In the United States, urban form and design changed tremendously during the twentieth century. From the early twentieth century, a time when small-scale, highly diverse city blocks or what Douglas Rae called “urbanism” predominated, urban redevelopment came to be dominated by large-scale modernist superblocks, often promoted by federal policy. In the last two decades of the century, some urban designers argued for recapturing the physical qualities of the premodern city, while others argued that large-scale, autonomous city areas were both inevitable and ideal.
Since the 1980s, Detroit’s historic building stock of automotive manufacturing facilities has mostly disappeared. Demolition, redevelopment, and abandonment have left little to mark the city’s twentieth-century history as the world capital of the automobile industry. Planning and policy making have been complicit by publicly subsidizing destructive redevelopment and by failing to advocate for retention or preservation of significant structures and complexes. Even today, Detroit’s leadership calls for the demolition of one of the city’s last remaining historic auto factories.
This research investigates the usage of smart devices and time at bus stops and on buses in Vancouver, Canada. Using passive observations and self-reported surveys mainly from college students, the majority of passengers were found to use their travel time actively. Most of the observed active activities are associated with the usage of smart devices. However, while the possession of smart devices is prevalent, less than one third of passengers used them during travel.
Automatic data collection (ADC) systems are becoming increasingly common in transit systems throughout the world. Although these ADC systems are often designed to support specific fairly narrow functions, the resulting data can have wide-ranging application, well beyond their design purpose. This paper illustrates the potential that ADC systems can provide transit agencies with new rich data sources at low marginal cost, as well as the critical gap between what ADC systems directly offer and what is needed in practice in transit agencies.
Excess journey time (EJT), the difference between actual passenger journey times and journey times implied by the published timetable, strikes a useful balance between the passenger's and operator's perspectives of public transport service quality. Using smartcard data, this paper tried to characterize transit service quality with EJT under heterogeneous incidence behavior (arrival at boarding stations). A rigorous framework was established for analyzing EJT, in particular for reasoning about passenger’ journey time standards as implied by varying incidence behavior.
A subjective measure of car dependence was developed based on people’s own assessment of their reliance on car use. The measure supplements the commonly used objective measure based on actual car use. Structural equation models (SEM) were estimated to quantify the subjective dependence and to examine its determinants: demographics, socioeconomics, and land use and transit access. The comparison between subjective dependence and actual car use discloses significant differences between both measures despite their statistical linkage.