Purdue University’s research, led by Dr. Darcy Bullock to field measure quality of signal timing offsets and vehicle arrivals on green versus red using local controller software.
14. INDOT Sign/Data Collection Unit Wireless Link Bluetooth Sensor Solar Power
15. Real Time Implementation Commercial Wireless Internet Access Commercial Wireless Internet Access SQL Database Query every 5 minutes for median MAC and Observation Time
17. Sample SR 32 Arterial Data SR 32 Instrumented Arterial from SR 238 to SR 37
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19. SR 32 @ SR 238 Bluetooth Data Logger Ethernet Switch Bluetooth Antenna Econolite ASC 3 with Indiana Data Logger Enabled
20. Probe Monitoring Stations Long Term Installation with Real-Time SQL Based Travel Time Calc Short Term Installation with Real-Time SQL Based Travel Time Calc Short Term Battery Powered Device (Traffax)..Data post processed
28. Purdue Coordination Diagram Construction 0 sec 12:00:00 Cycle ends Green phase ends Green phase begins 120 sec 12:02:00 90 sec 50 sec 70 sec 12:01:10 120 90 50 70 12:02:00 12:01:10 Green Red Cycle boundary Green window Coordination Loop Detection time Cycle begins time of day Time in cycle 0 12:00:00
29. Purdue Coordination Diagram (15 minutes) Green window Phase 6 is red while phases 7, 8 are served Phase 6 is red while phase 5 is served Phase 6 beginning of green Phase 6 end of green/ beginning of red
30. c383 c384 c385 c386 c387 c388 c389 c390 c391 c392 c393 c394 c395 c396 g f e d c b h i a Phase 2 Green Clearance Phase 1 Phase 4 Phase 3 Phase 2 Red c397
79. Percent of Cycles with Ped Phases, Wednesday 2 4 8 6 Before (1/9/08) After (1/30/08) 0:00 12:00 24:00 0:00 12:00 24:00 0% 100% 50% 0% 100% 50%
80. 24 Hour Counts by phase…dependent upon Cycle P1 P2 P3 P4 P6 P5 P7 P8 60 0 30 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 60 0 30 Time of Day Vehicle Detections per Cycle
81. 24 Hour Green Time by phase P1 P2 P3 P4 P6 P5 P7 P8 90 0 45 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 90 0 45 Time of Day Green Time (sec)
82. V/C Ratios by Phase, 24 Hours P1 P2 P3 P4 P6 P5 P7 P8 1.0 0.0 0.5 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 0:00 24:00 12:00 1.0 0.0 0.5 Time of Day Volume-to-Capacity Ratio
83. 24-Hour Plot of Intersection Saturation Showing Critical Path
84. 24-Hour Plot of Intersection Saturation With Split Failures Indicated
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Notas del editor
Now we’ll show a couple applications for progression diagrams… These are based on our testbed at SR 37 in Noblesville. First, we’ll use progression diagrams to observe the impact of a controller failure…. In this case, one of the controllers in the arterial system failed and was swapped out with an older controller with an incorrect plan programmed.
Developing weekend plans is a challenge for most agencies because of the need to collect data on weekends. In this case, on SR 37 the weekend plan has not been updated for quite some time… so we felt it would be a good idea to take a look and see if there were any opportunities for improving it. Here are the progression diagrams… (talk through good/bad) Good progression at x, y, z shown by the distribution of vehicles coinciding with the green band. -Poor progression at a,b,c illustrated by the distribution of vehicles coinciding with the red. We have random arrivals at the northern entry point into the system… we also see what appear to be random arrivals occurring at 37 and Pleasant.
Here’s a closer look at the three coord phases with poor quality of progression. Each of these shows a clear example of a case where we could improve the offsets. The vehicles appear to arrive in regular platoons, but those platoons are arriving during the red phase.
To illustrate this concept in detail, we will focus on the 2 nd and 3 rd intersections on SR 37.
Here’s an example where the approach on one end of the intersection has very good progression (POG = 80%), while the other on the opposite has rather poor progression (40%). Although we can change the offset at either intersection, there is only one relative offset between the two intersections that strongly influences the progression quality at both intersections. This is a classic example of a case where a tradeoff has to be made between one direction and the other… We’ll use progression diagrams to estimate what will happen as we change the offset… keeping track of total vehicle arrivals on green as the quantity we are trying to maximize.
Now that we have found some optimal offsets, we can use progression diagrams to estimate what the impact will be. First, we’ll put up the current weekend offsets and the actual time when vehicles are arriving during cycle for each intersection.
If we adjust the arrival times of vehicles according to the proposed offsets, this is the estimated impact on the system. (flip back and forth) As we can see here, we expect these adjustments to cause the coord platoons that are currently arriving in red to be shifted into green. The other offsets that were formerly good have not been negatively affected. In this case, we predict that southbound at 37/Town and Country will suffer a little, but it should be offset by substantial improvements at the other approaches.