Developing link capacity functions at urban arterials

Thesis (Master)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2009Includes bibliographical references (leaves: 67)Text in English; Abstract: Turkish and Englishxi, 77 leavesLink capacity functions are the relationships among the main variables of the vehicular traffic flow at any links. Moreover, developing link capacity function is a task that is related to traffic engineering, yet it is too difficult to find a unique link capacity function belonging to all links in cities. Therefore, this thesis does aim to develop link capacity functions peculiar to the selected divided and undivided links in downtown city İzmir. The main process of developing the link capacity functions depends upon the fastidious site selection, data collection and data analyses techniques. Especially, the main vehicular traffic variables such as flow rate, capacity, speed, travel time data describe the links capacity function. After the data collection process, the data manipulation and their analyses lead to build mathematical model about the link capacity functions. When considering the steps of this thesis, first of all, this thesis reviews the literature and formulates the problem statement and the research objective. Secondly, it conducts the task that consists of the site selection and data collection. In the following parts, this thesis study manipulates and analyzes the obtained data. Then, it performs the linear and non-linear model building by utilizing different functions called V/C ratio & dummy variable, BPR (Bureau of Public Roads) function and Overgaard function for the selected link groups in İzmir. Ultimately, this thesis study compares the model results and manifests the best link capacity function model

An Analysis of Vehicular Traffic Flow Using Langevin Equation

Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes

Developing link capacity functions at urban arterials

Thesis (Master)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2009Includes bibliographical references (leaves: 67)Text in English; Abstract: Turkish and Englishxi, 77 leavesLink capacity functions are the relationships among the main variables of the vehicular traffic flow at any links. Moreover, developing link capacity function is a task that is related to traffic engineering, yet it is too difficult to find a unique link capacity function belonging to all links in cities. Therefore, this thesis does aim to develop link capacity functions peculiar to the selected divided and undivided links in downtown city İzmir. The main process of developing the link capacity functions depends upon the fastidious site selection, data collection and data analyses techniques. Especially, the main vehicular traffic variables such as flow rate, capacity, speed, travel time data describe the links capacity function. After the data collection process, the data manipulation and their analyses lead to build mathematical model about the link capacity functions. When considering the steps of this thesis, first of all, this thesis reviews the literature and formulates the problem statement and the research objective. Secondly, it conducts the task that consists of the site selection and data collection. In the following parts, this thesis study manipulates and analyzes the obtained data. Then, it performs the linear and non-linear model building by utilizing different functions called V/C ratio & dummy variable, BPR (Bureau of Public Roads) function and Overgaard function for the selected link groups in İzmir. Ultimately, this thesis study compares the model results and manifests the best link capacity function model

A superstatistical model of vehicular traffic flow

In the analysis of vehicular traffic flow, a myriad of techniques have been implemented. In this study, superstatistics is used in modeling the traffic flow on a highway segment. Traffic variables such as vehicular speeds, volume, and headway were collected for three days. For the superstatistical approach, at least two distinct time scales must exist, so that a superposition of nonequilibrium systems assumption could hold. When the slow dynamics of the vehicle speeds exhibit a Gaussian distribution in between the fluctuations of the system at large, one speaks of a relaxation to a local equilibrium. These Gaussian distributions are found with corresponding standard deviations 1/β. This translates into a series of fluctuating beta values, hence the statistics of statistics, superstatistics. The traffic flow model has generated an inverse temperature parameter (beta) distribution as well as the speed distribution. This beta distribution has shown that the fluctuations in beta are distributed with respect to a chi-square distribution. It must be mentioned that two distinct Tsallis q values are specified: one is time-dependent and the other is independent. A ramification of these q values is that the highway segment and the traffic flow generate separate characteristics. This highway segment in question is not only nonadditive in nature, but a nonequilibrium driven system, with frequent relaxations to a Gaussian

Determining the complexity of multi-component conformal systems: A platoon-based approach

Many systems in nature and engineering are composed of subsystems. These subsystems may be formed in a linear, planar or spatial array. A typical example of these formations is a chain of vehicles known as platoon formation in traffic flow. Platoon formation of vehicles is a linear or planar formation of vehicles where a certain and a constant headway, and sideway if applicable, is provided in between every and each one of them. It is argued in this paper that a well-automated platoon formation of vehicles is an extreme case of conformity. During this transformation from a many degrees of freedom formation to a solid object, Tsallis q value is computed to be ranging from one extreme case of q=3 to the other where q=1, when classified in terms of inverse temperatures of clearance fluctuations. At one extreme of q=3, one observes unbounded fluctuations in clearance fluctuations so that inverse temperature distributions approach a Dirac delta at the origin. At the other extreme of q=1, fluctuations in clearance tend to zero asymptotically, where a solid structure of agents (vehicles) emerges. The transition from q=3 to q=1 is investigated through synthetic and experimental clearance fluctuations between the cars. The results show that during the transition from q=3 to q=1, the platoon loses its many degrees of freedom (dof) of motion until a solid single object emerges. Authors assert that the Tsallis q value of a platoon of vehicles is limited to 3>q<1

An entropy-based analysis of lane changing behavior: An interactive approach

Objectives: As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. Methods: The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Results: Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. Conclusions: The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would match discretionary lane changing behavior. This article states that driver behaviors would be in the nonadditive entropy domain to provide a safe traffic stream and hence with vehicle accident prevention in mind

Soft computing and regression modelling approaches for link-capacity functions

Link-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0:87 while this value was almost 0.60 for the regression-based models