Utilizing High Resolution Bus GPS Data to Visualize and Identify Congestion Hot-spots in Urban Arterials

Transcription

1 Portland State University PDXScholar TREC Friday Seminar Series Transportation Research and Education Center (TREC) Utilizing High Resolution Bus GPS Data to Visualize and Identify Congestion Hot-spots in Urban Arterials Nicholas B. Stoll Portland State University, Let us know how access to this document benefits you. Follow this and additional works at: Part of the Transportation Commons, and the Urban Studies and Planning Commons Recommended Citation Stoll, Nicholas B., "Utilizing High Resolution Bus GPS Data to Visualize and Identify Congestion Hot-spots in Urban Arterials" (2016). TREC Friday Seminar Series This Book is brought to you for free and open access. It has been accepted for inclusion in TREC Friday Seminar Series by an authorized administrator of PDXScholar. For more information, please contact

2 Utilizing High-Resolution Bus GPS Data to Visualize and Identify Congestion Hot Spots in Urban Arterials Project PI Miguel A. Figliozzi GRAs Nicholas B. Stoll & Travis B. Glick Friday, January 22nd, 2016

3 Presentation Overview Background & Purpose Methodology Data visualizations Point Level Segment Level Delay Analysis Next steps and future research ideas

4 Background & Purpose Utilize a new data set 5 Second Resolution ( breadcrumb ) Buses as speed probes Build upon previous research

5 5-SR Data Analysis 50 ft. Time 1 Time 2 Time ft. 150 ft. 200 ft. 250 ft. 300 ft. 350 ft. 400 ft. 450 ft.

6 5-SR Data Analysis 50 ft. 100 ft. 150 ft. Speed 1 Time 1 Time ft. Speed 2 Time 3 C = Centerness Factor 250 ft. C 0.49 C 0.15 Speed 3 C ft. 350 ft. 400 ft. 450 ft.

7 5-SR Data Analysis 50 ft. 100 ft. 200 ft. Speed 1 C 0.65 Time 1 C 0.71 Time 2 Time ft. C 0.34 C = Centerness Factor Speed 3 Speed ft. 300 ft. 350 ft. 400 ft. 450 ft.

8 5-SR Data Analysis 50 ft. 100 ft. 150 ft. 200 ft. Time 3 C = Centerness Factor 300 ft. Speed 1 Time 1 Time ft. C ft. C 0.30 Speed 2 Speed 3 C ft. 450 ft.

9 5-Second Resolution Data Point Distribution

10 W Powell and 87th W Powell and 82nd W 12th & Milwaukie Point Distribution at Bus Stops for buses that STOP

11 W Powell and 87th W W Powell Powelland and82nd 87th

12 Route Segment Visualizations Urban Corridor

13 Westbound Route 9 Points of Interest Bus Stop (BS) Intersection (INT) Lets Start Here SE Powell and Milwaukie (12th)

14 A B A B

15

16 Speed profile for all buses over 1 day Speed (1 day) A B

17 Speed profile for all buses over 5 days Speed (5 day) A A B B

18 Westbound Route ft. Segment from 92nd to 78th Westbound BS-82nd BS-79th BS-90th BS-84th SE Powell & 82nd BS-87th Bus Stop (BS) Intersection (INT)

19 Bus Stop (BS) Intersection (INT)

20 Bus Stop (BS) Intersection (INT)

21 Bus Stop (BS) Intersection (INT)

22 Route Segment Visualizations Urban Streets

23 Downtown th th SW 4 and SW 6 Points of Interest ABC N

24 Speed Profile on SW 6th

25 Speed Profile for all buses in Downtown: Crosswalks A B C

26 Delay Visualizations Urban Corridors

27 Delay over a segment by Distance Delay per 25ft Interval Int - Powell & 82nd BS - SE 84th BS - SE 87th BS - SE 90th Delay [seconds] BS - SE 79th BS - SE 82nd

28 Cumulative Delay over a segment by Distance Cumulative Delay BS - SE 79th BS - SE 82nd Int - Powell & 82nd BS - SE 84th BS - SE 87th BS - SE 90th Delay [seconds] 140

29 Delay over a segment by Time of Day Delay [sec] Bus Delay from Freeflow Traffic Speed from 90th to 79th Actual Delay mph 9 25 mph 20 mph 15mph 10mph Time [HH] 0 1

30 Some Potential Applications Buses as probes for traffic conditions Applications to PMs along urban arterials, collector streets and freeway sections (wherever there are buses running on regular routes) Complement Bluetooth, cell phone, and stationary sensor collection systems Compare before and after conditions (e.g. changes in roadway design or signal timing, additional crosswalks)

31 Acknowledgements NITC for funding this Research Steve Callas and Miles Crumley of TriMet for providing the data and definitions used in analysis Dennis Mitchel of ODOT for providing feedback and suggestions for potential applications And to the researchers who lay the groundwork for this analysis.

32 Thank you for listening. Any Questions?