In the postwar United States, cities used downzoning policies to limit construction, often for the sake of preserving neighborhood aesthetics and protecting property values. We show that downzonings in Chicago between 1970 and 2016 were more frequently implemented in high home value areas. We evaluate downzoning’s consequences by comparing outcomes between Chicago tracts that were subjected to this regulatory change and those that were not, using fixed-effects regressions. In downzoned areas, housing supply declined, but housing values and white population shares increased. Overall, downzoning has contributed to reduced housing availability in high-demand neighborhoods, while reinforcing class and racial segregation.

The area of an individual’s daily activity space may be constrained by difficulties traveling long distances or by proximity advantages in dense areas that reduce the need to travel far from home. Using travel diary data from 327 individuals in Granada, Spain for both a weekday and a weekend, this study examine the relationship between activity space areas and destination accessibility by car and non-car modes. We find that lower accessibility is associated with smaller activity spaces on weekdays, while weekend activity space areas are better explained by household resources. We interpret these patterns using a constraints-versus-freedom lens.

This study examines whether adolescents are more likely to cycle to school when their parents do, and whether this influence differs between female and male adolescents. Using 3,017 school trips from the Victorian Integrated Survey for Travel and Activity (VISTA), separate multinomial logit models were estimated for each group. Findings show that parental cycling significantly increases adolescents’ likelihood of cycling, with a stronger effect for females. These findings demonstrate that parental behaviour plays a crucial role in shaping active school travel.

Perceptions are often measured on unanchored scales, making it difficult to compare across individuals. I address this challenge by comparing how respondents rate speeding versus behaviors near universally regarded as dangerous. Results show that most respondents see speeding—especially on arterials—as much less dangerous than drunk or distracted driving. Correcting this misconception offers an opportunity to shift opinions on traffic cameras, which are effective but underutilized. A survey experiment reveals that a brief safety message increases support among those who initially underestimated the dangers of speed. Scholars should employ relative scales and practitioners should emphasize the risks of speed.

Big data from mobile phones are increasingly used in transport research and planning, offering unprecedented spatial and temporal detail. However, data accuracy remains unclear. This study evaluates Replica, a dataset modelled from mobile phone GPS data, by comparing modeled volumes for motor vehicles, bicycles, and pedestrians against field counts in Santa Barbara, California. Car volumes were modeled with high accuracy (R² = 0.92), while bicycle (R² = 0.23) and pedestrian (R² = 0.05) estimates showed substantial uncertainty. When using transport data generated from mobile phone GPS, additional caution is needed for non-motorized modes.

We introduce Access Surplus as a welfare measure that frames accessibility in a market-like form: the inverse cumulative cost to reach the next opportunity is the ‘supply,’ and the willingness to pay for one more choice is the ‘demand.’ The area where demand exceeds supply, up to a natural stop point, is Access Surplus . The metric avoids arbitrary cut-offs, is additive over residents, links clearly to project effects, and stays transparent when only origin–destination times and counts are available.

Construction of public transport infrastructure often disrupts daily life, but the extent of its perceived impact depends on residents’ subjective proximity to it. In 2018, Montreal began building the Réseau Express Métropolitain (REM), a 67-km grade separated light rail network. Using 2022 survey data (N = 4,065), we model how residents define being “near” to the project’s construction from their home, work, and school locations. Results show that perceived closeness to construction varies by context, sociodemographic characteristics, and mode-use patterns. Our findings can help better understand people’s perceptions of proximity to construction sites, which can spatially direct mitigation measures.

This is an exploratory analysis of 100 ‘family cycling’ images sourced from Google UK’s Image search. No depicted riders presented clearly visible disabilities, and images of larger bodies were rare. Most riders were white. The cycling family was usually portrayed as ‘nuclear’, comprising one man, one woman, and one to three children. Motor vehicles or pedestrians were rarely shown sharing space with people cycling; however, no images showed separated cycling infrastructure. These findings suggest a need to diversify images of ‘family cycling’ in relation to disability, body size, family structure and ethnicity, and including images of newer, separated cycling infrastructure.

Using a Swiss national survey, we explore three questions that can support better bicycle parking planning: 1) What destinations are the most likely to have bicycle parking? 2) Do trips by e-bikes more frequently end with parking at destinations than those by regular bicycles? 3) Is available bicycle parking at the destination for bicycle trips as frequent as free car parking? Results suggest a relative undersupply of bicycle parking at destinations compared with free car parking, an increasing need for bicycle parking for costlier e-bikes, and the identification of destination types where bicycle parking is most lacking.

Recent research shows that while total crashes decreased during COVID-19 stay-at-home orders, risky driving rose, leading to more severe crashes. This study examined how the pandemic impacted crash injury severity across demographic groups in California. Using over 1.4 million records from 2019 to 2021, logistic regression identified that young and Black drivers faced higher odds of severe crashes during the pandemic.