Delay Pattern Estimation for Signalized Intersections Using Sampled Travel Times

Intersection delays are the major contributing factor to arterial delays. Methods to estimate intersection delay patterns by using measured travel times are studied. The delay patterns provide a way to estimate the delay for any vehicle arriving at the intersection at any time, which is useful for providing time-dependent intersection delay information to the driving public. The model requires sampled travel times between two consecutive locations on arterial streets, one upstream and the other downstream of a signalized intersection, without the need to know signal timing or traffic flow information. Signal phases can actually be estimated from the delay patterns, which is a unique feature of the proposed method in this paper. The proposed model is based on two observations regarding delays for signalized intersections: (a) delay can be approximately represented by piecewise linear curves due to the characteristics of queue forming and discharging and (b) there is a nontrivial increase in delay after the start of the red time that enables detection of the start of a cycle. A least-squares–based algorithm is developed to match measured delays in each cycle by using piecewise linear curves. The proposed model and algorithm are tested by using field experiment data with reasonable results.

[1]  I G Taylor,et al.  THE USE OF THE OUTPUT FROM VEHICLE DETECTORS TO ASSESS DELAY IN COMPUTER-CONTROLLED AREA TRAFFIC CONTROL SYSTEMS , 1981 .

[2]  Gordon F. Newell THEORY OF HIGHWAY TRAFFIC SIGNALS , 1989 .

[3]  Donald Goldfarb,et al.  An O(n3L) primal interior point algorithm for convex quadratic programming , 1991, Math. Program..

[4]  Alexander Skabardonis,et al.  Improved Speed-Flow Relationships for Planning Applications , 1997 .

[5]  H. M. Zhang,et al.  Link-Journey-Speed Model for Arterial Traffic , 1999 .

[6]  Der-Horng Lee,et al.  Calibration-free arterial link speed estimation model using loop data , 2001 .

[7]  Stephen G. Ritchie,et al.  Anonymous Vehicle Tracking for Real-Time Traffic Surveillance and Performance on Signalized Arterials , 2002 .

[8]  Will Recker,et al.  Using Microscopic Simulation to Evaluate Potential Intelligent Transportation System Strategies Under Nonrecurrent Congestion , 2004 .

[9]  Alexander Skabardonis,et al.  Real-Time Estimation of Travel Times on Signalized Arterials , 2005 .

[10]  Cheol Oh,et al.  Anonymous Vehicle Tracking for Real-Time Freeway and Arterial Street Performance Measurement , 2005 .

[11]  Mobile Century Using GPS Mobile Phones as Traffic Sensors : A Field Experiment , 2008 .

[12]  Alexandre M. Bayen,et al.  Virtual trip lines for distributed privacy-preserving traffic monitoring , 2008, MobiSys '08.

[13]  Alexandre M. Bayen,et al.  An ensemble Kalman filtering approach to highway traffic estimation using GPS enabled mobile devices , 2008, 2008 47th IEEE Conference on Decision and Control.

[14]  Henry X. Liu,et al.  Virtual Probe Approach for Time-Dependent Arterial Travel Time Estimation , 2008 .

[15]  Pravin Varaiya,et al.  Arterial travel time estimation based on vehicle re-identification using wireless magnetic sensors , 2009 .

[16]  Gary A. Davis,et al.  Field Evaluation of Model-Based Estimation of Arterial Link Travel Times , 2009 .

[17]  P. Varaiya,et al.  Practical Scheme for Arterial Travel Time Estimation Based on Vehicle Reidentification Using Wireless Sensors , 2009 .