Application of Moving Car Observer Method for Measuring Free Flow Speed on Two-lane Highways

Abstract

There exists a need to evaluate the performance indicator that reflects the current level of service (LOS) of the subject facility to justify any decision making on expenditures to be made for improving the performance level of a road facility. Free-flow speed (FFS) is one of the key parameters associated with LOS assessment for two-lane highways. Application of a more realistic approach for assessing road’s performance indicators would result in better estimates which could in turn suggest the most appropriate decision to be made (for situations where upgrading is needed); especially, in terms of finance, materials and human resources. FFS is the driver’s desired speed at low traffic volume condition and in the absence of traffic control devices. Its estimation is significant in the analysis of two-lane highways through which average travel speed (ATS); an LOS indicator for the subject road class is determined. The Highway Capacity Manual (HCM) 2010 offers an indirect method for field estimation of FSS based on the highway operating conditions in terms of base-free-flow-speed (BFFS). It is however, recommended by the same manual that direct field FSS measurement approach is most preferred. The Malaysian Highway Capacity Manual (MHCM) established a model for estimating FFS based on BFFS, the geometric features of the highway and proportion of motorcycles in the traffic stream. Estimating FFS based on BFFS is regarded as an indirect approach which is only resorted to, if direct field measurement proved difficult or not feasible. This paper presents the application of moving car observer (MCO) method for direct field measurement of FFS. Data for the study were collected on six segments of two-lane highways with varying geometric features. FFS estimates from MCO method were compared with those based on MHCM model. Findings from the study revealed that FFS values from MCO method seem to be consistently lower than those based on MHCM model. To ascertain the extent of the difference between the FFS values from the two approaches, student t-statistics was used. The t-statistics revealed a P–value of less than 0.05 (P < 0.05) which implies that there is a statistically significant difference between the two sets of data. Since MCO method was conducted under low traffic flow (most desired condition for field observation), it can be suggested that MCO estimates of FFS represent the actual scenario. A relationship was therefore developed between the estimates from the two methods. Thus, if the MHCM model is to be applied, the measured value needs to be adjusted based on the relationship developed between the two approaches.