Evaluation of Different Vehicle Following Models under Mixed Traffic Conditions (original) (raw)

A STUDY ON CAR FOLLOWING MODELS AND THEIR EVALUATION

2010

Car-following model has important applications in traffic and safety engineering e.g. for traffic simulation, advance vehicle control and safety system, capacity analysis, traffic impact studies, junction design, accident analysis, network analysis etc. The model is an essential component in microscopic traffic simulation programs that are widely preferred for applications in traffic and safety engineering. Microscopic traffic flow models

Simulation Model of Traffic Operations on Single Carriageway Roads: Model Calibrationand Validation

2017

The current Malaysian procedure for a detailed evaluation of the capacity and effects of various road and traffic characteristics for single carriageway roads, which is adopted directly from the American Highway Capacity Manual, is inadequate and inaccurate since several aspects used in the method such as the consideration of the recreational vehicles and trucks are not directly applicable to the Malaysian traffic characteristics. The validity of the analysis is debatable since the way in which the effect of motorcycles on overall performance of the roadways is considered is not clear. The existing simulation models of traffic operations on single carriageway roads also suffer from a similar weakness. Therefore, there is a need to develop a comprehensive traffic simulation model to carry out this task. Such a model must be capable of simulating traffic behavior for a range of road layout and geometry, at junctions and compositions of traffic which include motorcycles. This paper des...

Calibration and Validation of Microscopic Traffic Flow Models

Transportation Research Record, 2004

Microscopic simulation models are becoming increasingly important tools in modeling transport systems. There is a large number of models used in many countries. The most difficult stage in the development and use of such models is the calibration and validation of the microscopic sub-models such as the car following and gap acceptance models. This difficulty is due to the lack of suitable methods for adapting models to empirical data. The aim of this paper is to present recent progress in calibrating a number of microscopic traffic flow models. Ten very different models have been tested using data collected via DGPS-equipped cars (Differential Global Positioning System) on a test track in Japan. To calibrate the models, the data of the leading car are fed into the model under consideration and the model is used to compute the headway time series of the following car. The deviations between the measured and the simulated headways are then used to calibrate and validate the models. The calibration results agree with earlier studies as there are errors of 12 % to 17% for all models and no model can be denoted to be the best. The differences between individual drivers are larger than the differences between different models. The validation process gives acceptable errors from 17 % to 22%. But for special data sets with validation errors up to 60% the calibration process has reached what is known as "overfitting": because of the adaptation to a particular situation, the models are not capable of generalizing to other situations.

The Art of the Utilization of Traffic Simulation Models: How Do We Make Them Reliable Tools

This paper, firstly, describes the current status of the utilization of traffic simulation models. Evaluation for the model’s application in Japan was based on a questionnaire survey. Secondly, the Best Practice Manual for Simulation Application, which is currently being developed, is discussed. In addition some exerts from the manual in regards to addressing the issues of simulation application are presented: i.e. i) understanding the models’ nature through verification and validation; ii) OD estimation from vehicle counts; iii) model parameter calibration; and iv) indices to measure the reproducibility. Finally this paper introduces the Clearing House of Traffic Simulation Models. These models promote simulation utilization.

Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow

2019

The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver's visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MID...

Fundamentals of Traffic Simulation

International Series in Operations Research & Management Science, 2010

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Impact of Differences in Driver-Desired Speed on Steady-State Traffic Stream Behavior

Transportation Research Record, 2006

The paper analyzes the steady-state behavior of car-following models within state-of-the-practice commercial traffic simulation software. The car-following models are classified based on their uncongested regime steady-state behavior into two categories. Apart from the INTEGRATION software that employs the Van Aerde car-following model, the research demonstrates that all stateof-the-practice traffic simulation software assume a constant desired speed that is insensitive to the flow level within the uncongested regime. The paper then quantifies the effect of speed variability, as a common approach to model driver differences with respect to desired speed, on the steadystate traffic stream behavior. The paper not only demonstrates that the speed variability has a significant impact on the speed-at-capacity, but also develops procedures for the calibration of the steady-state relationship while accounting for the effects of speed variability. Finally, the effectiveness and validity of the proposed procedure is demonstrated through an example illustration.

A car following model for traffic flow simulation

2016

The traffic flow microscopic modeling is basically important for the development of specific tools for understanding, simulating and controlling urban transportation systems. Car-following models have been developed to describe the dynamical characteristics of the moving vehicles. In this paper, we present a microscopic car following model based on the consideration of the driving behavior on a single-lane road. With this model, we propose an approach which permits to take into account the phenomenon of anticipation in driver behavior. A comparative study with the optimal velocity model is done. The proposed modeling approach is validated by simulation. The numerical simulation shows that the model can improve the representation of traffic flow.

Analysis of the influence of car-following input parameters on the modelled travelling time

Tehnicki Vjesnik

The calibration process is a basic condition of traffic model application in local conditions. The choice of input parameters, which are used in calibration process, influences the success of the calibration process itself; therefore the goal is to choose parameters with a larger influence on the modelling process. This paper offers a detailed analysis of car-following input parameters and their influence on the modelled travelling time. The experimental basis was a one-lane roundabout, and the tool used for traffic simulation was the VISSIM microsimulation traffic model. The results show that the car-following input parameters should be a part of the set of input parameters which will enter the process of calibration. The examined car-following input parameters affect the capacity of intersections and results show that it is necessary to revise the range of input values of one of the observed car-following input parameters.