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Accurately forecasting the influence of disturbances in High-Speed Railways (HSR) has great significance for improving real-time train dispatching and operation management. In this paper, we show how to use historical train operation records to estimate the influence of high-speed train disturbances (HSTD), including the number of affected trains (NAT) and total delayed time (TDT), considering the timetable and disturbance characteristics. We first extracted data about the disturbances and their affected train groups from historical train operation records of Wuhan-Guangzhou (W-G) HSR in China. Then, in order to recognize the concatenations and differences of disturbances, we used a K-Means clustering algorithm to classify them into four categories. Next, parametric and nonparametric density estimation approaches were applied to fit the distributions of NAT and TDT of each clustered category, and the goodness-of-fit testing results showed that Log-normal and Gamma distribution probability densities are the best functions to approximate the distribution of NAT and TDT of different disturbance clusters. Specifically, the validation results show that the proposed models accurately revealed the characteristics of HSTD and that these models can be used in real-time dispatch to predict the NAT and TDT, once the basic features of disturbances are known. [ABSTRACT FROM AUTHOR]

The goal of this paper is to investigate theoretically the possible directions of some specified methods for the alternative roundabouts effectiveness modeling and optimization. The out-coming criteria have an economical interpretation. Those are the objective functionals of the alternative roundabouts effectiveness as the profit gained in the course of the traffic flow changes in the view of the integral form. This is modeled taking into consideration the transport infrastructure functioning elements such as the traffic flow of a capacity model. It takes into account two major components of the transportation services which are the alternative roundabouts business’ incomes and expenses relating to the roundabouts transportation worthiness support. The prototypic approach is that one from the aircraft airworthiness support measures models. Corresponding managerial influences with respect to environmental, safety, utility, and other issues, as well as probable impacts, are modeled with the construction of the relevant under-integral expressions, equations, and appropriate coefficients and parameters of the mathematical models. The achieved theoretical results, on the basis of the Euler-Lagrange equation and accepted assumptions, have been checked for the sufficiency of the objective functional maximum presence at the “point” with the use of the conducted computer simulation. The necessary diagrams are plotted in order to illustrate the theoretical contemplations and speculations, as well as to check the correctness of the applied mathematical derivations and visualize the models’ preciseness and abilities. The theoretically constructed mathematical models have a significance of the prognostic values applicability required at the alternative roundabouts effectiveness modeling and optimization ensuring their design progress and evolutions. [ABSTRACT FROM AUTHOR]

In the field of traffic flow, speed, density, time, and distance are fundamental variables analyzed to predict traffic conditions. Reliable sources of information are gauged using tested mathematical approaches that have been developed. However, a fundamental diagram that could serve as a basis for expression techniques has not been devised. Red-green-blue (RGB) color modeling was used to overcome this limitation in traffic flow. The purpose of this study is to provide a way to understand traffic flow conditions based on features of three traffic flow elements simultaneously. The limitation of three-dimensional expressions in two-dimensional paper was extended to multi-dimensional information. Information on speed, density, and flow were combined into a single RGB color and given the name RGB flow-density space time-distance space. This cancels out the effect of each individual's vehicular trajectories and contains five major components of a specific road section. The new gizmo aims to provide information on traffic flow conditions in transition and to stimulate further approaches related to the predictions and understanding of traffic flow. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Hook turn (HT) is a unique traffic regulation rule for right-turning vehicles at intersections (in the system where driving is on the left), which was proposed in Melbourne to improve the safety level and operational efficiency of intersections. However, existing coordination plans for HT intersections are fixed and determined empirically, which restricts the further improvements of the efficiency. In this paper, mathematical models are developed for the calculation of the average vehicle delay, with consideration of the spillback phenomenon of HT vehicles in waiting areas. The platoon dispersion model is used to describe the traffic movements between coordinated intersections. With the aim of minimizing average delay of all vehicles, a mixed nonlinear integer model is developed for the optimal coordination plan, which is solved by a genetic algorithm due to the complexity of the model. Finally, a numerical example is built based on three HT intersections in downtown Melbourne, to verify the proposed methodology. Based on a comparison with the current signal plan, the optimal signal plan can significantly reduce the average delay as well as the number of spillbacks, in both the peak hour and off-peak hour cases. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Because transportation systems involve massive complex human activities, there exist substantial unpredictable uncertainties of the traffic demands. This paper aims at presenting an H∞ control method for transportation network that can enhance the tolerance of the system due to these uncertainties. In particular, the store-and-forward approach is applied to model the system into a linear form. Then, a detailed controllability analysis shows that the system is not completely controllable by taking the constraints on the green times into account. This makes difficult to apply directly the H∞ method. To overcome this difficulty, this paper isolates the fully controllable part of the transportation system, and the problem of disturbance attenuation is then solved by means of a convex optimization with linear matrix inequality. Finally, the simulation of a large-scale hypothetical network is carried out to illustrate the results. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Parcel express service in many countries assumes door-to-door delivery of parcels and small packages in the fastest possible way. Delivery companies usually organize hub delivery networks, as flows between hubs are characterized by the economy of scale effect. At hubs, parcels are exchanged across vans, trucks, and planes. To organize parcel delivery in a specific region, the parcel delivery company must make appropriate decisions about the total number of parcel delivery hubs, their locations, and the allocation of demand for facilities' services to facilities. These issues are modeled in this paper as a multi-objective problem. The model developed is based on compromise programming and genetic algorithms. We also demonstrate in the paper an interactive manner in which a defined problem can be solved. The proposed model could be implemented in large-scale networks. The paper also shows a case study of parcel delivery service in Serbia. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Highway traffic flow phenomena involve several complex and stochastic variables with high interdependencies. The variations in roadway, traffic and environmental factors influence the traffic flow quality significantly. Capacity analysis of road sections under different traffic and geometric conditions need to quantify the vehicles of widely varying characteristics to a common and universally acceptable unit. Passenger car unit (PCU) is the universally adopted unit of traffic volume, keeping the passenger car as the 'standard vehicle' with reference to its static and dynamic characteristics; other vehicles are expressed to its equivalent number in terms of PCUs. The studies carried out in this aspect represent the dynamic nature of impedance caused by a vehicle while moving through a traffic stream. The PCU values recommended by the Highway Capacity Manual are widely applied in many countries; however, their applicability is highly under debate because of the variations in prevailing local traffic conditions. There are several factors that influence the PCU values such as traffic, roadway, vehicle, environmental and control conditions, etc. Apart from vehicular characteristics, the other two major factors that influence the PCU of vehicles are the following: (i) road width and (ii) traffic volume. In this study, estimation of PCU values for the different types of vehicles of a highly heterogeneous traffic on 7.5- and 11.0-m-wide roads, using micro-simulation technique, has been dealt with. It has been found that the PCU value of a vehicle type varies significantly with variation in road width and traffic volume. The results of the study indicate that the PCU values are significantly influenced by the said two factors. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY The origin-destination matrix is an important source of information describing transport demand in a region. Most commonly used methods for matrix estimation use link volumes collected on a subset of links in order to update an existing matrix. Traditional volume data collection methods have significant shortcomings because of the high costs involved and the fact that detectors only provide status information at specified locations in the network. Better matrix estimates can be obtained when information is available about the overall distribution of traffic through time and space. Other existing technologies are not used in matrix estimation methods because they collect volume data aggregated on groups of links, rather than on single links. That is the case of mobile systems. Mobile phones sometimes cannot provide location accuracy for estimating flows on single links but do so on groups of links; in contrast, data can be acquired over a wider coverage without additional costs. This paper presents a methodology adapted to the concept of volume aggregated on groups of links in order to use any available volume data source in traditional matrix estimation methodologies. To calculate volume data, we have used a model that has had promising results in transforming phone call data into traffic movement data. The proposed methodology using vehicle volumes obtained by such a model is applied over a large real network as a case study. The experimental results reveal the efficiency and consistency of the solution proposed, making the alternative attractive for practical applications. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Density is the most important congestion indicator among fundamental traffic flow variables-flow, speed, and density. Measuring density by aerial monitoring, although accurate, cannot be widely used because of its cost and dependency on weather. The conventional method, estimating density based on the relationship between traffic flow and speed as measured by a point detector, does not yield an accurate density value, because the flow is not homogeneous. A new and advanced density measurement method, which is based on the in-out counting method, is proposed. This method uses average density instead of instantaneous density. By using two point detectors, this method can capture considerable variation in density and is accurate for single and multilane freeway segments. Establishing the number of floating vehicles necessary to obtain a fair approximation of the true density is for future research. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Traffic delay caused by incidents is closely related to three variables: incident frequency, incident duration, and the number of lanes blocked by an incident that is directly related to the bottleneck capacity. Relatively, incident duration has been more extensively studied than incident frequency and the number of lanes blocked in an incident. In this study, we provide an investigation of the influencing factors for all of these three variables based on an incident data set that was collected in New York City (NYC). The information about the incidents derived from the identification can be used by incident management agencies in NYC for strategic policy decision making and daily incident management and traffic operation. In identifying the influencing factors for incident frequency, a set of models, including Poisson and Negative Binomial regression models and their zero-inflated models, were considered. An appropriate model was determined based on a model decision-making tree. The influencing factors for incident duration were identified based on hazard-based models where Exponential, Weibull, Log-logistic, and Log-normal distributions were considered for incident duration. For the number of lanes blocked in an incident, the identification of the influencing factors was based on an Ordered Probit model which can better capture the order inherent in the number of lanes blocked in an incident. As identified in this study, rain is the only factor that significantly influenced incident frequency. For incident duration and the number of lanes blocked in an incident, various factors had significant impact. As concluded in this study, there is a strong need to identify the influencing factors in terms of different types of incidents and the roadways where the incidents occured. [ABSTRACT FROM AUTHOR]

We propose a macroscopic model of lane-changing that is consistent with car-following behavior on a two-lane highway. Using linear stability theory, we find that lane-changing affects the stable region and the propagation speeds of the first-order and second-order waves. In analyzing a small disturbance, our model effectively reproduces certain non-equilibrium traffic-flow phenomena-small disturbance instability, stop-and-go waves, and local clusters that are affected by lane-changing. The model also gives the flow-density relationships in terms of the actual flow rate, the lane-changing rate, and the difference between the potential flow rate (the flow rate that would have occurred without lane-changing) and the actual flow rate. The relationships between the actual flow rate and traffic density and between the lane-changing rate and traffic density follow a reverse-lambda shape, which is largely consistent with observed traffic phenomena. [ABSTRACT FROM AUTHOR]

Although many types of traffic sensors are currently in use, all have some drawbacks, and widespread deployment of such sensor systems has been difficult due to high costs. Due to these deficiencies, there is a need to design and evaluate a low cost sensor system that measures both vehicle speed and counts. Fulfilling this need is the primary objective of this research. Compared to the many existing infrared-based concepts that have been developed for traffic data collection, the proposed method uses a transmission-based type of optical sensor rather than a reflection-based type. Vehicles passing between sensors block transmission of the infrared signal, thus indicating the presence of a vehicle. Vehicle speeds are then determined using the known distance between multiple pairs of sensors. A prototype of the sensor system, which uses laser diode and photo detector pairs with the laser directly projected onto the photo detector, was first developed and tested in the laboratory. Subsequently this experimental prototype was implemented for field testing. The traffic flow data collected were compared to manually collected vehicle speed and traffic counts and a statistical analysis was done to evaluate the accuracy of the sensor system. The analysis found no significant difference between the data generated by the sensor system and the data collected manually at a 95% confidence interval. However, the testing scenarios were limited and so further analysis is necessary to determine the applicability in more congested urban areas. The proposed sensor system, with its simple technology and low cost, will be suitable for saturated deployment to form a densely distributed sensor network and can provide unique support for efficient traffic incident management. Additionally, because it may be quickly installed in the field without the need of elaborate fixtures, it may be deployed for use in temporary traffic management applications such as traffic management in road work zones or during special events. [ABSTRACT FROM AUTHOR]