Can the #BuiltEnvironment actually influence #TravelBehavior?

In this brand new #OpenAccess paper, “Heterogeneity in mode choice behavior: A spatial latent class approach based on accessibility measures,” authors Orrego-Oñate, Clifton, & Hurtubia tackle this age-old question by developing a novel, probability-based approach to estimating #travel #ModeChoice. (1/3)

https://www.jtlu.org/index.php/jtlu/article/view/2115

#JTLU #transport #LandUse #Research #TravelBehaviour

I stumbled upon an article from my institute's quarterly bulletin from 1951 that asks, "How Essential Are Automobiles?" which summarizes this report from Brookings: "Automobile Transportation in Defense of War"

https://hdl.handle.net/2027/uc1.$b98980

It posits that 55% of all driving is home-to-work trips.

#transportation #CarCulture #TravelBehavior

"Land Use Patterns, Location Choice, and Travel Behavior: Evidence from #SãoPaulo""

#LandUse influences #TravelBehavior, even in a #GlobalSouth metropolitan area with strong income-based spatial segregation.
Millennials in Global South metros prefer living in central, accessible, and mixed areas, owning fewer and using #PublicTransit & #NonMotorized modes.

#OpenAccess

In Vol 15 of #JTLU: https://www.jtlu.org/index.php/jtlu/article/view/2125

João de Abreu e Silva & Shanna Lucchesi, 2022

What makes a bikeable neighborhood?
As this 2019 #OpenAccess paper
in #JTLU by Salon, Conway, Wang, & Roth suggests, the answer depends in part on age and gender.

"Heterogeneity in the relationship between biking and the built
environment"

https://www.jtlu.org/index.php/jtlu/article/view/1350/1226

#TravelBehavior #BuiltEnvironment #ActiveTravel #GenderAndTransport

#TravelBehavior #Question:
If you need to #walk from the southwest side of this intersection to the northeast side, do you follow the marked crosswalks (total distance 432', 15 total traffic lanes crossed) or take the straightest path (162', ~7 lanes)?
https://www.google.com/maps/place/35%C2%B039%2727.4%22N+78%C2%B050%2754.8%22W/@35.6576778,-78.848735,101m/data=!3m1!1e3!4m4!3m3!8m2!3d35.65761!4d-78.8485443