1. National Household Travel Survey California Data (NHTS-CA)
Planning Horizons December 11, :00-12:00
Office of Travel Forecasting and Analysis
Caltrans, Division of Transportation Planning
Good morning and thank you for attending this edition of Planning Horizons.
This presentation is the first in a series on household travel surveys.
The survey gathers trip-related data such as mode of transportation, duration, distance,
and purpose, and then links the travel related information to demographic, geographic, and
economic data for analysis.
. I will begin with very brief introduction of a few of the socio-economic variables in the California data of the NHTS.

2. Man Asked: Who am I ? Where am I ? How did I get here?
In Antiquity
Man Asked:
Who am I ?
Where am I ?
How did I get here?
How Do I Get There?
Few variables

3. Today, these questions and a lot more are answered in the Household Travel Surveys
Who - Socio-economic characteristics of Persons, Households, Workers and Drivers
Where – Live, Work, Shop, Play
Why – Activity, Origin/Destination
What – Vehicles, Transportation Issue
When – Time , Day of the Week
How - Mode, VMT (how far - miles), VHT (how long – hours) mode
Who are we –persons, workers, households
Where –cities,rural areas
Why – we leave the house to travel to work, shop, medical appt, recreation
What- what transportation issues concern us the most, what medical condition prevents us from traveling, what type of vehicle are we likely to repair or buy
When – do we travel
How – many miles, hours….

4. Who Are We? – Age/Gender
Birth dearth – falling fertility rates

5. More than half of California residents are white with Hispanics comprising the next largest group at 20%, followed by Asian and African Americans.

6. Who Are We? - Lifecycle
Very interesting variable as it measures the cycle of life.
One adult households clearly lag except at the beginning lifecycles and at the end lifecycles.

7. Household Income Distribution
Figures in the thousands. # of households increase with the increase in income until $20k, then it flucuates until it reaches a low of less than 300,000 at the $70k group. The dramatic # at the $100k mark covers >= to $100k.

8. Distribution of Incomes for One Adult, Youngest Child 0-5 Households

9. Who Are We? – Job Category

10. One Adult, Youngest Child 0-5 Households by Job Category
A detailed job category analysis of one household composition group.
Have requested of Oakridge that they include a 2 or 3 digit NAICS code

11. Households by Household Vehicle Count

12. What are We Driving?

13. What Type of Vehicle?
Most owned

14. As in the income graph, the income levels increase as do the VMT peaking at $50K mark, dipping then keeping constant at close to 14K average miles a year.

15. Average Minutes Spent Driving Per Person, Per Day Sacramento, Los Angeles, San Diego and San Francisco by Household Composition
LA dominates all household composition groups except for SF households with 2+ adults with youngest child between which shows an average daily minutes spent driving, of over 80 minutes.

16. Importance of Transportation Issues
Attitudnal questions are a very important component of the NHTS. What persons believe is the most important travel issue is measured. 29% of all persons surveyed in state consider Price of Travel as the most important with highway congestion coming in second at 23% and aggressive drivers and safety next.

17. We have been looking at statewide data. This slide shows county data
We have been looking at statewide data. This slide shows county data. Lots of no-vehicle households in SF. Transit question might have been misinterpreted to mean frequent, reliable…? A closer look at infrastructure, transit might be in order.

18. Drilling down this same variable is illustrated on a city level…
Drilling down this same variable is illustrated on a city level….Inglewood in the south, Oakland in the Bay Area and Roseville in the Sacramento area. Again price of travel dominates.. Access and Availability of transit is very strong in Oakland as is highway congestion. Safety concerns are equal in all areas as is lack of sidewalks/walkways

19. Traffic Congestion Issue
How much of an issue traffic congestion is…Respondents were asked to assign a degree of concern. Do they think it is a big issue, moderate issue or little issue.
After $10,000 traffic congestion becomes a big issue
Produce issue horizontal bar chart for issue by income distribution – already run need to run again – LS

20. Objective of SCAG Study
Is to use NHTS data to provide updated travel characteristics for SCAG region.
This presentation includes results of following analysis:
Overall demographics and travel characteristics
Relation between residential location and commuting
Assimilation of Hispanic immigrants’ travel behavior
Income interaction with land use – transportation relation
Results will be provided to SCAG modelers and planners for their analysis.
Source:
Residential Land Use, Travel Characteristics, and Demography of Southern California – presented by the Southern California Association of Governments
A few slides from a SCAG study.
Demographics
Where LA residents live and how long it takes to commute
Hispanic immigrants travel behavior
Income as it relates to land use

21. * Demographics & Travel
Travel by Age
Daily Trips and Distance by Age
Daily trips and travel distance are the highest for the working age population (25-64).
The elderly still rely on a car, but drive less.
Auto Use by Age
# of trips on right, # of miles on left
Mode choice 21 21

22. Travel by Age (Elderly)
* Demographics & Travel
Travel by Age (Elderly)
% of Persons Did Not Travel
20% - 33% of the elderly did not travel on the survey day.
However, when they travel, their trips are no less than the younger.
Non-work Trips by Age
One out of 3 senior respondent did not travel on travel day
Elderly non-work trips are no less than younger??

23. Time of Day by Purpose LS takes over * Demographics & Travel 23 lunch
school
LS takes over
HBW – means returning as well as going
HBSHOP – stopping to shop after work
Include ?? LS wants!!
school
open hours 23

24. Residential Density & Commuting Distance
* Residential Location and Commuting
Residential Density & Commuting Distance
Living in higher density neighborhoods:
Shorter commuting distance.
Commuting time is about the same for all density.
LS – look if you have time??
People per square mile?
SCAG may manipulated the data 24
Density from low to high

26. Change to landscape

27. Bold and take out footer
Explain paragraph on each group

28. Bold and delete footer, bigger title, formatting in general

29. School Trips by Distance and Mode
Take out small title and LS formatting

30. Uses for O & D Survey Data Sets .
Household Origin and Destination Surveys help transportation analysts understand people's travel choices:
What trips or tours do people make (origins and destinations)
Why they travel (purposes or activities)
Travel patterns (amounts by household or person characteristics and by places they go)
How travel would change under different circumstances (travel models)
These surveys provide the detailed information about the large number of choices travelers make. Those explanations are most usefully expressed in transportation models which in turn allow analysts to estimate travel under changed circumstances, usually alternate land use and transportation system scenarios.
LS will send slide info

31. Some Travel Pattern Descriptions
School and Commute distances and modes
Non-driving trips by distance and home region
Reasons for not walking more
Reasons for living where they do
Trip purposes and start and end times
Medical conditions affecting mobility
Use of mobility devices
Internet use: frequency, purchases, delivery
Bold indicates a chart in this presentation.

32. Region to Region Trips (Annual 000)
Much larger Intra Regional

33. Sample Mode Percentages

34. Bike and Pedestrian Hours by Caltrans District
WalkHrs
BikeHrs
D01 Eureka
814,064
78,704
D02 Redding
1,089,364
74,542
D03 Marysville
5,923,755
896,778
D04 Oakland
16,427,130
2,524,209
D05 San Louis Obispo
3,364,097
518,854
D06 Fresno
4,027,689
647,768
D07 Los Angeles
21,980,348
3,251,802
D08 San Bernardino
7,238,376
1,101,887
D09 Bishop
97,662
10,116
D10 Stockton
3,210,006
516,364
D11 San Diego
6,526,006
794,366
D12 Irvine
5,033,585
872,235

35. FHWA Contract
In 2008, NHTS invited state DOTs to supplement the sampling in their areas
Caltrans allocated $3.15 million to survey additional households and ask additional travel and attitudinal questions about biking and walking
California Original Samples – 3,000
California Add-On Samples – 18,000 to total - 21,000 (Oversampling in San Diego County to 5,500)
1 in 1000? Check total household weights – Ask LS

36. Areas with Supplemental Samples
Some MPOs

37. Total Sample (Households) California 21,225 District 1 - Eureka 255
Geography
Total Sample (Households)
California
21,225
District 1 - Eureka
255
District 2 - Redding
326
District 3 - Marysville
1,609
District 4 - Oakland
3,808
District 5 - San Luis Obispo
735
District 6 – Fresno
990
District 7 – Los Angeles
3,767
District 8 – San Bernardino
1,566
District 9 – Bishop 22
District 10 - Stockton
815
District 11 – San Diego*
6,050
District 12 – Irvine
1,282
*District 11 (San Diego) has a supplement of 4,600 households

38. Map samples by district/county

40. Data FilesSETS
Files with records for each. Many variables on more than one file.
Sampled telephone numbers; converted to households.
80 p. Users’ Guide, 80 pp. Weighting Report
I will present a few examples of how data will be used.

41. Geographic Designations
National
Region
State
MSA/CMSA/CBSA
County
City
Census Tract/Block
Latitude/Longitude coordinates

42. Customized Areas – Under Construction
Traffic Analysis Zone (TAZ) Air Quality Conformity Regions
Get exact name from LS

43. Analysis Tools SAS MS Access
Statistical Tool on Oakridge Lab website – output is Excel and HTML

44. Services
Analysis on Request
Consultation
Data Downloads

45. How to get Data or Analyses
NHTS Website:
California Household Travel Survey (CHTS)
Caltrans DOTP Website:
Leonard Seitz:
(916)
Diana Portillo
(916)
Soheila Khoii (CHTS)
Need to add NHTS to intranet with new category of Origin and Destination Surveys
Open hyperlink for NHTS home page and special reports.Ask Leonard how to hyperlink.

46. Estimating total miles walked and biked by census tract in california
Caltrans Planning Horizons Forum
December 11, 2013
Deborah Salon, PhD
Institute of Transportation Studies
University of California, Davis

47. Motivation
Vehicle activity is an output of travel models, but detailed estimates of bicycle and pedestrian activity are often not available.
Good estimates of the total amount of cyclist and pedestrian activity on our roads are useful for:
Informing demand-based investments in bicycle and pedestrian infrastructure
Identifying dangerous locations for potential road safety investment

48. Research question
What are the total miles walked by pedestrians and total miles biked by cyclists living in each census tract in California?
Important Note: The estimates presented here are not of miles walked and biked within the geographic area of each tract, but we expect them to be highly correlated with these values.

49. Method
Assign census tracts to neighborhood types based on built environment characteristics
Calculate miles biked and miles walked for each respondent in the 2009 NHTS and the CHTS (all results presented are from NHTS)
Assign each survey respondent to their age-gender-home neighborhood category
Calculate average miles biked and miles walked for each age-gender-home neighborhood category
Use these averages with census data to expand travel survey data to population totals

50. Neighborhood type classification
Cluster analysis of 10 variables yielded 4 neighborhood types:
Population Density
Road Density
Local Job Access
Regional Job Access
Restaurants Within 10 Minute Walk
Pct. Walk/Bike Commuters
Pct. Single Family Detached
Pct. Old Housing
Pct. New Housing
Median House Value

51. San francisco bay area

52. Los angeles area

53. Surveyed individual miles walked and biked
NHTS
Total N (weekday)
34,123
N biked
773
N walked
7,891
% biked
2.3%
% walked
23.1%

54. survey respondent categories
Categories based on:
Gender
Age Group (5 groups, chosen based on biking and walking distance distributions across ages)
Home Neighborhood Type (4 Types)
Yields 40 Categories

55. Average miles walked by survey respondent categoryF

56. Average miles biked by survey respondent categoryF

57. Survey-to-population estimation method
Simple Expansion Formula:
𝑻𝒐𝒕𝒂𝒍𝑴𝒊𝒍𝒆𝒔 𝒕𝒓𝒂𝒄𝒕 = 𝒊=𝟏 𝟏𝟎 𝑺𝒖𝒓𝒗𝒆𝒚𝑨𝒗𝒈𝑴𝒊𝒍𝒆𝒔 𝒊 ∗ 𝑻𝒓𝒂𝒄𝒕𝑷𝒐𝒑𝒖𝒍𝒂𝒕𝒊𝒐𝒏 𝒊
where i indexes gender-age group categories.

58. Example of use for pedestrian infrastructure analysis

59. Example of use for cycling infrastructure analysis

60. tract-level walking estimates: San francisco
Weekday Miles
Walked Per
Non-Highway
Road Mile

61. tract-level walking estimates: Los angeles

62. tract-level biking estimates: san francisco
Weekday Miles
Biked Per
Non-Highway
Road Mile

63. tract-level biking estimates: los angeles

64. tract-level biking estimates: los angeles

65. Example use for safety analysis

66. Example use for safety analysis

67. Map of accidents per distance walked in san francisco
Annual Severe
Pedestrian
Accidents Per
1000 Weekday
Miles Walked

68. Map of accidents per distance walked in los angeles

69. conclusions
The method used here can provide estimates of cyclist and pedestrian activity based on travel survey and census data, without a full travel model
The estimates here of miles of activity per road mile are highly correlated with tract population density
The CHTS data produce somewhat lower estimates of bike/walk activity
It would be interesting to compare these results with those from a full travel model, if available
Contact:

70. Questions/Comments