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An Assessment of the Operational Benefits of Countdown Pedestrian Signals John R. Engle Ghassan Abu-Lebdeh Thomas Maleck Department of Civil and Environmental Engineering Michigan State University. Project Description.
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An Assessment of the Operational Benefits of Countdown Pedestrian Signals John R. Engle Ghassan Abu-Lebdeh Thomas Maleck Department of Civil and Environmental Engineering Michigan State University
Project Description • 16 Intersections along MDOT State Trunklines within the State of Michigan • 20 Hours of Data for Before and After Conditions • Survey of Pedestrians
What was discovered: • After implementation, majority of peds in the crosswalk (when Solid Don’t Walk phase began) tended to be closer to curb. • Being closer to their destination, the peds were able to leave the roadway quicker after the flashing don’t walk phase ended. • People overwhelmingly liked them.
What was discovered: • There are significant exceptions to the generalizations made previously • There were a significant number of intersections in which this did not occur • Much of this variance could potentially be attributed to social/economic characteristics of the pedestrians
The 16 Intersections were broken down into three groups for analysis.
Group A: • Michigan @ Larch - Lansing • Saginaw @ Capitol - Lansing • Saginaw @ Pennsylvania - Lansing • Michigan @ Rose - Kalamazoo • Bridge @ Jefferson - Grand Ledge • Beach @ 5th - Flint
Group A Findings • ‘Normal’ geometric layouts with peds exhibiting ‘usual’ behavior • After CPS, a small increase in volume of peds who cleared before solid don’t walk (SDW) phase • After CPS, minor decrease in the percentage of pedestrians crossing on the SDW phase
In five of the six locations of Group A, after CPS implementation a larger percentage of peds began crossing during flashing don’t walk (FDW) phase • With CPS, if peds were ‘caught’ in the intersection when FDW phase ended, they tended to be much closer to their destination curb than before
Group B: • Gratiot @ Linhurst - Detroit • Gratiot @ Hickory - Detroit • Gratiot @ Outer - Detroit • Gratiot @ Filbert - Detroit • Dexter @ Washington - Ionia • Genesee @ Washington - Saginaw
Group B Findings • Locations in distressed, lower income neighborhoods • Number of pedestrians that exhibited unusual walking behaviors was significantly higher than at other locations
Group B Findings • For five of the six locations, percentage of peds who cleared before the solid don’t walk increased after CPS • Percentage of peds crossing on SDW also decreased for five of the six locations
Group C • Mission @ Bellows - Mt Pleasant • Michigan @ Ann Arbor - Saline • Wyoming @ 8 Mile - Detroit • VanDyke @ 10 Mile - Centerline
Group C Findings • “Miscellaneous” group • No consistency between intersections • Four intersections, locations w/ certain unique geometric layout, traffic flow, or pedestrian behavior may have resulted in different behavior problems
Case Example: Mt Pleasant • Near CMU campus • Majority of peds were college students, who displayed more aggressive walking behaviors • Often would use countdown clock from another approach to decide • This may explain the higher percentage of peds crossing on solid don’t walk after the CPS
Case Example: Centerline • Demographics similar Group A • Unique geometric feature: very wide highway width of VanDyke with no median (~108 ft) • After CPS a greater % cleared before the solid don’t walk • Little change on bringing peds closer to curb • Possible, CPS encouraged peds to walk faster compared to an unusually long flashing don’t walk phase
Case Example: Detroit/8Mile • Near a school • Majority of peds middle school and elementary school children who crossed 8 Mile Road • Majority of peds were unable to clear the intersection in one phase • Resorted to waiting on a median island before completing their crossing
Case Example: Detroit/8Mile • Exception to majority of behaviors • Located in a exurb of Ann Arbor • Majority of peds high income demographic. • Unclear why after CPS a lower % of peds cleared before solid don’t walk, or why
Summary • Impact was mostly positive • There appear to be some exceptions • Non-engineering factors important at some • More analysis needed • Statistical • Qualitative • Relevant finding to start develop guidelines