Applied Mechanics and Materials Vols. 241-244

Abstract: In order to evaluate the ship traffic safety about the large water area, the system of maritime macroscopic traffic safety was developed, which can give the simulation result under the setting conditions, using the electronic chart display and information system conform to S57 and S52. The simulation model of ship traffic flow is proposed, which play an important part in the system. The outcome can be provided according to the assessment method of maritime safety, and displayed on the ECDIS. With the clicking on the icons by the mouse button, the information about the simulation can be offered.

Abstract: Over the last decade, neural networks have found application for solving a wide range of areas from business, commerce, data mining and service systems. Hence, this paper constructs a new model based extension theory and neural network to forecast the ship transportation. The new neural network is a combination of extension theory and neural network. It uses an extension distance to measure the similarity between data and cluster center, and seek out the useless data, then to use neural network to forecast. When presenting a test example of prediction of ship transportation, the results verifies the effectiveness and applicability of the novel extension neural network. Compared with other forecasting techniques, especially other various neural networks, the extension neural network permits an adaptive process for significant and new information, and gives simpler structure, shorter learning times and higher accuracy.

Abstract: In order to improve the level of water transportation information management and decrease the loss of ship-bridge collision, a ship-bridge collision early warning calculation method that based on fuzzy math and expert advice was established. It was used in Chongqing VTS and the real ship experiment was made. The results show that this method can predict the risk of ship-bridge collision, avoid the collision accident, which have value in practice and popularization.

Abstract: The aim of the paper is to study the effect of the weaving section length on traffic flow operating under the different traffic demand. The paper uses the optimal velocity car-following model and symmetric lane-changing rule to simulate traffic flow operating in the weaving section, and calculate the headway and average speed under the different weaving section length. The results show that there is a critical value for the weaving section length. When the weaving section length is less than a critical value, the space headway significantly increase and the speed significantly decrease. When the weaving section length is larger than the critical value, the increased weaving section length has little improvement of traffic flow performance. The study proposes the critical value for the weaving section length of city expressway. Lastly, the paper analyzed the trajectory of traffic flow in the phase space of speed and space headway.

Abstract: Traffic overflow has great negative impact on normal traffic flow. Improper time setting and offset, even more right turn input traffic flow can cause this extreme phenomenon. In order to discover the intrinsic factor and relationship between overflow and signal setting, traffic flow incoming, we build the traffic flow model. This model takes two adjacent crosses as example, and to count the remained traffic flow queue length in given time interval. The simulation results prove our model’s feasibility. Our model well helps us to understand the overflow characteristics and to find the effective solution to conquer it in the future.

Abstract: The taxi with GPS is an efficient measure for detecting traffic condition. It is often called as floating car or moving detector. The aim of the paper is to estimate the characterization of urban traffic congestion based on taxi GPS data. Owing to the various factors including signal control, heterogeneous driver behavior, various vehicle performance, speed distribution of urban traffic is the typical mixed distribution. Based on this understanding, the paper firstly used kernel density estimation technique to estimate the probability density of mixed speed distribution. This method was a non-parametric probability density estimation method. Under the precondition that Gaussian kernel obtained the good fit quality, the paper used mixed Gaussian model to analyze the characterization of the congestion. By mixed Gaussian model, the paper obtained the numerical index including the mean, variance, weight. The example shows that we can estimate the characterization of urban traffic congestion using the paper's method. The results are important for designing traffic management plan for different scenarios and evaluating the performance of traffic management facilities.

Abstract: Based on the two-dimension cellular automaton traffic flow model (BML model), a mixed traffic flow model for urban traffic considering the transit traffic is established in this paper. Under the don't block the box rules and the opening boundary conditions, the impacts of transit traffic, the central station, traffic lights cycle, the vehicles length on the mixed traffic flow is studied by computer simulation. Some important characters appearing in the new model are also elucidated. It shows that traffic flow is closely related to traffic lights cycle, the geometric structure of transport network and boundary conditions. Under certain traffic light cycle time, the traffic flow has a periodical oscillation change. The comparison to practical measured data shows that our stimulation results are accordant with the changes of real traffic flow, which confirms the accuracy and rationality of our model.

Abstract: Real-time traffic flow prediction is the core of traffic control and management, which is the basis of traffic safety in mountain area. Traffic flow, which is highly time-relevant, with the features of high non-linear and non-determinism, can be treated as the time sequence forecast. Considering these features, this paper deals specially with this issue based on Wavelet neural network. Besides, by taking a road in mountain area for example, the paper realizes the analog simulation through the Matlab software programming. And the simulation results show that the traffic flow can be precisely forecast using Wavelet neural network, and its value is close to the expectations. The MAE of the Wavelet neural network is 20.1074 and the MSE is 2.5254.

Abstract: Slow traffic accounts for a great part of urban transportation, and is drawn more and more attention. However, the service system for this kind of traffic is rather inadequate, which seriously hampers the construction of smart city and digital urban. In this paper, beginning with the characteristics of slow travel persons, we design a multi-mode traffic information service platform for pedestrians and bicycle system specially. In our platform, non-interactive facilities for slow traffic are designed and deployed oriented pedestrians and cyclists. To provide customized information meeting pedestrians’ various demands and allow users’ feedback, the interactive service platform based intelligent mobile terminals and mobile internet is introduced instead of current electronic inquire equipments settled in public.

Abstract: To detection the realtime information of the traffic congestion on the road, a method based on realtime video analysis was present. The method, firstly figure out the density of the vehicles on the lane, and then calculates optical flow velocity vetors of corner points on vehicles, finnaly, judges the current condition of the traffic flow by fuzzy logic based on the conditions of denisty and velocity. The proposed method is capable to accurately and timely detect the status of traffic congestion.