Comparative Study of Density over Time by Several Approaches Using Individual and Sample Data in the Mixed Traffic

Fadly Arirja Gani, Toshio Yoshii, Shinya Kurauchi

Abstract


At the macroscopic perspective, traffic analysis requires the knowledge of Fundamental Diagram, which involves the relationship between the variables of density, flow, and speed. As one of the macroscopic traffic flow variables, density can be derived by several approaches. At first, the density of traffic was measured over space, which difficult to be collected mainly in the long section of the road. Therefore, the density variable was simply derived from the fundamental relation of macroscopic traffic flow variable. By this method, the individual speed and flow variable are required in the local measurement. Both traffic density and flow will apply the concept of PCU, which refers to the Indonesian Highway Capacity Manual, 1997 to consider the different characteristic of the vehicle. In the mixed traffic of developing countries, providing traffic data was difficult due to the limitation of the traffic sensor infrastructures. Frequently, providing density variable relies on the sample data for speed analysis. In the present study, the estimation of density will focus on the local measurement over a time interval. By using individual data, density is proposed to be measured directly over time, in which the equation can be modified to utilize the sample data. The number of sample for speed analysis will be varied to know the accuracy and the performance of each approach in the density estimation of mixed traffic. Several approaches for density estimation will be summarized and compared each other. Theoretically, the estimated density which measured over time and space by using individual data can provide the most appropriate result. So, this estimated density will be established as an actual density throughout the study. Then, the performance of each approach either using individual or sample data will be evaluated upon the actual traffic density by mean absolute percentage error (MAPE). The result shows by using the same trap length to measure the speed, the existing and the proposed approaches provide a good estimation of density either by utilizing individual data or sample data of the vehicle speed. This result was indicated by the MAPE value, which obtained under ten percent. Based on the further evaluation of the MAPE value, the performance of each approach was changed by utilizing the different category of data. In addition, estimation of traffic density which utilizes the sample data of vehicle speed has good reliability.

Keywords


density; mixed traffic; passenger car unit; local measurement; time interval

Full Text:

PDF

References


Gani FA, Yoshii T, Kurauchi S. The Suitable Index of Flow and Density in the Mixed Traffic. IOP Conf Ser Earth Environ Sci [Internet]. 2017 Jun [cited 2017 Jun 23];71(1):12015. Available from: http://stacks.iop.org/1755-1315/71/i=1/a=012015?key=crossref.0626bbb7f39fd01816a857fa32994145

Chari SR, Badarinath KM. Study of mixed traffic stream parameters through time lapse photography. Highw Res Bull (Indian Road Congr Highw Res Board) [Internet]. 1983 [cited 2016 Nov 25];20:57–83. Available from: http://www.safetylit.org/citations/index.php?fuseaction=citations.viewdetails&citationIds%5B%5D=citjournalarticle_486942_38

Mallikarjuna C, Rao KR. Area occupancy characteristics of heterogeneous traffic. Transportmetrica [Internet]. 2006 [cited 2015 Aug 27];2(3):223–36. Available from: http://www.tandfonline.com/doi/abs/10.1080/18128600608685661

Arasan VT, Dhivya G. Methodology for Determination of Concentration of Hetrogeneous Traffic. J Transp Syst Eng Inf Technol [Internet]. 2010;10(4):50–61. Available from: http://dx.doi.org/10.1016/S1570-6672(09)60052-0

Gani FA, Yoshii T, Kurauchi S. The Effect of Heterogeneity of Vehicle Size on the Fundamental Diagram in Mixed Traffic. (Case Study: Makassar Traffic on Urip Sumoharjo Street). In: Proceeding of the International Conference of Transdiciplinary Research on Environmental Problem in Southeastern Asia. Makassar, Indonesia: Penerbit ITB; 2014. p. 95–104.

Alhassan HM, Ben-Edigbe J. Effect of Rainfall on Traffic Stream Characteristics during Peak and Non-Peak Periods. Int J Adv Sci Eng Inf Technol [Internet]. 2012 [cited 2017 Jul 19];2(2):162–7. Available from: http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=177

Alhassan HM, Ben-Edigbe J. Effect of Rain on Probability Distributions Fitted to Vehicle Time Headways. Int J Adv Sci Eng Inf Technol [Internet]. 2012 [cited 2017 Jul 23];2(2):144–50. Available from: http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=173

Alhassan HM, Ben-Edigbe J. Highway Capacity Loss Induced by Rainfall. Int J Adv Sci Eng Inf Technol [Internet]. 2011 [cited 2017 Jul 23];1(6):635–8. Available from: http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=127

Mane A, Kumar P, Arkatkar S, Bhaskar A, Joshi G. Comparative Evaluation of Density Estimation Methods on Expressway : A Case Study Delhi-Gurgaon Expressway.

Bharadwaj N, Kumar P, Mane A, Arkatkar S. Comparative Evaluation of Density Estimation Methods on Different Uninterrupted Roadway Facilities : Few Case Studies in India. Transp Dev Econ. 2017;3(1):3.

Highway Research Board. Special Report 87. In: Highway Capacity Manual. Washington D. C.: National Research Council; 1965.

Papageorgiou M, Vigos G. Relating time-occupancy measurements to space-occupancy and link vehicle-count. Transp Res Part C Emerg Technol. 2008;16(1):1–17.

Edie LC. Discussion of Traffic Stream Measurements and Definitions. In: Proceedings of the Second International Symposium on the Theory of Traffic Flow. Paris: OECD; 1965. p. 139–154.

Logghe S. Dynamic modeling of heterogeneous vehicular traffic. Fac Appl Sci Kathol Univ Leuven, Leuven [Internet]. 2003 [cited 2015 Nov 29]; Available from: http://www.kuleuven.be/traffic/dwn/P2003B.pdf

Wardrop J. Some theoretical aspects of road traffic research communication networks. ICE Proc Eng Div. 1952;2:325–62.

Gerlough DL, Huber MJ. Traffic flow theory: a monograph. 1975. p. 238.

Tiwari G, Fazio J, Gaurav S, Chatteerjee N. Continuity Equation Validation for Nonhomogeneous Traffic. J Transp Eng [Internet]. 2008;134(3):118–27. Available from: http://ascelibrary.org/doi/10.1061/%28ASCE%290733-947X%282008%29134%3A3%28118%29

Chandra S, Kumar U. Effect of Lane Width on Capacity under Mixed Traffic Conditions in India. J Transp Eng. 2003;129(2):155–60.

Directorate General Bina Marga. Indonesian Highway Capacity Manual (IHCM). In Jakarta: Directorate General of Highway Ministry of Public Works; 1997.




DOI: http://dx.doi.org/10.18517/ijaseit.8.1.4172

Refbacks

  • There are currently no refbacks.



Published by INSIGHT - Indonesian Society for Knowledge and Human Development