characterization of the coronavirus pandemic on …
TRANSCRIPT
CHARACTERIZATION OF THE CORONAVIRUS PANDEMIC ON SIGNALIZED INTERSECTIONS USING PROBE VEHICLE DATA
Problem StatementIn order to analyze signalized intersections, data needs to be taken from its
approaches. One way of doing so is through Traffic Message Channels, whichprovides traffic data on specific road segments. Using the unique TMCsintersections approaches, probe vehicle speed data stored in those TMCs canbe collected. The raw data is provided in 1-minute bins, which can then beaggregated into other size bins, typically 15-minute bins. As the aggregation ofdata increases into larger sized bins, the level of detail is expected to alsodecrease. Because of this, when analyzing data on the approaches to bestudied, 15- and 10-minute bins were used when dealing with traffic data, withthe expectation being that 10-minute bins would show finer detail. Whenanalyzing the intersections volumes would work better to display congestion,however as only speed data was available, it was used to display potentialtimes of higher congestion levels. For a simple visual analysis, speeddistributions could be made to show day by day patterns in speed visually. Withthe coronavirus pandemic, a unique scenario was created where a visualapproach could show how drastically speeds throughout the day havechanged. Due to its potentially high infection rates, the state closed publicbuildings such as schools and offices on March 18, 2020 and issued a stay athome order on March 21, 2020. With this, a unique event in transportationoccurred, where a statewide unplanned sustained event suddenly changedtraffic volumes. Because of its sudden nature, speeds could be comparedaround a turning point, March 18, where speeds before could be compared tospeeds after. Alongside a quantitative analysis of the probe vehicle speeds,speed distributions could be applied to visualize how typical morning andafternoon peaks have changed before March 18th, to after.
Study Area Quantitative Analysis Results of US-22 Westbound
US-22 Westbound, Speeds for Varying Bin Sizes Before and After March 18, 2020
Speed Distributions of US-22 and Bin Comparison
Thomas M. Brennan Jr., Ph.D, P.E.1, Bryan Remache-Patino11The College of New Jersey
10 Minute Bins
United States Route 9 and Route 22 Study Sites
10 Minute Bins
Speed Distributions of US-9
• Looking at how speed patterns change, although some road segments may have remainedchanged, some such as US-9 Northbound qualitatively show signs of recovery, as thechanges seem to have begun to revert to patterns prior to March 18
• A similar visual analysis could be conducted in the future to show the duration the effectsCovid-19 has had on transportation, as well as how the effects have varied from road toroad,
15 Minute Bins 15 Minute Bins
Eastbound Daily Speeds for US22 Westbound Daily Speeds for US22
US-9 Northbound, 15-Minute Bins
US-9 Southbound, 15-Minute Bins
US-22 Westbound, Day by Day Speed Average Changes
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
25 30 35 40 45 50 55
Cum
ulat
ive
Perc
ent
Daily Average Speed (MPH)
BC 15 Min BinsDC 15 Min BinsBC 10 Min BinsDC 10 Min BinsBC 1 Min DataDC 1 Min Data
+2.3 MPH
25
30
35
40
45
50
Mon Tues Wed Thurs Fri Sat Sun
Spee
d Av
erag
es (M
PH)
BC 15 Min BinsDC 15 Min Bins
Road/Direction Avg(MPH) Variance St Dev.
US22 Eastbound 38.6 35.6 6.0
US22 Westbound 39.5 31.7 5.6
US9 Northbound 43.5 25.3 5.0
US9 Southbound 29.8 93.9 9.7
Road/Direction Avg(MPH) Variance St Dev.
US22 Eastbound 42.6 17.3 4.2
US22 Westbound 42.7 24.5 4.9
US9 Northbound 46.6 30.9 5.6
US9 Southbound 33.9 120.8 11.0
Before Covid-19 Closings Weekday (Mon-Fri) Statistics Based on 1 Min. Data
After Covid-19 Closings Weekday (Mon-Fri) Statistics Based on 1 Min. Data