Yun, Ilsoo (E-mail : ilsooyun@ajou.ac.kr) Oh, Cheol (E-mail : cheolo@hanyang.ac.k) Ahn, Hyunkyung (E-mail : anhyunkyung@ajou.ac.kr) Kim, Kyunghyun (E-mail : kk6661@ajou.ac.kr) Han, Eum (E-mail : hano3106@ajou.ac.kr) Kang, Nam Won (E-mail : khcknw1@ex.co.kr) Yoon, Jung Eun (E-mail : yoon22@kict.re.kr) ABSTRACT PURPOSES : The control delay in seconds per vehicle is the most important traffic operational index to evaluate the level of service of signalized intersections. Thus, it is very critical to calculate accurate control delay because it is used as a basic quantitative evidence for decision makings regarding to investments on traffic facilities. The control delay consists of time-in-queue delay, acceleration delay, and deceleration delay so that it is technically difficult to directly measure it from fields. Thus, diverse analysis tools, including CORSIM, SYNCHRO, T7F, VISTRO, etc. have been utilized so far. However, each analysis tool may use a unique methodology in calculating control delays. Therefore, the estimated values of control delays may be different by the selection of an analysis tool, which has provided difficulties to traffic engineers in making solid judgments. METHODS : This study was initiated to verify the feasibility of diverse analysis tools, including HCM methodology, CORSIM, SYNCHRO, T7F, VISTRO, in calculating control delays by comparing estimated control delays with that measured from a field. RESULTS : As a result, the selected tools produced quite different values of control delay. In addition, the control delay value estimated using a calibrated CORSIM model was closest to that measured from the field. CONCLUSIONS : First, through the in-depth experiment, it was explicitly verified that the estimated values of control delay may depend on the selection of an analysis tool. Second, among the diverse tools, the value of control delay estimated using the calibrated microscopic traffic simulation model was most close to that measured from the field. Conclusively, analysts should take into account the variability of control delay values according to the selection of a tool in the case of signalized intersection analysis. Keywords traffic operational index, control delay, highway capacity manual, CORSIM, TRANSYT-7F, SYNCHRO, VISTRO Corresponding Author : Yoon, Jungeun, Researcher (Daehwa-Dong) 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si, Gyeonggi-Do, 411-712, Korea Tel : +82.31.910.0682 Fax : +82.31.910.0746 E-mail : yoon22@kict.re.kr International Journal of Highway Engineering http://www.ksre.or.kr/ ISSN 1738-7159 (print) ISSN 2287-3678 (Online) 109
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Bill Cisco, 2013. PTV VISTRO: ADVANCES IN TRAFFIC ENGINEERING ANALYSIS SOFTWARE, PTV GROUP, p.19. Cho, J. et al., 2005. Comparison of Delay Estimates for Signalized Intersection, Journal of Korean Society of Transportation, Vol. 23, No. 1, pp.67-80. Doh, T., 2007. Principle if Transportation Engineering, Cheongmoongak Publishing, pp.54-55. Francois, D. et al., 2004. Comparison of delay estimates at undersaturated and over-saturated pre-timed signalized intersections, Transportation Research Part B: Methodological, Vol. 38, No. 12, pp.99-122. Husch, D. and Albeck, J., 2006. Traffic Signal Software-User Guide Synchro Studio 7, Trafficware. Kim, Y. et al., 1991. Singnalized Intersection Delay Model, Journal of Korean Society of Transportation, Vol. 15, No. 2, pp.27-40. McTrans, 2009. TRANSYT-7F Users Guide, McTrans, pp.225-230. Ministry of Land, Transport and Maritime Affairs, 2013. Korea Highway Capacity Manual 2013, Ministry of Land, Transport and Maritime Affairs, pp.209-417. Olszewski, P., 1993. Overall Delay, Stopped Delay, and Stops at Signalized Intersections, Journal of Transportation Engineering, Vol. 119, No. 6, pp.835-852. Park, B., Won, J., and Yun, I., 2006. Application of Microscopic Simulation Model Calibration and Validation Procedure: A 118 International Journal of Highway Engineering Vol.16 No.5
Case Study of Coordinated Actuated Signal System, Transportation Research Board, Transportation Research Record, Vol. 1978, pp.113-122. Park, B., Yun, I. and Choi, K., 2004. Evaluation of Microscopic Simulation Tools for Coordinated Signal System Deployment, KSCE Journal of Civil Engineering, Vol. 8, No. 2, pp.1-10. Robertson, H. et al., 1994. Manual of Transportation Engineering Studies, Prentice-Hall, pp.70-73. Yun, I. and Park, B., 2006. Application of Stochastic Optimization Method for an Urban Corridor, Proceedings of the 2006 Winter Simulation Conference L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, eds. 119