REVALIDATION OF Q=KV FOR MIXED TRAFFIC FLOW

Abstract

Density is one of the fundamental macroscopic characteristics of the traffic stream. Density is used as the measure of effectiveness for road network performance and as a means ofjudging level of service (LOS) of the roads, therefore its accurate measurement is important. In practice, density is usually calculated by measuring flow and speed using the fundamental traffic equation. Fundamental traffic equation was derived under few unrealistic assumptions, none of which are valid in case of mixed traffic flow. This necessitates to find other methods to measure density which can be used under heterogeneous traffic situation as prevalent in India. This paper presents a critical review of four different methods for measuring density, namely x-t method, n-t method, HCM method, time and area occupancy method and also proposes a new method. Analysis on field data using n-t method establishes the validity of fundamental equation even in mixed traffic flow. N-t method gives accurate value of density and is quite simple and quick. Results of 14CM method are highly misleading under mixed traffic situation. Area occupancy gives better result as compared to time occupancy under heterogeneous traffic situation but both of these methods are less accurate than n-t method. Proposed method is a modification of 1-1CM method and it shows that as the number of observations are increased during study period, error in density measurement goes on reducing exponentially. Density value measured by proposed method is sensitive to a number of factors such as trap length used for the study, traffic volume and traffic composition. To further explore the effect of these parameters on density measurement, simulation was performed. Results shows that Minimum trap length reduces with increase in traffic volume. Percentage error in density measurement also shows a declining trend with volume. Error in density measurement increases as the share of two-wheelers go up and decreases with increase in share of heavy vehicles and light commercial vehicles.