IJSTR

International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
0.2
2019CiteScore
 
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020

CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT

IJSTR >> Volume 9 - Issue 9, September 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Volumetric Traffic Count Survey And Statistical Analysis On Baraki Intersection Kabul Afghanistan

[Full Text]

 

AUTHOR(S)

Rustam Hafizyar, Sayed Dawood Karimi

 

KEYWORDS

Traffic Survey, Traffic History, Manual Count, Automatic Counts, Intersection surveying

 

ABSTRACT

the current paper is evaluated the traffic characteristics which is vital for selecting an appropriate geometric design of pavement. The traffic data includes traffic volume, traffic speed, and the percentage of trucks or other large vehicles. Traffic volume is an important basis for determining what improvements, if any, are required on a highway or street facility. Traffic volumes can be expressed in terms of average daily traffic or design hourly volumes. These volumes must be used to calculate the service flow rate, which is typically used for evaluations of geometric design alternatives. This study was found the variability of traffic volumes by vehicle classification. It is discussed the traffic volume in terms of statistics. The purpose of this study is to demonstrate how to estimate daily traffic volumes in peak hours which is selected 3-hour-vehicles counts and also identifying, collecting the data, and analyzing it. This study has counted more than 12179 vehicles for 3 hours for each observation period is 15 min. It is distributed as follows; 9035 cars, 137 taxies, 1710 Light vehicle, 755 heavy vehicles, 86 bus, 456 minibusses. It is found the percentage of cars 75% in one location site and it is selected the highest percentage of vehicles.

 

REFERENCES

[1]. Sinha KC, Bullock D, Hendrickson CT, Levinson HS, Lyles RW, Radwan AE, Li Z. Development of transportation engineering research, education, and practice in a changing civil engineering world. Journal of transportation engineering. 2002 Jul; 128(4):301-13.
[2]. Kinzer JP. Application of the probability to the problem of highway traffic. Proc. Inst. Traffic. Eng. 1934; 3:211.
[3]. Albright D. History of estimating and evaluating annual traffic volume statistics. Transportation Research Record. 1991; 1305:103-7.
[4]. Shelton W. Dispersion of highway traffic by periods. InHighway Research Board Proceedings 1938 (Vol. 1938). National Research Council (USA), Highway Research Board.
[5]. Adebisi O. Improving manual counts of turning traffic volumes at road junctions. Journal of transportation engineering. 1987 May; 113(3):256-67.
[6]. Watling DP, Maher MJ. A graphical procedure for analysing partial registration-plate data. Traffic engineering & control. 1988 Oct; 29(10).
[7]. Findley DJ, Cunningham CM, Hummer JE. Comparison of mobile and manual data collection for roadway components. Transportation Research Part C: Emerging Technologies. 2011 Jun 1; 19(3):521-40.
[8]. Zheng P, Mike M. An investigation on the manual traffic count accuracy. Procedia-Social and Behavioral Sciences. 2012 Jan 1; 43:226-31.
[9]. Wylie M. Automating the Collection of Turning Count Data at Signalized Intersections in Southampton. Traffic Engineering & Control. 2010 Dec; 51(11).
[10]. Jalihal S. Evaluation of automatic traffic counters under mixed traffic conditions. Journal of the Institution of Engineers (India), Part CV, Civil Engineering Division. 2005 Nov; 86(3):96-102.
[11]. Zhao M, Garrick NW, Achenie LE. Data reconciliation–based traffic count analysis system. Transportation research record. 1998; 1625(1):12-7.
[12]. Sapsford, R., & Jupp, V. (Eds.). (2006). Data collection and analysis. Sage
[13]. Sharma SC. Minimizing cost of manual traffic counts: Canadian example. Transportation Research Record. 1983; 905:1-7.
[14]. Roess RP, Prassas ES, McShane WR. Traffic engineering. Pearson/Prentice Hall; 2004.
[15]. Antoniou C, Balakrishna R, Koutsopoulos HN. A synthesis of emerging data collection technologies and their impact on traffic management applications. European Transport Research Review. 2011 Nov 1; 3(3):139-48.
[16]. Leduc G. Road traffic data: Collection methods and applications. Working Papers on Energy, Transport and Climate Change. 2008 Nov; 1(55):1-55.
[17]. Oh S, Ritchie SG, Oh C. Real-time traffic measurement from single loop inductive signatures. Transportation Research Record. 2002; 1804(1):98-106
[18]. Cheung SY, Coleri S, Dundar B, Ganesh S, Tan CW, Varaiya P. Traffic measurement and vehicle classification with single magnetic sensor. Transportation Research Record. 2005; 1917(1):173-81.
[19]. Lee, J. J., Wilkinson, S. R., Rosen, R. A., Krikorian, K. V., & Newberg, U.S. Patent No. 7,061,443. Washington, DC: U.S. Patent and Trademark Office (2006).
[20]. Zhang G, Avery RP, Wang Y. Video-based vehicle detection and classification system for real-time traffic data collection using uncalibrated video cameras. Transportation research record. 2007 Jan; 1993(1):138-47.
[21]. Elefteriadou L. An introduction to traffic flow theory. New York: Springer; 2014.
[22]. Golob TF, Recker WW, Alvarez VM. Freeway safety as a function of traffic flow. Accident Analysis & Prevention. 2004 Nov 1; 36(6):933-46.
[23]. Bierlaire M, Toint PL. Meuse: An origin-destination matrix estimator that exploits structure. Transportation Research Part B: Methodological. 1995 Feb 1; 29(1):47-60.
[24]. Mahama F. Study of vehicular traffic congestion in the Sekondi-Takoradi metropolis (Doctoral dissertation). (2012).