Abstract
The heterogeneity of traffic and the lack of lane discipline on the roads in India and other developing countries add complexity to the analysis and modeling of traffic. It is generally believed that it is important to take heterogeneity into account in traffic modeling. The aim of the present study is to check the validity of this assumption by analyzing the effect of incorporating heterogeneity in a macroscopic level traffic flow analysis. The application considered is real-time congestion analysis on Indian roads. Traffic density is considered as the congestion indicator. The measurement of density is difficult since it is a spatial parameter. It is usually estimated from other traffic parameters that can be readily measured using available sensors. A model-based estimation scheme using Kalman filtering has been employed to estimate traffic density. A non-continuum macroscopic model was attempted based on the lumped parameter approach. All the traffic variables were quantified without considering traffic lanes in order to take into account the lack of lane discipline. The effect of heterogeneity has been studied by incorporating static values of Passenger Car Units (PCU), dynamic values of Two Wheeler Units (TWU) and considering different classes of vehicles explicitly in the modeling process. The proposed estimation schemes without and with heterogeneity have been compared. The results have been corroborated using data collected from a road stretch in Chennai, India. The study shows that the significance of incorporating heterogeneity into the modeling of mixed traffic at the macroscopic level was not very significant.
Highlights
Analysis and modeling of traffic flow is essential for understanding the traffic flow phenomena and for planning, design and management of transportation systems
The performance of all these estimation schemes were quantified by calculating the Mean Absolute Percentage Error (MAPE) given by:
Traffic flow conditions prevailing in India and many other developing countries are highly complex with its heterogeneity and lack of lane discipline making analysis and modeling of traffic difficult
Summary
Analysis and modeling of traffic flow is essential for understanding the traffic flow phenomena and for planning, design and management of transportation systems. The heterogeneous traffic conditions existing in India and other developing countries are highly complex and differ from the homogeneous and lane disciplined traffic seen in developed countries. Modeling of heterogeneous traffic is challenging due to the typical features that characterize a heterogeneous system such as the presence of several vehicle types and the absence of lane discipline. It is assumed that to characterize such a system with reasonable accuracy, it is essential to incorporate heterogeneity into the modeling process. To incorporate the effect of heterogeneity, the common approach is to use passenger car equivalents. There are no reported systematic studies analyzing the effect of this approach in the performance of traffic flow models
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