Development of Capacity Estimation Models for Multi-lane Roads under Heterogeneous Traffic Conditions

Abstract

The objective of this study is to develop capacity models to estimate the traffic carrying capacity of multi-lane roads with heterogeneous traffic flows. Since capacity is an important parameter in traffic engineering studies, it is vital that it is accurately estimated. Most of the current capacity estimation methodologies available are developed based on homogeneous traffic flows and hence not conducive for use in heterogeneous traffic conditions observed in Sri Lanka. Therefore, this study is done to fulfill the requirement of a capacity estimation model for this purpose. Fifty midblock sections were surveyed using manual flow data collection methods and a novel Google Application Program Interface (API) based method for speed data collection. Based on the collected data, capacity values were developed following the fundamentals of traffic flow. Regression models were built to estimate four-lane and six-lane capacity values based on roadway characteristics such as effective lane width, access point density, median type, and built environment condition. Separate models were developed because the impact these characteristics have on four-lane and six-lane roads are different. The models showed good fit with R2 values of 0.81 and 0.86 for four-lane and six-lane roads, respectively. The base capacity value of a four-lane urban road was estimated to be 2044 pcu/h/l and for a six-lane sub-urban road section 2108 pcu/h/l. The outcomes of this study can be used to develop capacity guidelines in countries with heterogeneous traffic conditions for capacity estimation.