Issues with work zone free flow speed computation in 6th edition HCM and proposed improvements

2021 ◽  
pp. 1-12
Author(s):  
Hongjae Jeon ◽  
Rahim F. Benekohal
2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Othman Che Puan ◽  
Muttaka Na’iya Ibrahim ◽  
Usman Tasiu Abdurrahman

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.


Author(s):  
Shradha S. Zanjad

A flyover is a bridge constructed along an intersecting highway over an at-grade intersection. It allows two –direction traffic to flow at free flow speed on the bridge. The flyover is one of the methods for solving traffic problems at at-grade junctions on highways including capacity, congestion, long delay and queue length. Traffic signalization at the upgraded intersection often uses the same fixed time control plans, even after the installation of a flyover over the intersection. Most of the flyovers in India are constructed at the junctions on highway bypasses of big cities. The present work deals with a efficient scheduling of flyover at the grade intersection under the mixed traffic environment. From the results and the modeling carried out in the “SIDRA Intersection” software different points are observed. The present work consists of the Proposed Intersection at Rajkamal Square, Amravati.


2016 ◽  
Vol 15 (1) ◽  
pp. 95-106
Author(s):  
Gito SUGIYANTO

Traffic congestion is one of the significant transport problems in many cities in developing countries. Increased economic growth and motorization have created more traffic congestion. The application of transportation demand management like congestion pricing can reduce congestion, pollution and increase road safety. The aim of this research is to estimate the congestion pricing of motorcycles and the effect of a congestion pricing scheme on the generalized cost and speed of a motorcycle. The amount of congestion pricing is the difference between actual generalized cost in traffic jams and in free-flow speed conditions. The analysis approach using 3 components of generalized costs of motorcycle: vehicle operating, travel time and externality cost (pollution cost). The approach to analyze the pollution cost is marginal-health cost and fuel consumption in traffic jams and free-flow speed conditions. The value of time based on Gross Regional Domestic Product per capita in Yogyakarta City in October 2012. The simulation to estimate the effect of congestion pricing using Equilibre Multimodal, Multimodal Equilibrium-2 (EMME-2) software. The results of this study show that while the free-flow speed of a motorcycle to the city of Yogyakarta is 42.42 km/h, with corresponding generalized cost of IDR1098 per trip, the actual speed in traffic jams is 10.77 km/h producing a generalized cost of IDR2767 per trip, giving a congestion pricing for a motorcycle of IDR1669 per trip. Based on the simulation by using EMME-2, the effect of congestion pricing will increase on vehicle speed by 0.72 to 8.11 %. The highest increase of vehicle speed occurred in Malioboro Street at 2.26 km/h, while the largest decrease occurred in Mayor Suryotomo Street at north-south direction at 1.07 km/h. Another effect of this application for motorcycles users will decrease the generalized cost by 1.09 to 6.63 %.


2014 ◽  
Vol 26 (2) ◽  
pp. 121-127 ◽  
Author(s):  
Ivan Lovrić ◽  
Dražen Cvitanić ◽  
Deana Breški

Free flow speed is used as a parameter in transportation planning and capacity analysis models, as well as speed-flow diagrams. Many of these models suggest estimating free flow speed according to measurements from similar highways, which is not a practical method for use in B&H. This paper first discusses problems with using these methodologies in conditions prevailing in B&H and then presents a free flow speed evaluation model developed from a comprehensive field survey conducted on nine homogeneous sections of state and regional roads.


2012 ◽  
Vol 54 ◽  
pp. 628-636 ◽  
Author(s):  
Mario De Luca ◽  
Renato Lamberti ◽  
Gianluca Dell’Acqua
Keyword(s):  

2014 ◽  
Vol 70 (4) ◽  
Author(s):  
Nordiana Mashros ◽  
Johnnie Ben- Edigbe ◽  
Sitti Asmah Hassan ◽  
Norhidayah Abdul Hassan ◽  
Nor Zurairahetty Mohd Yunus

This paper explores the impact of various rainfall conditions on traffic flow and speed at selected location in Terengganu and Johor using data collected on two-lane highway. The study aims to quantify the effect of rainfall on average volume, capacity, mean speed, free-flow speed and speed at capacity. This study is important to come out with recommendation for managing traffic under rainfall condition. Traffic data were generated using automatic traffic counters for about three months during the monsoon season. Rainfall data were obtained from nearest surface rain gauge station. Detailed vehicular information logged by the counters were retrieved and processed into dry and various rainfall conditions. Only daylight traffic data have been used in this paper. The effect of rain on traffic flow and speed for each condition were then analysed separately and compared. The results indicated that average volumes shows no pronounce effect under rainfall condition compared to those under dry condition. Other parameters, however, show a decrease under rainfall condition. Capacity dropped by 2-32%, mean speed, free-flow speed and speed at capacity reduced by 3-14%, 1-14% and 3-17%, respectively. The paper recommends that findings from the study can be incorporated with variable message sign, local radio and television, and variable speed limit sign which should help traffic management to provide safer and more proactive driving experiences to the road user. The paper concluded that rainfall irrespective of their intensities have impact on traffic flow and speed except average volume.


2020 ◽  
Vol 12 (8) ◽  
pp. 3445
Author(s):  
Lee Vien Leong ◽  
Tuti Azmalia Azai ◽  
Wins Cott Goh ◽  
Mohammed Bally Mahdi

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.


Author(s):  
Alberto M. Figueroa Medina ◽  
Andrew P. Tarko

The mean free-flow speed and its variability across drivers are considered important safety factors. Despite a large body of research on operating speeds, there is still much to learn about the factors of free-flow speeds, especially on tangent segments of two-lane rural highways. The roadway factors of speed dispersion across drivers are largely unknown. Also, the use of the entire free-flow speed distribution suggested by other authors has not yet been addressed. Consequently, the existing models are not aimed to evaluate the speed variability at a site. This paper presents free-flow speed models that identify factors of mean speed and speed dispersion on tangent segments and horizontal curves of two-lane rural highways. Ten highway variables, six of them functioning as both mean speed and speed dispersion factors, were identified as speed factors on tangent segments. Four highway and curve variables, two of them functioning as both mean speed and speed dispersion factors, were identified as speed factors on horizontal curves. The developed free-flow speed models have the same prediction capabilities as traditional ordinary-least-squares models developed for specific percentile speeds. The advantages of the developed models include predicting any user-specified percentile, involving more highway characteristics as speed factors than traditional regression models, and separating the impacts on mean speed from the impacts on speed dispersion.


Author(s):  
Nipjyoti Bharadwaj ◽  
Praveen Edara ◽  
Carlos Sun ◽  
Henry Brown ◽  
Yohan Chang

What effect does work activity type have on traffic conditions in a work zone? This question has still not been answered satisfactorily in practice. Without knowing the true effect a work activity has on traffic, practitioners are forced to make assumptions while scheduling work. This paper attempts to answer this question by studying the traffic flow characteristics, that is, traffic speed versus flow curves, capacity reduction factors, and free-flow speed reduction factors, for various activities related to construction and maintenance. The importance of the speed–flow curves and reduction factors for work zone planning is also stressed in the latest edition of the Transportation Research Board’s Highway Capacity Manual. This manual recommends capacity and speed reduction factors for work zones, yet does not include specific guidance for including the impact of work activities. Thre e traffic stream models, Gipps, Newell–Franklin, and Van Aerde, were calibrated using field data from St. Louis, Missouri. The Van Aerde model fitted the field data the best as compared to the other two models. Using the Van Aerde model-generated speed–flow curves, it was found that the capacity for bridge-related activities varied from 1,416 vehicles per hour per lane (vphpl) to 1,656 vphpl and for pavement-related activities from 1,120 vphpl to 1,728 vphpl. The capacity reduction factor for different work activities was found to be in the range 0.68 to 0.95, whereas the free-flow speed reduction factor was found to be in the range 0.78 to 1.0. The methodology proposed in this paper contributes toward the development of practitioner guidance and incorporation of work activity effects into traffic impact assessment tools.


Sign in / Sign up

Export Citation Format

Share Document