COMPARATIVE EVALUATION OF THE MOVING CAR METHOD FOR TRAFFIC DATA COLLECTION ON MULTILANE HIGHWAYS
DOI:
https://doi.org/10.11113/jurnalteknologi.v87.22806Keywords:
Moving car method, traffic volume, Speed, travel time, comparison and modelingAbstract
Collecting traffic flow data is essential for most traffic studies to analyze and evaluate the performance of systems that provide safe trips for people and goods on highways. There are several methods for collecting traffic data. The moving car method (MCM) calculates traffic volume, speed, and travel time simultaneously, while stationary methods, such as camera recordings or radars, observe these data separately. This research aims to use both data collection methods on six segments of urban multi-lane highways to determine the accuracy of the moving car method compared to traditional methods. Additionally, it seeks to model a relationship between these methods to facilitate data collection using MCM for more accurate results. The results indicate no significant difference between the two methods, as the T statistic is less than the critical T in the t-test results. The models show low values of RMSE for the relationships between observed volume, arithmetic and harmonic mean speed, and arithmetic and harmonic means of travel time obtained by stationary methods and these data calculated by MCM. These models can be used with MCM for the study area.
References
P. V. Suvin and C. Mallikarjuna. 2018. Modified Generalized Definitions for the Traffic Flow Characteristics under Heterogeneous, No-Lane Disciplined Traffic Streams. Transp. Res. Procedia. 34: 75–82. Doi: 10.1016/j.trpro.2018.11.016.
S. Salini, S. George, and R. Ashalatha. 2016. Effect of Side Frictions on Traffic Characteristics of Urban Arterials. Transp. Res. Procedia. 17: 636–643. Doi: 10.1016/j.trpro.2016.11.118.
Knoop, V., Hoogendoorn, S.P., van Zuylen, H. 2009. Empirical Differences Between Time Mean Speed and Space Mean Speed. In: Appert-Rolland, C., Chevoir, F., Gondret, P., Lassarre, S., Lebacque, J. P., Schreckenberg, M. (eds). Traffic and Granular Flow ’07. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77074-9_36.
S. Wijayaratna. 2015. Impacts of on-street Parking on Road Capacity. ATRF 2015 - Australas. Transp. Res. Forum 2015. Proc. 1–15.
L. V. Leong, T. A. Azai, W. C. Goh, and S. A. M. Shafie. 2019. Development and Assessment of Free-flow Speed Models based on Different Methods of Measurements for inter Urban Multilane Highways in Malaysia. J. Appl. Eng. Sci. 17(3): 256–263. Doi: 10.5937/jaes17-21205.
A. Al-Kaisy and S. Karjala. 2008. Indicators of Performance on Two-lane Rural Highways: Empirical Investigation. Transp. Res. Rec. 2071: 87–97. Doi: 10.3141/2071-11.
J. G. Wardrop and G. Charlesworth. 1954. A Method of Estimating Speed and Flow of Traffic from a Moving Vehicle. Proc. Inst. Civ. Eng. 3(1): 158–171. Doi: 10.1680/ipeds.1954.11628.
W. J. Mortimer. 1957. Moving Vehicle Method of Estimating Traffic Volumes and Speeds. 14–26. [Online]. Available: http://onlinepubs.trb.org/Onlinepubs/hrbbulletin/156/156-002.pdf.
F. Alhomaidat and S. Ardekani. 2015. A Statistical Comparison of Traffic Measurements from the Moving versus Stationary Observer Methods. J. Transp. Technol. 05(04): 204–213. Doi: 10.4236/jtts.2015.54019.
M. Abdulrahman, H. S., Almusawi, A. A. and Abubakar. 2017. Comparative Assessment of Macroscopic Traffic Flow Properties Estimation Methods: A Case for Moving Car Observer Method. Eng. Sci. Technol. Int. Res. J. 1(2): 11–15.
A.- Mulligan and A. Nicholson. 2002. Uncertainty in Traffic Flow Estimation Using the Moving-Observer Method. Inst. Prof. Eng. New Zeal. Transp. Group. Tech. Conf. Pap. 2002. 12p.
M. J. Solanki, F. S. Umrigar, L. B. Zala, and A. A. Amin. 2016. Application of Moving Car Observer Method for Measuring Travel Time, Delay & Vehicle Flow under Heterogeneous Traffic Condition of C.B.D. Area: Case Study of Surat-Rajmarg (Chowk to Delhi Gate). Int. J. Curr. Eng. Technol. 6(3): 799–803. [Online]. Available: http://inpressco.com/category/ijce.t
C. A. O’flaherty and F. Simons. 1972. An Evaluation of the Moving Observer Method of Measuring Traffic Speeds and Flows. An Evaluation of the Moving Observer Method of Measuring Traffic Speeds and Flows, Melbourne, Victoria Australia.
O. C. Puan, M. N. iya Ibrahim, and U. T. Abdurrahman. 2014. Application of Moving Car Observer Method for Measuring Free Flow Speed on Two-lane Highways. J. Teknol. (Sciences Eng.). 69(6): 15–19. Doi: 10.11113/jt.v69.3233.
Barua, Saurav & Das, Anik & Hossain, Md. Julfiker. 2015. Estimation of Traffic Density to Compare Speed-Density Models with Moving Observer Data. 4: 471-474. Doi: 10.15623/ijret.2015.0408080.
N. Delhi, S. P. Scientist, and N. Delhi. 2014. Roadway Capacity Estimation for Multi-Lane Inter- Urban Highways in India.
National Academies of Sciences, Engineering, and Medicine. 2022. Highway Capacity Manual 7th Edition: A Guide for Multimodal Mobility Analysis. Washington, DC: The National Academies Press. https://doi.org/10.17226/26432.
P. D. Bruce Douglas Greenshields, C. E. and P. D. Frank Mark Weida. 1952. Highway Traffic Analyses. Washington, DC.
S. M. Ross. 2014. Introduction to Probability and Statistics for Engineers and Scientists. Fifth Edition. Doi: 10.1016/C2013-0-19397-X.
M. Guerrieri, G. Parla, and R. Mauro. 2019. Traffic Flow Variables Estimation: An Automated Procedure based on Moving Observer Method. Potential Application for Autonomous Vehicles. Transp. Telecommun. 20(3): 205–214. Doi: 10.2478/ttj-2019-0017.
M. Guerrieri and G. Parla. 2021. Deep Learning and Yolov3 Systems for Automatic Traffic Data Measurement by Moving Car Observer Technique. Infrastructures. 6(9). Doi: 10.3390/infrastructures6090134.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
