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Applications of High-Resolution Traffic Event Data: Managing Oversaturated Arterials Dr. Xinkai Wu, Assistant Professor Department of Civil Engineering.

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Presentation on theme: "Applications of High-Resolution Traffic Event Data: Managing Oversaturated Arterials Dr. Xinkai Wu, Assistant Professor Department of Civil Engineering."— Presentation transcript:

1 Applications of High-Resolution Traffic Event Data: Managing Oversaturated Arterials Dr. Xinkai Wu, Assistant Professor Department of Civil Engineering California State Polytechnic University Pomona ITE Western District 2012 Annual Meeting

2 High-Resolution Event Data ITE Western District 2012 Annual Meeting

3 SMART-SIGNAL Terminal Box DAC ITE Western District 2012 Annual Meeting

4 Trunk Highway 55 and Boone Ave (Golden Valley, MN) ITE Western District 2012 Annual Meeting

5 Oversaturation Gazis (1963): An oversaturated intersection is defined as one in which the demand exceeds the capacity. Little research has been conducted on the identification and quantification of oversaturated conditions – Mostly qualitative and incomplete

6 Detrimental Effects Temporally, characterized by a residual queue at the end of cycle. – Residual vehicles cannot be discharged due to insufficient green splits – Creating detrimental effects on the following cycle by occupying a portion of green time. Spatially, characterized by a spill-over from a downstream intersection. – Vehicles cannot be discharged even in green phase due to spill-over – Creating detrimental effects by reducing useable green time for upstream movements

7 Oversaturation Severity Index (OSI) OSI: the ratio between unusable green time and total available green time in a cycle. Further differentiate OSI into T-OSI and S-OSI. – Temporal dimension (T-OSI) The “unusable” green: because of the residual queue from the last cycle – Spatial dimension (S-OSI) The “unusable” green: because of the downstream blockage

8 Measure T-OSI & S-OSI T-OSI: – Estimate the length of residual queue at the end of cycle S-OSI: – Identify spillover – Calculate the reduction of green time of upstream intersections

9 T-OSI & S-OSI Measure Using High- Resolution Traffic Event Data ITE Western District 2012 Annual Meeting

10 Queue Length Estimation Instead of traditional input-output approach, we estimate queue length by taking advantage of queue discharge process Based on LWR shockwave theory

11 Queue Length Estimation Utilize the data collected by advance detector Identify Critical Points: A, B, C

12 Break Point Identification from High- Resolution Detector Data

13 Field Tests Test Site: TH55 (6 intersections) Independently evaluated by Alliant Engineering, Inc. – At Rhode Island Ave. – Three morning peaks (7:00am-9:00am) Jul. 23 rd, 2008 Occ. 29 th, 2008 Dec. 10 th, 2008 ITE Western District 2012 Annual Meeting

14 SOSI: Identify Queue-over-detector (QOD) Caused by Spillover

15 S-OSI: Identification of Spillover Identify QOD-II. High-resolution data. ITE Western District 2012 Annual Meeting

16 Managing Oversaturation: A Simple Forward-Backward Procedure ITE Western District 2012 Annual Meeting

17 A Simple Forward-Backward Procedure Based on TOSI and SOSI measurements Respond and mitigate traffic congestion quickly Simple and effective Reactive ITE Western District 2012 Annual Meeting

18 Problem Setting N intersections along an oversaturated path At control period t, decisions are made according to the average TOSI and SOSI values at the control period t-1, i.e., ITE Western District 2012 Annual Meeting

19 Basic Mitigation Strategies The TOSI and SOSI values can help identify the causes of arterial traffic congestion Positive SOSI indicates the spill-back of downstream queue Positive TOSI indicates that the available green time is insufficient for queue discharge Therefore for a single intersection, three basic strategies can be applied. ITE Western District 2012 Annual Meeting

20 TOSI > 0 Extending green ITE Western District 2012 Annual Meeting

21 SOSI > 0 Reducing red at the downstream intersection ITE Western District 2012 Annual Meeting

22 SOSI > 0 Gating (Reducing traffic arrivals & giving green to other approaches) ITE Western District 2012 Annual Meeting

23 Handling Spillover ITE Western District 2012 Annual Meeting

24 Forward-Backward Procedure Forward Process (Seeking the available green) – Follow the flow direction to eliminate spillovers and residual queues – Boundary condition ITE Western District 2012 Annual Meeting

25 Forward-Backward Procedure Backward Process (Gating or metering) – Follow the opposing flow direction to check the arc capacity – Boundary condition ITE Western District 2012 Annual Meeting

26 Simulation Test 22 intersections, Pasadena, CA Offline control

27 Simulation Test TOSI/SOSI Changes Fair Oaks Ave SBColorado Blvd. WB ITE Western District 2012 Annual Meeting

28 Future Work The Fundamental Diagram: Congestion Safety Environment Control ITE Western District 2012 Annual Meeting


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