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Introduc4on
1Ins.tue of Transporta.on Studies, University of California, Irvine , CA, USA. 2Dept. of Civil Eng., University of California, Irvine , CA, USA
Thuy T.B. Luong 1 , Will Recker 2
ANALYSING HOW SOCIO-‐DEMOGRAPHIC CHARACTERISTICS ASSOCIATE PUBLIC TRANSIT USAGE A COMPARISON BETWEEN SOUTHERN AND NORTHERN CALIFORNIA
94th Annual Mee.ng of Transporta.on Research Board, January 2015, Washington, D.C., USA.
• The National Household Travel Survey, 2009
• Select by Metropolitan Statistical Areas (CBSA) Codes • South: 2446 individuals from Los Angeles-Long Beach-
Santa Ana, San Diego-Carlsbad-San Marcos, Riverside-San Bernardino-Ontario
• North: 1605 individuals from San Jose-Sunnyvale-Santa Clara, Sacramento--Arden-Arcade—Roseville, San Francisco-Oakland-Fremont
Data
• California needs transit systems that are smart and diverse to make them more viable and effective for commutes.
• Knowledge about California transit riders’ characteristics and how they affect transit usage still is lacking.
• Investigates the differences in transit usage between people in Southern and Northern California.
• Transit riders’ socio-demographic and travel attitudes are accounted for in the comparison between the regions.
Source: Google Map 2014, US Census Bureau
Most of the determining socio-demographic variables - race, education, employment status, age, household income – are significantly different between the Northern and the Southern transit riders, while gender showed no significant difference (chi square test).
Results A series of multivariate regressions were performed to identify the characteristics of those in each region who prefer to take transit. The results show that the socio-demographic factors associated with frequency of taking transit that vary between the regions.
Predictors South North Model 2
y = PTUSED Model 1
y = log(PTUSED) Model 3
y = PTUSED Model 4
y = log(PTUSED)
(Intercept) 16.473 *** 1.837 *** 14.761 *** 1.568 *** African American, Black -‐0.400 0.114 0.095 Asian Only 0.999 0.248 * -‐0.058 Other race -‐1.247 -‐0.037 3.313 Hispanic/Mexican 3.200 ** 0.237 ** -‐3.828 Number of drivers 1.602 * 0.169 ** 1.287 $25,000 -‐ $44,999 -‐2.476 * -‐0.248 ** -‐1.249 $45,000 -‐ $64,999 -‐3.215 ** -‐0.436 *** 0.255 $65,000 -‐ $79,999 -‐3.609 ** -‐0.436 *** -‐0.962 $80,000 -‐ $99,999 -‐3.712 ** -‐0.403 *** -‐1.865 more than $100,000 -‐4.218 *** -‐0.343 *** -‐1.034 HH size -‐0.616 * -‐0.065 ** -‐1.347 ** -‐0.127 *** Number of vehicles -‐2.597 *** -‐0.236 *** -‐2.399 *** -‐0.209 *** Number of adults 1.345 0.084 1.313 0.261 *** Number of workers -‐0.085 0.245 Foreign born -‐0.759 2.048 * 0.152 * Has driver status -‐0.805 0.234 * 2.578 0.264 Some college or Voca4onal 0.456 0.044 1.399 0.264 ** Bachelor -‐1.440 -‐0.127 1.227 0.170 Graduate or Professional -‐1.949 -‐0.112 1.099 0.197 * Access to/availability of public transit 6.203 *** 0.508 *** 6.405 *** 0.684 *** Lack of walkways or sidewalks 2.715 0.041 0.538 -‐0.157 Price of travel 0.205 0.041 0.946 0.219 ** Aggressive / distracted drivers 0.178 -‐0.087 0.701 0.082 Safety concerns 0.075 0.006 -‐0.132 0.026 AGE -‐0.040 -‐0.006 *** -‐0.105 *** -‐0.007 *** Male -‐0.659 -‐0.112 * -‐1.192 -‐0.174 ** Not a worker -‐3.193 *** -‐0.203 *** -‐4.113 *** -‐0.327 ***
DF 2418 2410 1577 1578 p-‐value <2.2e-‐16 <2.2e-‐16 <2.2e-‐16 <2.2e-‐16 Adjusted R-‐squared 0.104 0.147 0.101 0.142
signif.codes: '***' 0.001 '**' 0.01 '*' 0.05
• A significant association between region and views on public transit.
• The models were able to distinguish between respondents
who did and did not take transit and between regions.
• Major differences between regions in trends in propensity to use public transit related primarily to race, ethnicity, and income.
Conclusion
Income
Race Educa.on
Rela.onship with other factors
AXtudes
Clustering family characteris.cs
North
South
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