehicle is analyzed. Fuzzy PI controller is designed and realized the longitudinal control of following vehicle. Use Matlab to build a vehicle cyber-physical models and vehicle simulation environment. The experiment simulations show that vehicle interior information delays affecting the control of autonomous platoon vehicles, the designed model and fuzzy PI controller can realize safety of vehicle tracking control, also can maintain the platoon stable.
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