Saturation flow is a fundamental performance measure parameter used for the design of intersections. However, in mixed traffic conditions, the evaluation of saturation flow is more sensitive due to heterogeneous traffic where vehicles are travelling in the same right of way without any lane separation. In such cases, the passenger car unit (PCU) plays a major role in analysing heterogeneity using an equivalent value for each vehicle. This paper presents a novel approach using the optimisation technique to determine PCU values and saturation flow for mixed traffic streams. Field data were collected at six signalised intersections in three Indian cities. The optimisation technique produced reasonable PCU values and an accurate estimation of saturation flow of 1906 PCUs/h. The saturation flow prediction model was developed using the multi-linear regression technique as per Pearson's correlation between saturation flow and vehicle compositional share. The developed saturation flow model was validated using field data from another site and the predicted value was in good agreement with the observed value. Finally, the predictive model was used to analyse the impact of traffic composition on saturation flow in mixed traffic streams.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.