The paper explores how the built environment and weather impact travel patterns in Weinan, a medium-sized city in China with a bus-focused transit system. The research used #machinelearning analysis on data from multiple sources and found that residential and commercial density significantly influence #travelbehavior at both origin and destination locations, while some factors have different effects at the origin versus destination. (2/3)
The #Covid19 pandemic affected commuting #TravelBehavior, with soft modes emerging as reliable options for short-distance trips. This paper focuses on evaluating the bike-friendliness of Venice, evaluating the potential for using bicycles to reach the historic city center from the mainland. One critical issue identified is the inadequate provision of bike parking, which must be addressed to position bicycles as a competitive and viable alternative for commuting. (2/2)

Just dropping in to say it's possible to own a #car *and* prefer getting around by other modes most of the time.

Habituation to #driving is not an insurmountable obstacle to reducing #automobile dependency and creating safer, greener, more resilient cities. Habits can be broken if the right supports are available at the right time.

#ClimateChange #Cars #TravelBehavior (1/2)

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

Heterogeneity in mode choice behavior: A spatial latent class approach based on accessibility measures | Journal of Transport and Land Use

"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

Land-use patterns, location choice, and travel behavior: Evidence from São Paulo | Journal of Transport and Land Use

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
Marked crosswalks (432')
29.6%
Shortest distance (162')
25.9%
A combination route
44.4%
Poll ended at .
Bevor Sie zu Google Maps weitergehen