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Diverging Diamond Interchanges (DDIs) are an emerging interchange configuration that eliminates the need for left-turn phases in conventional diamonds and may be less expensive to construct than some alternative geometries. This paper examines signal timing for DDIs. To date, DDI signal timing has typically used two-phase configuration reflecting the two competing movements at the cross-over points at each intersection of the DDI. This configuration inherently contains some inefficiency: i) there is potential for internal queuing under two-phase configuration, and ii) it is possible for the inflow demand to exceed outflow capacity of the interchange. This paper uses high-resolution event data to develop performance measures to evaluate operations at a DDI in Salt Lake City, Utah. Alternatives to the existing signal timing within the two-phase configuration are modelled and tested with a field deployment. The field deployment demonstrated the ability to prioritize ramp or thru vehicles within the two-phase configuration. Additionally, a new three-phase configuration was developed and deployed to address the internal queuing that occurs with two-phase timing. Under this new configuration, the flows from one DDI intersection to the other are balanced and progression within the DDI is improved. By implementing the three-phase configuration, the percent of vehicles arriving on green at the heaviest internal movement within the DDI increased from 53% to 92%. To qualitatively illustrate these performance measures and improved DDI operation, a video from a tethered unmanned aerial vehicle (UAV) was prepared that demonstrates the vehicle arrival characteristics by overlaying vehicle detection and signal state graphics on the video. Hainen, Stevens, Day, Li, Mackey, Luker, Taylor, Sturdevant, Bullock 3 INTRODUCTION The Diverging Diamond Interchange (DDI) is an innovative interchange geometry whose use is increasing. Typically, DDI signal timing has consisted of a relatively simple two-phase configuration at each intersection. Most of the published literature on DDIs has focused on geometrics, capacity, and safety, with very little published on signal timings. This paper summarizes the DDI literature and describes the application of high-resolution controller data to develop performance measures to optimize DDI timing. BACKGROUND The diverging diamond interchange was developed by Chlewicki from 2000-2003 and was first deployed in the U.S. at I-44 and Kansas Expressway (SR 13) in Springfield, Missouri (1) (2). Bared et al. reported increased capacity at DDIs compared to regular diamond interchanges under various simulations mainly due to the elimination of the left-turn phase which reduces signal timing to a two-phase configuration (3). Several other papers used microsimulation-based evaluations (4) and all reported that for a majority of the cases that DDIs performed better than conventional diamond interchanges, single-point urban interchanges (5), and other alternative intersections often due to the two-phase signal operations (6). In recent work, the HCM delay formulas have been adapted to DDIs (7), simulation packages have been created (8), selection tools have been developed (9), split optimization software made available (10), and critical lane volume analysis tools implemented (11). Cycle length has been investigated (12) and timing the DDI with overlaps instead of a traditional two-phase configuration has been considered (13). In summary, existing work has focused on simulation-based comparisons of the DDI to other operational types. This study reports on the application of high resolution traffic signal controller performance measures to assess DDI field operations and identify opportunities to improve signal timing. The evaluation is carried out during peak and off-peak periods for a DDI in Salt Lake City, Utah. PERFORMANCE MEASURE APPROACH One of the challenges of DDI timing is that under some demand scenarios there is an imbalance between upstream and downstream capacity. Given the relatively limited number of field deployments, there are opportunities to identify and establish performance measures that can be used for optimizing DDI timing efficiencies. This paper documents the following contributions  First, performance measures are developed for the DDI. Graphical tools are applied to the case of the DDI to evaluate how the interchange is performing.  The performance measure data is further applied to explore the optimization of traffic flows between the two intersections. By associating traffic signal states with vehicle detection times, it is possible to identify traffic origins (ramp or mainline) and optimize the total number of arrivals on green.  To address the imbalance between upstream inflow demand and downstream intersection outflow capacity that is inherent in the two-phase configuration, a three-phase configuration which features a “hold-back” phase is proposed and tested in the field. The new configuration improves traffic flows within the DDI by balancing green times at each intersection so that periods of inflow are aligned with compatible greens, and eliminating stops and queuing in the middle of the interchange. Hainen, Stevens, Day, Li, Mackey, Luker, Taylor, Sturdevant, Bullock 4  Lastly, video obtained from a tethered unmanned aerial vehicle (UAV) was prepared that demonstrates the vehicle arrival characteristics by overlaying vehicle detection and signal state graphics on the video. SITE CHARACTERISTICS The DDI at SR-201 and Bangerter Highway in Salt Lake City, Utah was the study interchange for this work. This interchange was formerly configured as a traditional diamond, but experienced substantial congestion during peak periods. Progression along the arterial (14) is a critical consideration at this location due to the high volume of truck traffic to/from the area north of the intersection (adjacent signal approximately 1,000 feet away), as well as the closely spaced signalized intersection to the south of the intersection (adjacent signal approximately 500 feet away). A DDI option was selected as the most cost effective upgrade to mitigate congestion. Figure 1 shows the lane configuration and phasing for the interchange that was re-constructed in 2011. At the north intersection (WB ramp), there are two sources for SB traffic:  External Southbound Thru (Overlap-E). Overlap-E is driven by Ø5 (phase 5) and Ø6.  Westbound Left Movement (Overlap-H). Overlap-H from the ramp is driven by Ø8. At the south intersection (EB ramp), there are two sources for NB traffic:  External Northbound Thru (Overlap-A). Overlap-A is driven by Ø1 and Ø2.  Eastbound Left Movement (Overlap-D). Overlap-D from the ramp is driven by Ø4. Each ramp intersection includes two movements that provide separate inflows to the other intersection. In Figure 1, the black arrows (OL-E and OL-A) are the movements from the external thru movements along Bangerter Highway, and the gray arrows (OL-H and OL-D) are the movements carrying traffic off the ramps. All ramp movements are signalized and turning left on red is not permitted. A 60-second cycle length was used with a 5-second offset between the rings. Ring 1 handles the south intersection and Ring 2 handles the north intersection. The even-numbered phases (2,4,6,8) each have 23-second splits. The odd-numbered phases (1,3,5,7) each have 7second splits. The sole purpose of the odd-numbered phases is to provide additional clearance time to allow the vehicles in the cross-over area to clear the off-ramp conflict points before allowing ramp traffic to proceed. Backup prevention rules were programmed in the controller to ensure that these clearance phases are always served. In some controllers, the same behavior could possibly be achieved without using separate phases by using leading overlaps with red time. Although the ramp and thru movements are controlled by overlaps at this location, the existing timing is effectively the same as “two-phase” operation, since each intersection effectively alternates between two states (northbound or southbound at each intersection). The north intersection alternates between Overlaps G and E while the south intersection alternates between Overlaps A and C. Changing the number of “phases” is considered later in this paper. The locations of the advance detectors are shown in Figure 1. Radar detection was used. The posted speed limit on the bridge is 40 MPH. Hainen, Stevens, Day, Li, Mackey, Luker, Taylor, Sturdevant, Bullock 5 PERFORMANCE MEASURES In previous studies, Indiana has leveraged high-resolution event-based data (15) to develop performance measures for engineers to better understand arrival characteristics and other operational characteristics at intersections (16). The two common performance measures used are the Purdue Coordination Diagram (PCD) and the flow profile diagram. Purdue Coordination Diagram The PCD (17) is a graphical tool for visualizing progression between intersections. Each vehicle arrival time at the stop bar is plotted by the time of day along the horizontal axis and by time in cycle along the vertical axis. Moving from the x-axis upward, the beginning of the cycle is the beginning of red; the next event is the start of green (green line), and the final event is the end of green (red line). Vehicle arrivals represented by dots below the green line represent arrivals on red, while dots above the green line represent arrivals on green. The greater the proportion of dots above the green line, the higher the percent of arrivals on green and the better the progression of vehicles. Figure 2a and Figure 2b are further enhanced by coding the arrivals according to their originating phase. Figure 2a is the PCD for the northbound movement at the north intersection. The black dots (northbound thru vehicles) are located in a dense band immediately following the start of green. This suggests that at the start of green, t

High-Resolution Controller Data Performance Measures for Optimizing Divergent Diamond Interchanges and Outcome Assessment for Drone Video