1. Using Big Data: Exploring the Differences between Weekday and Weekend Travel
Leta F. Huntsinger, PhD, PE
Senior Technical Principal, WSP
Xuan Wang, PhD, PE
Project Manager, Regional Transportation Commission
Working with Big Data
Monday, May 15, 2017

2. Outline Motivation Background Data description and processing
Weekday versus Weekend Comparisons
Basic Trip Statistics
Travel Time Comparisons
District to District Flows
Highway Assignment Results
Summary and Conclusions

3. Average Weekday Models
Weekday versus Weekend Travel
Project Prioritization and Decision Making
Research Motivation
Household travel surveys and the travel models developed from those surveys typically represent average weekday travel. However, it is often the case that transportation planners and decision makers want to understand the impact of weekend travel on the transportation system, especially for communities with high levels of visitor travel
The primary interest revolves around whether weekend travel is considerably different, and if so, how that would impact project prioritization and decision making.

4. Background Located in the high sierra mountains Biggest Little City
Casinos, dining, and entertainment
Lake Tahoe and world class ski resorts
Over 4 million visitors per year (Washoe County)

5. Data Collection Study Area:
Regional Transportation Commission (Washoe County, Nevada)
Study Period: Month of October, 2015
Weekdays
Weekends
Data Provider: AirSage, Inc.
Data Collection Funded by RTC
Reno / Sparks urban center – only one in region, then surrounded by rural

6. Data Format 6 External Zones 77 Internal Zones OD Data:
Trip ends outside these zones are mapped to nearest zone
77 Internal Zones
Aggregations of model zones
OD Data:
OD Zone Pair
Resident vs Visitor
Synthesized Trip Purpose
HBW
HBO
NHB
Time of Day
Average Weekday
Average Weekend
Expanded Trip Count

7. Data Processing Data provided in user specified districts
Internal trip ends disaggregated to model TAZs
External trip ends disaggregated to external stations
District to District Zone to Zone

8. Weekday vs. Weekend Comparisons
Basic Trip Statistics

9. Avg Weekday
Avg Weekend
Trips by HH
3.96
2.45
Trips by Per
1.70
1.05
Trips by ~Wk
0.43
0.14
Trips/Job
0.36
0.12

13. Weekday and Weekend Trips by Time of Day and Trip Purpose

14. Weekday and Weekend Trips by Time of Day and Trip Purpose

15. Weekday and Weekend Trips by Time of Day and Trip Purpose

17. Weekday vs. Weekend Comparisons
Travel time Comparisons

18. AM
Weekday
Weekend
Resident
9.82
9.23
Visitor
12.22
12.49
Total
10.99
11.00 MD
Weekday
Weekend
Resident
8.96
8.80
Visitor
12.61
13.35
Total
10.63
11.33 PM
Weekday
Weekend
Resident
8.96
8.70
Visitor
12.21
12.30
Total
10.30
10.39

19. Weekday vs. Weekend Comparisons
District to district flows

20. Districts in the Region

21. 5 Highest District to District Flows
Weekday
Weekend
14,059
13,954
13,317
12,467
11,781
12,175
10,325
9,122
8,332
8,002

22. 5 Highest District to District Flows
Residents
Weekday
Weekend
14,059
13,954
13,317
12,467
11,781
12,175
10,325
9,122
8,332
8,002

23. 5 Highest District to District Flows
Visitors
Weekday
Weekend
8,963
6,988
5,845
5,552
4,290
8,982
5,070
4,812
4,144
3,642

24. Absolute Difference

25. Absolute Difference (Normalized)

26. Percent Difference (Normalized)

27. Weekday vs. Weekend Comparisons
Highway Assignment

28. Flow Comparisons in relation to gaming venues and Hotel Rooms
Weekday
Weekend

29. Flow Comparisons weekday vs weekend midday assignment Differences

30. Weekend Peak Volume > Weekday Peak volume

31. Summary and Conclusions
Weekday vs Weekend Trip Patterns

32. Weekday vs. Weekend Differences
For this case study:
Overall weekday travel is higher for this case study
Visitor travel higher on weekends
Visitors make more NHB trips
Different time of day patterns
Average trip lengths are similar between weekday and weekend
Visitor average trip lengths are longer
Variations in flow patterns
Variations in trip assignment

33. Conclusions Important to validate the data
Data are useful in understanding variations in travel patterns
Project prioritization and decision making
The authors would like to thank AirSage, Inc. for the use of their data in this analysis

34. Questions? Leta F Huntsinger: huntsinger@pbworld.com
Xuan Wang: