Cellular automata model for heterogeneous traffic

Abstract

Cellular Automata (CA) modelling is extended to study the heterogeneous traffic observed in developing countries. In heterogeneous traffic, the physical and mechanical characteristics of different vehicles vary widely which in turn leads to complex traffic behaviour resulting in no-lane discipline. This nature of the heterogeneous traffic is modelled with the help of an improved discrete CA model. A detailed description of the methodology used in developing the basic structure of the CA model is presented and the modified methodology is used to generate different traffic scenarios. From the results, it is observed that with the help of simple updating rules along with typical heterogeneous traffic characteristics of the region, this model is able to reproduce real traffic behaviour. An added advantage is that the modified structure of the CA model can also be used to extract some basic traffic characteristics which are useful in understanding the heterogeneous traffic behaviour. The simulation model is finally validated using the flow and occupancy relationship obtained from the field. IntroductionThere exists a need for traffic flow modelling in developing countries on account of the growth in personalized traffic. Since the past decade, and for many developing cities, traffic management schemes are gaining importance. The core of any traffic management scheme is a better understanding of the traffic behaviour. There exist several traffic models to study homogeneous traffic behaviour. However, since the traffic is heterogeneous in nature and vehicle characteristics vary widely, it is not known whether any conventional microscopic (car following) or macroscopic models are applicable to study traffic in developing countries.In spite of this, microscopic simulation models were developed to study the heterogeneous traffic and it was found that these models had Ch. Mallikarjuna and K.R. Rao 322limited applicability for traffic analysis and further, they required enormous computational effort. Moreover, interactions between different elements such as the road conditions, type of vehicle, and the driver were also explicitly considered in these simulations, though this could limit the applicability of these models for different traffic conditions. In most of the simulation models, either space or time or both are considered as continuous variables, and since these models involve numerous elements (various vehicle types, different road conditions etc.), they require immense computational time. The objective of this study is to achieve a better computational efficiency in modelling complex traffic systems for different scenarios.The model developed in the present study is based on the Nagel and Schreckenberg's (NS) approach (1992). In the NS model, interactions between different elements (vehicles, road and driver) were considered implicitly and even though this basic model could not reproduce all the observed traffic characteristics, it was however able to reproduce the trends observed in real traffic. The model has unde...

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