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Methodology and Learnings from Calculating the Cost of the Causes of Congestion

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David Johnston & Kath Johnston

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Methodology and Learnings from Calculating the Cost of the Causes of Congestion

  1. 1. Methodology and Learnings from Calculating the Cost of the Causes of Congestion David Johnston, Intelligent Transport Services Kath Johnston, QLD Transport and Main Roads 27 July 2016
  2. 2. Project Objective To produce a congestion pie for TMR similar to the FHWA example, but with the following causes of excessive congestion: • Recurring congestion • Traffic Incidents • Roadworks • Inclement Weather • Special Events/Other
  3. 3. Steps in Methodology A) Import data B) Generate benchmarks of link performance (i.e. ‘Normal’) C) Generate congestion cost components (delay, fuel use, pollutants) D) Generate abnormal congestion footprints E) Map causes onto abnormal congestion footprints F) Produce reports Start (A) Import data for processing (B) Generate benchmark link performance profiles (C) Generate Congestion Cost measures End (E) Map causes onto abnormal congestion footprints (F) Produce reports (D) Generate abnormal congestion footprints
  4. 4. Import Data • NPI Link Data – Speed & Volume • STREAMS Transport Network model – links, intersections, movements, NPI Links • Weather data (30 minute rainfall observations) • SIMS data – incidents, roadworks, planned events. • 131940 data (traffic information line) • Fleet data - % by vehicle type, % business / private use • Unit cost data – delay (ABS wages), fuel, pollution
  5. 5. Step B: Benchmark ‘Normal’ Traffic METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  6. 6. ‘Normal’ Profiles A profile defines what is ‘normal’ for an NPI Link and each 15- minute period • Profile holds mean & standard deviation of volume & speed across days selected for profile • Multiple profiles across the days in a data set • Key question: How do you select which days to include in a profile?
  7. 7. Day Types in the Calendar The following attributes are identified in the calendar for each day: • Weekday (Sat and Sun will normally be different to Mon – Fri) • Season (More travel to & from the beach during summer) • Public Holidays • School Holidays • School Fringe (e.g. November when grade 10-12 out, private schools) • Late night shopping (Thursdays plus week before Christmas)
  8. 8. Break types associated with Days Further intelligence required for public holidays near weekends • Each weekend is a 2-day “break” • If Friday is a public holiday, Thursday traffic will be more like a normal Friday • If Thursday is a public holiday, Wednesday will be like a normal Friday and Friday will be much quieter than normal. • To ‘learn’ these, the calendar identifies each day as one of: a) Day not in “break”; b) Day before “break”; c) First day of “break”; d) Day inside “break”; e) ‘Normal’ day during “break”; f) Last day of break; or g) Day after “break”
  9. 9. Step C: Generate Congestion Cost Components METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  10. 10. 10 | Daily cost of congestion for Brisbane state-controlled roads (Network & Performance Team E&T Road Operations Feb 2016)
  11. 11. Allocation of Costs Excessively Congested (as per ARRB formula) Not Excessively Congested (as per ARRB formula) Less than Normal Congestion All congestion cost attributed to Recurring Excessive Congestion. No cost of excessive congestion to allocate. Normal Congestion Greater than Normal Congestion Any ‘normal’ congestion cost attributed to Recurring Excessive Congestion. All excessive congestion cost attributed to one or more causes.
  12. 12. 12 | Congestion – without incident 0 2 4 6 8 10 12 14 16 18 20 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 102 105 Speed, km/h Weekday freeway speeds, 5:30pm Excessive congestion < 70% of posted speed Posted speed 100 km/h
  13. 13. 13 | Congestion – without incident 0 2 4 6 8 10 12 14 16 18 20 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 102 105 Speed, km/h Weekday freeway speeds, 5:30pm Average speed 53 km/h Normal range
  14. 14. 14 | Congestion – without incident 0 2 4 6 8 10 12 14 16 18 20 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 102 105 Speed, km/h Weekday freeway speeds, 5:30pm Normal recurring 44%
  15. 15. Step D: Generating Abnormal Congestion Footprints METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  16. 16. Determine spatial extent of abnormal congestion
  17. 17. Merging Abnormal Congestion Footprints • Where separating link is excessively congested and this is normal, merge the abnormal congestion footprints. • NPI Link X meets this condition. NPI Link Y does not.
  18. 18. Step E: Map Causes onto Abnormal Congestion Footprints METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  19. 19. 19 | Separating the causes of excessive congestion Excessive Congestion Normal Infrastructure bottlenecks Abnormal Incidents Weather Roadworks Special events
  20. 20. 20 | Congestion – during incident 0 2 4 6 8 10 12 14 16 18 20 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 102 105 Speed, km/h Weekday freeway speeds, 5:30pm
  21. 21. 21 | Congestion – during incident 0 2 4 6 8 10 12 14 16 18 20 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 102 105 Speed, km/h Weekday freeway speeds, 5:30pm Abnormal recurring 34% Incidents 9%
  22. 22. Step F: Report Results METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  23. 23. 23 | Causes of congestion 2014, Brisbane State-controlled roads Normal recurring $112,302,783 Abnormal recurring $86,874,208 Incidents $22,533,228 Roadworks, $535,967 Special, $7,368 Other, $302,107 Weather, $7,189,360 Unknown $24,204,211
  24. 24. Limitations & Opportunities Identified METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  25. 25. 25 | Data limitations Missing data Truck cost excludes value of goods Congestion inside 15 min periods Other modes
  26. 26. Additional Opportunities Arising • ‘Normal’ profiles could be used to: – improve detector monitoring, improve incident detection – input to traffic models, better understanding of what is ‘normal’ when – calculate actual operational capacity of each link in real time & where there is spare capacity • Calculate impact of individual weather or incident events: cost, VKT affected, VKT lost, actual start time & duration, etc. and save with SIMS or 131940 record • Improve traffic management methods by analysis of cost data to target specific causes • Visualisation of congestion events (see example)
  27. 27. The authors wish to acknowledge the support of QLD Transport and Main Roads and thank Kelvin Marrett, Miranda Blogg and Frans Dekker for their contributions to this project. METHODOLOGY AND LEARNINGS FROM CALCULATING THE COST OF THE CAUSES OF CONGESTION
  28. 28. Visualisation: Traffic Data, Incident Data, Weather Data, Bus Service Data. Thanks to netBI for data integration & visualisation.

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