Abstract
Analysis of traffic at a signalized intersection requires quantification of the number of vehicles in the queue and the corresponding delay. Such analyses can be used for optimal signal control as well as for intelligent transportation system (ITS) applications such as advanced traveler information systems (ATISs). However, the direct measurement of these variables is difficult because of their spatial nature. Hence, they are usually estimated using location-based data such as count, speed, occupancy, and so on that can be obtained from point-based detectors such as loop detectors installed on roads. However, driving maneuvers such as lane shifts and free right turns can lead to inaccurate queue estimates in lane-based analysis. To check this, analysis of lane-based data was carried out and discrepancies in the count data obtained from loop detectors were observed. To address these issues, the present study proposed a model-based queue estimation scheme using the Kalman filtering technique, taking into account the statistical properties of detector errors. The detector data and the signal timing information were used as inputs in the estimation scheme. The estimation was carried out for two cases—one where the queue ends within the advance detector and one in which the queue extends beyond the advance detector. Field data collected from four different intersections were used to corroborate the estimation scheme for the “queue within advance detector” scenario. Because of the lack of availability of field data for “queue beyond advance detector,” simulated data were used to corroborate the corresponding results. Results showed that the estimation scheme that incorporated the statistical properties of the detector errors performed better than the scheme that did not incorporate errors.
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Acknowledgments
The authors acknowledge the support provided by Indo-US Science and Technology Forum (IUSSTF), Government of India, under the grant IUSSTF/JC-Intelligent Transportation Systems//95-2010/2011-12, through which the exchange of ideas and personnel were facilitated. The authors thank the efforts of Evangeline and Arul Stephen from the University of Nebraska, Lincoln, U.S., for their assistance in data extraction.
References
Akcelik, R. (1999). “A queue model for HCM 2000.” ARRB Transportation Research Ltd., Vermont South, Australia.
Anusha, S. P., Vanajakshi, L., Subramanian, S. C., and Sharma, A. (2015). “Performance comparison of two model based schemes for estimation of queue and delay at signalized intersections.” 2015 IEEE Intelligent Vehicles Symp. (IV), COEX, Seoul.
Ban, X., Hao, P., and Sun, Z. (2011a). “Real time queue length estimation for signalized intersections using sample travel times from mobile sensors.” Transp. Res. Part C, 19(6), 1133–1156.
Barceló, J., Montero, L., Bullejos, M., Serch, O., and Carmona, C. (2012). “A Kalman filter approach for the estimation of time dependent OD matrices exploiting Bluetooth traffic data collection.” Proc., 91st Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Briedis, P., and Samuels, S. (2010). “The accuracy of inductive loop detectors.” ARRB Conf., ARRB Group Ltd., Melbourne, Australia.
Catling, I. (1977). “A time dependent approach to junction delays.” Traffic Eng. Control, 18(11), 520–526.
Chang, J., Talas, M., and Muthuswamy, S. (2012). “A simple methodology to estimate queue lengths at signalized intersections using detector data.” Proc., 91st Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Cheng, Y., Qin, X., Jin, J., and Ran, B. (2012). “An exploratory shockwave approach to estimating queue length using probe trajectories.” J. Intell. Transp. Syst., 16(1), 12–23.
Coleman, C., and Swanson, D. (2007). “On MAPE-R as a measure of cross-sectional estimation and forecast accuracy.” J. Econ. Soc. Meas., 32(4), 219–233.
Gold, D. L., Turner, S. M., Gajewski, J., and Spiegelman, C. (2001). “Imputing missing values in its data archives for intervals under 5 minutes.” Proc., 80th Annual Meeting, Transportation Research Board, Washington, DC.
Hu, H., Wu, X., and Liu, H. X. (2013). “Managing oversaturated signalized arterials: A maximum flow based approach.” Transp. Res. Part C, 36(1), 196–211.
Kenneth, D. L., and Ronald, K. K. (1982). “Advances in business and management forecasting.” Emerald books, Vol. 7, Howard House, U.K., 140.
Lee, J. B., Jiang, R., and Chung, E. A. (2013). “A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps.” Proc., 92nd Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
LightHill, M. J., and Whitham, G. B. (1955). “On kinematic waves: A theory of traffic flow on long crowded roads.” Proc., R. Soc., 229(1178), 317–345.
Liu, H. X., Ma, W., Wu, X., and Hu, H. (2012). “Real-time estimation of arterial travel time under congested conditions.” Transportmetrica, 8(2), 87–104.
Liu, H. X., Wu, X., Ma, W., and Hu, H. (2009). “Real-time queue length estimation for congested signalized intersections.” Transp. Res. Part C, 17(4), 412–427.
May, A. D. (1975). “Traffic flow theory-the traffic engineers challenge.” Proc., Institute of Traffic Engineers, World Traffic Engineering Conf., Institute of Transportation and Traffic Engineering, Univ. of California, Berkeley, CA, 290–303.
May, A. D. (1990). Traffic flow fundamentals, Prentice-Hall, Inc., Englewood Cliffs, NJ.
Mucsi, K., Khan, A. M., and Ahmadi, M. (2011). “An adaptive neuro-fuzzy inference system for estimating the number of vehicles for queue management at signalized intersections.” Transp. Res. Part C, 19(6), 1033–1047.
Newell, G. F. (1965). “Approximation methods for queues with application to the fixed-cycle traffic light.” SIAM Review, 7(2), 223–240.
Okutani, I., and Stephanedes, Y. J. (1984). “Dynamic prediction of traffic volume through Kalman filtering theory.” Transp. Res. Part B: Methodol., 18(1), 1–11.
PTV Vision. (2012). “VISSIM 5.40 user manual: Innovative transportation concepts.” Planung transport verkehr AG, Karlsruhe, Germany.
Richards, P. I. (1956). “Shock waves on highway.” Oper. Res., 4(1), 42–51.
Sharma, A., Bullock, D. M., and Bonneson, J. (2007). “Input-output and hybrid techniques for real-time prediction of delay and maximum queue length at signalized intersection.” Transp. Res. Rec., 2035, 69–80.
Skabardonis, A., and Geroliminis, N. (2005). “Real-time estimation of travel times on signalized arterials.” Proc., 16th Int. Symp. on Transportation and Traffic Theory, Univ. of Maryland, College Park, MD, 387–406.
Stephanopoulos, G., and Michalopoulos, P. G. (1979). “Modeling and analysis of traffic queue dynamics at signalized intersections.” Transp. Res. Part A, 13(5), 295–307.
Stephanopoulos, G., Michalopoulos, P. G., and Stephanopoulos, G. (1981a). “An application of shock wave theory to traffic signal control.” Transp. Res. Part B, 15(1), 35–51.
Strong, D. W., Nagui, M. R., and Ken, C. (2006). “New calculation method for existing and extended HCM delay estimation procedure.” Proc., 85thTransportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
TRB (Transportation Research Board). (2000). Highway capacity manual, National Research Council, Washington, DC.
Turner, S. M., Albert, L., Gajewski, L. B., and Eisele, W. (2000). “Archived ITS data quality: Preliminary analysis of San Antonio Transguide data.” Transp. Res. Rec., 1719, 77–84.
Vigos, G., and Papageorgiou, M. (2008). “Real-time estimation of vehicle count within signalized links.” Transp. Res. Part C, 16(1), 18–35.
Vigos, G., and Papageorgiou, M. (2010). “A simplified estimation scheme for the number of vehicles in signalized links.” IEEE Trans. Intell. Transp. Syst., 11(2), 312–321.
Webster, F. V. (1958). “Traffic signal settings.” Road research laboratory, Her Majesty’s Stationery Office, London.
Wu, J., Xia, J., and Horowitz, A. J. (2008). “Methodologies for estimating metered on-ramp vehicle queue length.” Proc., 87th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Wu, X., and Liu, H. X. (2011). “A shockwave profile model for traffic flow on congested urban arterials.” Transp. Res. Part B, 45(10), 1768–1786.
Wu, X., Liu, H. X., and Gettman, D. (2010). “Identification of oversaturated intersections using high-resolution traffic signal data.” Transp. Res. Part C, 18(4), 626–638.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 143 • Issue 8 • August 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jun 14, 2016
Accepted: Jan 12, 2017
Published ahead of print: Mar 29, 2017
Published online: Mar 30, 2017
Published in print: Aug 1, 2017
Discussion open until: Aug 30, 2017
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