Dr Bobby Du and Paul-Antonin Dublanche presented a seminar titled "Is bus bunching serious in Sydney? Preliminary findings based on Opal card data analysis" as part of the SMART Seminar Series on 2nd August 2018. More information: https://news.eis.uow.edu.au/event/is-bus-bunching-serious-in-sydney-preliminary-findings-based-on-opal-card-data-analysis/ Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/

1. Is bus bunching serious in Sydney?
–PreliminaryfindingsbasedonOpalcarddataanalysis
Dr. Bobby Du
Mr. Paul-Antonin Dublanche

2. What is bus bunching (BB)?
Phenomenon
Bus bunching is described as the
effect of two successive buses of
same route arriving at same bus stop
with a headway shorter than a pre-
defined threshold.
(source: https://austinrailnow.files.wordpress.com/2015/03/0_arn_otw-bus-brt-jam-mackenzie-king-bridge-2011-sep-z_flickr.jpg)

3. Why does BB happen?
Phenomenon
(source: https://www.youtube.com/watch?v=V9vjvfbM7ko&feature=youtu.be)

4. Longer waiting time
1.5 times than normal
Dissatisfaction
Complaining and loss of passengers
Inefficiency
High and low occupancies
Worse level of service (LOS)
Lower on-time rate
Is BB good or not?
Phenomenon
Bus Rapid Transit corridor in Guangzhou, China. Credit: ITDP
(source: http://1.bp.blogspot.com/-Alml1YB9d3Q/USYiBK8BYwI/AAAAAAAALB4/wiO0CKPdDJQ/s1600/guangzhou-kf-070310_196_thumb.JPG)
NO !!!

5. BB Identification
3D: spatial, temporal, operational
Causes Analysis
2D: supply and demand
BB Prediction
Historical and real-time data
Solution Strategies
Planning and operation
How to solve BB problem?
Framework
(Source: https://landtransportguru.net/web/wp-content/uploads/2018/04/5008-67-5017-67.jpg)

6. BB Identification
Spatial
(Source: https://www.google.com.au/maps/place/New+South+Wales/)(Source: https://transportnsw.info/routes/details/illawarra-buses-network/55a)
?

7. BB Identification
Temporal

8. BB Identification
Operational
Various bus operators
Different management and operation strategies
Types of bus stops
Interchange/non-interchange, single/multiple bus lines
Features of bus lines
Loop, bidirectional
(Source: https://opendata.transport.nsw.gov.au/open-data/)

9. CausesAnalysis
Supply
(Source: https://medium.com/lovesong/why-chinese
-tourists-behave-badly-a102b40bb589)
(Source: https://trevallog.com/travel-singapore-johor
-bahru-jb-public-transport-bus/)
Bus stop
Location, capacity, function, layout, queueing design
Driver’s behavior
Subjective, unstable, unpredictable
Traffic condition
Complex, unpredictable, objective, interactive
Operation management
Timetable, schedule, supervision, real-time control

10. CausesAnalysis
Demand
(Source: https://www.businessinsider.com.au/the-nsw-gover
nment-is-getting-rid-of-free-trips-on-the-opal-card-2016-5/)
(Source: http://citygreen.com/case-studies/jurong-smart-bus
-station-singapore//)
Peak hours
High volume, commuters (workers, students)
Non-peak hours
Relatively lower volume, irregular travelers
Weekdays
Higher volume
Weekend and public holiday
Lower volume

11. BB Prediction
Historical data
Long-term and stable trend analysis

12. BB Prediction
Real-time data
Short-term and dynamic prediction

13. Solution Strategies
Planning/Preventive
Dedicated bus lane
avoid traffic congestion
Bus route design
avoid long bus route
Bus bay design
avoid conflict and disordered queue
(Source: https://archpaper.com/2014/06/route-improvements-2/

14. Solution Strategies
Operation/Corrective
Skipping
for the leading bus running behind schedule
Holding
for the following bus running ahead of schedule
Overtaking
for empty/following bus
Speed Adjustment
for drivers to keep constant headway
Conditional Signal Priority
for delayed bus
Adaptive Control Scheme
for real-time control
(Source: https://www.bttoronto.ca/2017/02/09/exclusive-bus-driver-bypassing-lake-shore-stop-ttc-blames-driver-confusion/)

15. Case Studies
BB Identification
(Source: http://bondibeach.com/getting-to-bondi-beach)
Historical data
Feb-Mar 2016
Real situation
Expected to be better
New data
Expected for further reearch

16. 16
Case Studies
BB Identification
Single bus line
Bus 343 in Sydney
Multiple bus lines
29 bus lines in north-eastern area of Sydney
Whole region
All bus operators in Sydney

17. • Stops info
• Opal card data
17

18. • Select a direction
• List all stops number
• For each stop: Find all trips id related
• For each trip id: Use tap in/off data to determine what time the
bus stops
• Compare
18
Case Studies
BB Identification

19. Line 343
19

20. Line 343
20
Case Studies
BB Identification

21. Line 343
21
Case Studies
BB Identification
BB per day

22. BB per 30mins
Line 343
22
Case Studies
BB Identification

23. Boarding passengers per 30mins
Line 343
23
Case Studies
BB Identification

24. 29 lines in
selected Sydney region
24
Case Studies
BB Identification

25. 25
Run directions: 1, 2, ‘Regular’, ‘Limited Stops’, ‘1’, ‘2’ ‘1’, ‘2’, ’Regular’, ‘Limited Stops’
Case Studies
BB Identification

26. Stop number 1
Stop number 2
Stop number 3
Stop name Longitude/Latitude
Multiple numbers for one name:
26
Case Studies
BB Identification

27. 201065Burton St near Forbes St
201065 Burton St near
Forbes St
112 Tomaree Rd
4
112 Tomaree Rd
Fix the name problem:
>4
Burton St near Forbes St
27
Case Studies
BB Identification

28. BB per day
29 lines
28
Case Studies
BB Identification

29. BB per 30mins
29 lines
29
Case Studies
BB Identification

30. BB per day Interchange / non-interchange
29 lines
30
Case Studies
BB Identification

31. 29 lines
31
Case Studies
BB Identification
BB per day color scale

32. 29 lines
32
Case Studies
BB Identification
BB per 30min
Interchange / non-interchange:

33. 29 lines
33
Case Studies
BB Identification

34. 29 lines
34
Case Studies
BB Identification

35. 29 lines
35
Case Studies
BB Identification

36. All operators
36
Case Studies
BB Identification

37. Document title37
Case Studies
BB Identification
All operators

38. 38
All operators
Per day
Case Studies
BB Identification

39. 39
All operatorsPer day
Case Studies
BB Identification

40. Per 30mins
All operators
40
Case Studies
BB Identification

41. Datasets
41
Case Studies
BB Identification

42. 42
Case Studies
BB Identification

43. Thankyou!