The desired speed that drivers can drive without being obstructed or influenced by other road users is characterized as free-flow speed. However, free-flow speed can be influenced by other factors such as the characteristics of the vehicle, driver, road conditions, weather, and speed limits. Due to the country’s heterogeneous traffic conditions, this study aims to develop and assess free-flow speed models based on different vehicle classes and road characteristics in Malaysia. Data were sampled at 16 sites of multilane highways in Malaysia. Analyses of free-flow speed were conducted based on individual and grouped vehicle classes. Subsequently, multiple regression analyses were conducted based on these grouped vehicle classes to develop free-flow speed models. The findings show that the model with the grouping of all vehicles, which includes heavy vehicles and motorcycles, is the most suitable model as it yields the best results based on the performance indicators. The development of a free-flow speed model based on local traffic conditions, which can accurately estimate free-flow speed without having to conduct field measurements, is essential for saving time and costs in data collection. The findings from this study will contribute to improving the design of multilane highways and, ultimately, ensuring the sustainable environment of road networks.
Volume delay functions (VDFs) are mathematical relationships used by the traffic allocation step of demand forecasting models to take into account the effect of increased traffic flow on the time spent to travel each possible route between different travel sources and destinations. The VDF is usually applied in static traffic assignment to describe the resultant link travel times, as a function of flow and capacity and free-flow travel time. This study aims to investigate the interface between the delay functions used by demand forecasting models and the highway capacity manual (HCM) model flow-speed relationships. The most commonly used VDFs in transport demand modeling packages in the literature were identified. The Bureau of Public Roads (BPR), conical functions (CF), Akçik and Troutbeck function (ATF), and delay logistics function (LF) were described. The four VDFs and the current HCM models were calibrated for the Iraqi road environment, and their compatibilities were examined. Results show that the best adjustments were obtained using the BPR function (quadratic error 0–0.012) and LF (quadratic error 0–0.002). The roles of CF and ATF were used with care, as both appear to neglect the delay in the condition of small to medium traffic patterns typical to country roads. Particularly, in response to single-lane roads, the LF has proven to be useful due to its potential to represent significant delays for low traffic flows and simultaneously produce more delays in congestion conditions; furthermore, the effect of flow as well as intersection spacing is obviously nonlinear. As flow reaches 600 pcu/h/lane, running time increases quickly. With more intersections per kilometer, the impact is obviously greater.
Highways and freeways usually experience severe traffic congestion due to the presence of toll plazas which is considered as a bottleneck. In recent years, traffic engineers around the world have utilised microscopic traffic simulation models as tools to evaluate the performance of selected freeway facilities based on known traffic pattern data. This study attempts to analyse the performance of toll plaza by utilizing the microscopic traffic simulation software VISSIM 6.0, based on two different output measures, namely: average queue length and average delay time. At the selected toll plaza, data are collected at toll booths for all three modes of payments, which are: cash mode, Touch n Go, and Smart TAG. Therefore, this study aims to build a microscopic traffic simulation model that is capable of analysing the behaviour of vehicles at toll plaza based on the mentioned output measures for each mode of payment and also to determine the type of payment mode that has the most significant impact on the overall performance of toll plazas and ultimately, to understand the causes of congestion at toll plaza.
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