A SURVEY ON VEHICULAR MOBILITY MODELING: FLOW MODELING

Motion or Movement patterns of vehicles communicating wirelessly play a important role in the simulation based evaluation of Vehicular Ad Hoc Networks (VANETs). It is to know that recent research about mobility modeling has given direction for vehicular network study still to obtain realistic behavior of vehicles; developments in this area are required in detail level. In this paper, one of the main mobility modeling approach is discussed to the extent that it can help to understand models formulation and integr0ation strategies with network simulators. This approach is called as flow mobility modeling. It is put into the discussion and elaborated in such way it clarifies basics of flow modeling and its impact. It also finds a different ways of modeling and implementation into existing traffic simulators viz. SUMO, VISSIM etc. Flow of vehicle is a key aspect of flow modeling which is often used in VANET‘s simulation

The Effects of Car Density on the Overall Interaction of the Vehicles Current Traffic Flow Models Case Study at Wolaita Sodo Town

Congestion of vehicular traffic within urban areas is a problem experienced worldwide. It has adverse effects on people quality of life due to delays, accidents and environmental pollution. Congestion is gaining popularity in the Wolaita Sodo and quantifying the effects of an additional vehicle joining the traffic stream is a critical issue to determine the toll rates. When additional vehicles enter a crowded roadway they increase travel time for all vehicles. The effect of additional vehicles worsens when the flow is near the capacity of the traffic stream. The speed and flow of the traffic stream are considered as the major variables to quantify these effects. Hence to better understand and quantify this issue it is necessary to accurately model the traffic stream near capacity. A mathematical macroscopic traffic flow model known as Lighthill, Whitham and Richards model appended with a closure nonlinear velocity-density relationship yielding a quasi-linear first order (hyperbolic) partial differential equation as an initial boundary value problem was considered. The aims of this analysis are principally represented by the maximization of vehicles flow, and the minimization of traffic congestions, accidents and pollutions. We  present  numerical simulation  of  the  IBVP  by  a  finite  difference  scheme report  on  the stability and efficiency of the scheme by performing numerical experiments. The computed result satisfies some well known qualitative features of the solution. Keywords: Density function , quasi-linear, Macroscopic Traffic flow, Numerical simulation

Microscopic traffic models, accidents, and insurance losses

The paper develops a methodology to enable microscopic models of transportation systems to be accessible for a statistical study of traffic accidents. Our approach is intended to permit an understanding not only of historical losses but also of incidents that may occur in altered, potential future systems. Through such a counterfactual analysis, it is possible, from an insurance, but also from an engineering perspective, to assess the impact of changes in the design of vehicles and transport systems in terms of their impact on road safety and functionality. Structurally, we characterize the total loss distribution approximatively as a mean-variance mixture. This also yields valuation procedures that can be used instead of Monte Carlo simulation. Specifically, we construct an implementation based on the open-source traffic simulator SUMO and illustrate the potential of the approach in counterfactual case studies

A Comprehensive Approach to WSN-Based ITS Applications: A Survey

In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios

A new car-following model considering acceleration of lead vehicle

For decades, the general motors (gm) car following model has received a great deal of attention and provided a basic framework to describe the interactions between vehicles on the road. It is based on the stimulus-response assumption that the following vehicle responds to the relative speed between the lead vehicle and itself. However, some of the empirical findings show that the assumption of gm model is not always true and need some modification. For example, the acceleration of the following vehicle is very sensitive to the sign of the relative speed and because of no term in the model that directly represents the leader’s acceleration, the follower’s response to the leader’s acceleration can be retarded. This paper offers a new car-following model that can be considered as a variant of the gm model that can better capture car following behavior. The new model treats the follower’s acceleration as a proportion of a weighted sum of the leader’s acceleration and the relative speed between the lead and following vehicles. This paper compares the new model with the original gm model numerically and the characteristics of the new parameters in the model are investigated. It is also shown that the new model overcomes the shortcomings of the original gm model identified in this paper and gives us more instruments to capture the real-world car-following behavior. First published online: 28 May 201