High Mixed Land Use Research Articles

Impacts of the Feeder-Related Built Environment on Taxi-Metro Integrated Use in Lanzhou, China

It is very common that taxi is used as a feeder mode to/from a metro station especially in third-tier cities of China. But research on taxi-metro integrated use is rather limited. This paper investigates the relationship between feeder-related built environment and taxi-metro integrated use by using taxi trajectory data in Lanzhou, China. Firstly, regression models are developed to explore the transfer distance of access/egress trips during peak hours. Then, the catchment area is delineated for collecting feeder-related environment variables. Finally, several negative binomial regressions are employed to examine the relationships between feeder-related built environment and taxi-metro integrated use during peak hours on weekdays. The results reveal that (a) people prefer to use taxi as feeder mode for metro access during morning peak hours and for metro egress during evening peak hours; (b) the transfer distance of taxi-metro integrated use is about 3.8 km; (c) higher mixed land use generates more taxi-metro integrated use during evening peak hours. Higher proportion of residential land use attracts more taxi-metro integrated use for metro access during morning peak hours. Those findings will help transport planners to develop tailored land-use interventions to improve transit accessibility and promote the sustainable multimodal travel.

Walking Behavior in Temuco, Chile: The Contribution of Built Environment and Socio-Demographic Factors.

The increase in active travel contributes to maintaining the minimum rate of physical activity and therefore has a positive impact on inhabitants’ public health. The level of walking for daily transport has decreased significantly during the last decades in Temuco, Chile. This study examined the contribution of socio-demographic factors, active family environment, and built environment factors to walking behavior and walking level based on three types of destination in Temuco. The results of Encuesta Origin Destino (EOD 2013), geographic information system (GIS), and, finally, hierarchical multiple regression analysis were used to examine the objectives. Correlations were found between total walking behavior, walking level based on three destination types, and several socio-demographic factors such as age, gender, and access to TV and Internet. Furthermore, correlations were found between walking behavior and active family environment, as well as several built environment factors. For instance, the higher mixed land use as well as number of parks and plazas contribute towards more overall walking as well as two types of walking. Identifying that most persons who walk come from low-income families and the negative impact of network connectivity on overall walking are the major differences between this context and developed countries.

Modeling Injury Severity of Unconventional Vehicle Occupants: Hybrid of Latent Segments and Random Parameters Logit Models

Road safety research in developing countries has evolved in two categories: (a) crash frequency prediction modeling and (b) injury severity analysis. In injury severity analysis, the focus is to identify the influential factors for different injury severity categories. However, limited research has been undertaken in this domain, especially to assess the injury severity of the occupants of unconventional vehicles (UVOs) (including both human-pulled and engine-operated vehicles). This study investigates the injury severity of UVOs in Dhaka, Bangladesh adopting a hybrid of latent segments and random parameters logit (LSRPL) models. The model is developed utilizing police-reported collision records for the years 2011–2015. The LSRPL model captures multi-dimensional heterogeneity by allocating victims into discrete latent segments (i.e., inter-segment heterogeneity) and allowing a continuous distribution of parameters within the segments (i.e., intra-segment heterogeneity). The model is estimated for two segments using victim and crash attributes, where segment one is lower risk and segment two is higher risk. The model results suggest that victim and driver profiles, crash attributes, environmental factors, road network attributes, transportation infrastructure, and land use attributes influence the injury severity of UVOs. The model confirms the existence of significant inter-segment heterogeneity. For example, mid-block crashes are more likely to result in severe injury in higher-risk segments, and less likely to result in severe injury in lower-risk segments. The model further confirms intra-segment heterogeneity for areas with higher levels of mixed land use. For example, for mid-block crashes, higher mixed land use shows a significantly lower mean in high-risk segments, revealing lower likelihood of sustaining severe injury.

Modelling the adoption of autonomous vehicle: How historical experience inform the future preference

This study investigates individuals’ preference towards autonomous vehicle (AV) as a privately-owned vehicle and as a vehicle in shared services. One of the key features of this study is to examine the effects of historical changes and experiences over the life course towards the adoption of AVs. A joint bivariate ordered probit model is developed using data from a retrospective survey conducted in the Okanagan region of British Columbia, Canada. The model captures unobserved error correlation between the response variables: preference towards AV ownership and using AV as a vehicle in shared services. The model confirms the existence of a significant error correlation between preferences for AV ownership and sharing. The model results suggest that AV adoption is significantly affected by individuals’ historical experiences over the life course, such as exposure to technology, household characteristics, vehicle ownership, and accessibility and built-environment attributes of the residential location. For example, individuals with historical exposure to technologies including average smartphone ownership/person in the household over the life course and availability of advanced vehicle technology such as lane assist, parking assist, and autonomous emergency stop in the current and previously owned vehicles are more likely to adopt AVs. Individuals historically living in suburban areas have a higher likelihood of owning AVs whereas historically urban dwellers living in higher mixed land use neighbourhoods over the lifetime are more likely to prefer AV sharing. Ownership of technology devices such as smartphones and google home may lead to owning as well as sharing AVs. In addition, the model retains the effects of attitudinal factors, and socio-demographics. For instance, pro-environment individuals are likely to own and share AVs. Pro-shared-mobility individuals are more likely to share AVs whereas they are less interested in owning.

Evaluation of Preferences for Alternative Transportation Services and Loyalty towards Active Transportation during a Major Transportation Infrastructure Disruption

This paper investigates active transportation mode users’ preferences for alternative services during the temporary closure event of a bridge and its active transportation (AT) lanes. It also evaluates the loyalty of AT users during the event. The study uses data from a travel survey distributed to cyclists and pedestrians, who are the regular AT lane users of the Macdonald Bridge in Halifax, Canada. Random parameter logit models are developed in this study that examine the effects of socio-demographic, travel and neighborhood characteristics on active transportation users’ preferences. Four alternative transportation services are considered in this study: free shuttle services, frequent ferry services, frequent bus services and other services. Results suggest that higher-income individuals are more likely to prefer frequent ferry services during the AT lane closure event. Transit commuters are found to prefer frequent bus services. Probability of preferring free shuttle services increases if individuals use AT lanes for cost savings. Loyalty towards AT is explored in this study by means of anticipated modal shift. For instance, higher mixed land use area dwellers tend to be loyal towards AT during the disruption event, as demonstrated by their lower probability to shift from current AT mode. This study offers critical behavioral insights, which would assist transportation planning and policies that aim to adopt sustainable transportation planning measures to retain current users’ loyalty towards active transportation and prevent a long-term behavioral shift.

Exploring car ownership and car use in neighborhoods near metro stations in Beijing: Does the neighborhood built environment matter?

Public transport services are believed to play an important role in constraining car use. However, it has been found that cars are still used at high rates near many metro stations. This paper aims to explore car ownership and car use in people living close to metro stations. Taking Beijing, China, as a case study, this study shows that the likelihood of owning a car, and the number of work and non-work vehicle kilometers traveled (VKT), is lower in areas with higher mixed land use. Residents’ income and family structure both affect VKT. People with an awareness of sustainable land use and transportation modes use fewer VKT. The study also has some interesting new findings in the Chinese context. It found that residential density was not significantly related to VKT. Interestingly, neighborhood type was firmly associated with car ownership and use: those who live in Danwei neighborhoods generated more work VKT, and those living in indemnificatory neighborhoods used more non-work VKT. Additionally, renters were less likely to own cars than house owners, and people with Beijing hukou generated more VKT. People preferring to live in close proximity to the metro system and travel by foot were more likely to own cars in the future than other people. The results suggest that increasing land use diversity and the accessibility of living amenities in neighborhoods near metro stations could enhance the performance of transport systems by reducing dependence on cars. Housing and transport policies, along with behavior-education programs, could strengthen this effect.

Abstract B65: Development of neighborhood “obesogenic factors” and its applicability to obesity and cancer studies in diverse populations: The Multiethnic Cohort Study

Abstract Background: Although social and built environment attributes are associated with obesity, limited research has characterized their underlying relationships and differential effects across race/ethnicity. Our study developed composite measures of the neighborhood obesogenic environment for California and investigated their associations with obesity and breast, colorectal, and prostate cancer risk within the Multiethnic Cohort Study (MEC). Methods: Principal component factor analysis (PCFA) was conducted to characterize block group-level obesogenic environments in California. Nine neighborhood attributes derived from geospatial data were selected based on their potential to contribute to obesity: population density, traffic density, commuting by car/motorcycle, numbers of businesses, parks, recreational facilities, restaurants, retail food outlets, and street connectivity. Multinomial logistic regression was used to examine associations between neighborhood obesogenic factors and obesity at baseline by sex and race/ethnicity (African American (AA), Japanese, Latino and White) in the California component of the MEC (n=102,906; obese=24,701). Multivariable Cox proportional hazards regression was used to examine associations between these neighborhood obesogenic factors at baseline and risk of breast (n=48,247; cases=2,341), colorectal (n=81,187, cases=1,973), and prostate (n=41,565; cases=4,650) cancers in the California MEC, overall and stratified by race/ethnicity. Results: PCFA identified four neighborhood obesogenic factors: 1) “urban environment” (high population density, high street connectivity, low commuting by car/motorcycle, high traffic density); 2) “mixed land use” (high number of recreational facilities and businesses); 3) “unhealthy food outlets” (high ratios of unhealthy to healthy for restaurants, and for retail food outlets); 4) “parks” (any parks). For males, less urban environments among AAs and Whites; lower mixed land use among Latinos; and any parks among AAs were associated with increased odds of obesity. For females, more unhealthy food outlets among Whites was associated with increased odds of obesity. For breast cancer, more unhealthy food outlets for all racial/ethnic groups combined and lower mixed land use in Latinos were associated with increased risk of disease. For colorectal cancer, some unhealthy food outlets for all groups combined, higher mixed land use in Japanese males, no parks in AA males, and lower mixed land use in White females were associated with increased risk of disease. For prostate cancer, higher mixed land use in Whites was associated with increased risk of disease and more unhealthy food outlets in AAs was associated with increased risk of aggressive disease. Conclusion: The associations between the four neighborhood obesogenic factors with obesity and cancer risk varied across sex and race/ethnicity, demonstrating the complex relationships involved in cancer disparities. Citation Format: Salma Shariff-Marco, Li Tao, Juan Yang, Alison Canchola, Christina Clarke, Yurii Shvetsov, Shannon Conroy, Song-Yi Park, Andrew Hertz, Cheryl Albright, Laurence Kolonel, Kristine Monroe, Loic Le Marchand, Lynne Wilkens, Scarlett Lin Gomez, Iona Cheng. Development of neighborhood “obesogenic factors” and its applicability to obesity and cancer studies in diverse populations: The Multiethnic Cohort Study. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr B65.

Built Environment and Household Electric Bike Ownership

Planners and policy makers have recognized the effects of the built environment on vehicle ownership and use. Within the voluminous literature, however, few studies have examined how the built environment was associated with household electric bike (e-bike) ownership. This study explored the relationship between the built environment and household e-bike ownership in the Chinese context, on the basis of data collected in the Zhongshan Metropolitan Area. The e-bike choice models suggested that household measures dominated the number of household e-bikes, but the models also detected a relationship between several built environment attributes and household e-bike ownership. All else being equal, denser and higher mixed land use development, more connective transportation links, and accessibility to commerce and jobs were related to lower household e-bike ownership. Households located in urban neighborhoods tended to own fewer e-bikes than those in suburban or rural areas. The availability of competitive transportation modes was strongly related to the likelihood of e-bike ownership. The results suggested that policy makers should consider built environment attributes with respect to policies on e-bike ownership and set different policies in different areas according to the variations in the built environments. The findings also suggested that e-bike ownership policies should be integrated with ownership policies on competitive modes and with policies related to public transportation service improvement.

Association between residents’ perception of the neighborhood’s environments and walking time in objectively different regions

The purpose of this study is to delineate the association between residents' perception of the neighborhood's environments and walking time in objectively different regions in Japan. Two regions were selected as high and low walkable regions on the basis of differences in their residential density, mixed land use and street connectivity. The subjects in this study were participants in a health promotion program focused on walking sponsored by local governments. A questionnaire was sent to the participants asking about how their perception of the neighborhood's environment related to walking, and the time spent walking per week. There were 237 residents from the high walkable region and 195 from the low walkable region who completed the study survey. The high walkable region had a larger residential density, a high mixed land use and a higher street connectivity than the low walkable region. Walking time, and the scores of the perception of the neighborhood's environment for the high walkable region residents were significantly higher than those for the low walkable region residents. Thus, residents' perception of the neighborhood's environment generally reflected the actual physical environmental characteristics. Residents in the high walkable region whose scores for accessibility and aesthetics were high, spent significantly more walking time. Residents in the low walkable region whose scores for accessibility, safety, convenience and aesthetics were high, spent significantly more walking time. The study results suggested that the neighborhood's environment may influence daily walking time. The perceptions of the neighborhood's environmental factors that correlate with walking times differ between the different regional physical environments. Therefore, to promote physical activity, the consideration of environmental factors unique to residents' neighborhood's environments is needed.