1 Abstract—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 MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation. Keywords—Area-based traffic, car-following model, micro- simulation, stochastic modeling. I. INTRODUCTION ICROSCOPIC simulation has long been a topic of research. Numerous microscopic simulation models have been developed to advance the microscopic flow theory [1]. All microsimulation models require a set of parameters. In practice, there is no hard and fast rule to determine what values of parameters of models accurately represent an individual driver’s behavior. Overall, in many cases, the model parameters are not estimated rigorously due to the limited availability of details vehicle trajectory data [2]. However, the importance of modeling estimated parameters in a microscopic simulation cannot be overlooked. This paper focuses on the stochastic modeling for parameters of MIDM in area-based traffic. In area-based traffic which is frequently termed as non-lane based traffic in the literature of traffic flow, modeling drivers generally ignore the lane markings and perceive the entire road space while progressing longitudinally. The traditional car-following (CF) for longitudinal and lane changing (LC) for lateral movements N. C. Sarkar is with the School of Civil Engineering and Built Environment, Queensland University of Technology, Australia (corresponding author, e-mail: nikhilchandra.sarkar@hdr.qut.edu.au). A. Bhaskar is with the School of Civil Engineering and Built Environment, Queensland University of Technology, Australia (e-mail: ashish.bhaskar@qut.edu.au). Z. Zheng is with the School of Civil Engineering, The University of Queensland, Australia (e-mail: zuduo.zheng@uq.edu.au). models are not directly applicable in this traffic regime. Recently such system has gained interest, and numbers of the simple and modified models are proposed for modeling the area-based traffic. For instance, [3] refers a simulation framework for modeling area-based heterogeneous traffic flow, [4] refers the strip-based space discretization framework for modeling the driving behaviors of non-lane based mixed traffic and the latent leader acceleration model is proposed in [5] for modeling driving behavior in weak lane discipline. The driving behavior in area-based heterogeneous traffic has significantly different from the lane-based traffic. The subject vehicle frequently changes its lateral position in different lanes while progressing longitudinally. The dynamics of such vehicles define the variability of the state of traffic (speed and density) being experienced by the subject vehicle. Such variability influences the lateral and longitudinal movements of the subject vehicles, i.e. it follows the current direction of motion or move laterally (refer to [6] for details of modeling the area-based traffic in two steps approach in sequential order such as area selection using a discrete choice framework and vehicle movement modeling with a modified CF model). Firstly, a discrete choice modeling framework is developed for area-based traffic flow in terms of alternative selection to microscopically capture the dynamic of the subject vehicle in presence of the other mixed vehicles in its choice space from the visual perception area. The choice space of the subject vehicle is divided by numbers of realistic radial cones considering the possible moving directions of the subject vehicle in the next time step that forms the alternatives for his decision. The modeling framework consisted of alternatives from choice space of the driver’s visual perception area, attributes of the alternatives and modeling the selection of an alternative. Secondly, the vehicle following behavior model is developed to simulate the next position of the subject vehicle along the direction of the selected alternative. The intelligent driver model (IDM) [7] is modified to incorporate such driving maneuverability in area-based traffic condition, and the model is known as the MIDM. Based on the information that is available in data, the realistic bounds for each parameter of MIDM are defined for an individual vehicle from randomly selected subject vehicles. A univariate dataset is developed by calibrating the parameters of MIDM. This paper focuses on the modeling of parameters of MIDM. The purpose of this paper is to provide a robust simulation framework for the parameters of a microscopic simulation model in area-based traffic. N. C. Sarkar, A. Bhaskar, Z. Zheng Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow M World Academy of Science, Engineering and Technology International Journal of Transport and Vehicle Engineering Vol:13, No:3, 2019 137 International Scholarly and Scientific Research & Innovation 13(3) 2019 ISNI:0000000091950263 Open Science Index, Transport and Vehicle Engineering Vol:13, No:3, 2019 waset.org/Publication/10010117