Browsing by Subject "traffic congestion"
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Item Identification of the relationship between economic and land use characteristics and urban mobility at the macroscopic level in Texas urban areas(Texas A&M University, 2004-11-15) Schrank, David LynnTraffic congestion continues to be a growing problem for cities of all sizes in the United States. Transportation agencies in urban areas are facing the difficult challenges of providing an efficient and reliable transportation system for residents and businesses despite ever-diminishing resources. Agencies in these areas need the capability of determining the future benefits of transportation investments so they can communicate this information to the public. This capability is difficult for many agencies, especially some of the smaller ones, who may not have the resources to make these analyses without turning to expensive long-range models. This research uses readily available socio-economic, land use, and traffic congestion data from many of the Texas urban areas to create prediction models to estimate future traffic congestion levels. Many of the transportation agencies that could utilize this tool do not have the resources to deal with large complex databases. Thus, basic information such as income, employment, single family residences, or commercial properties, to name a few, is used to create the predictions models. Results from this research show that traffic congestion prediction models can be created from socio-economic and land use data. These models were created for eighteen individual Texas urban areas and several combinations of areas. Transportation agencies could use the results of this research to estimate future congestion in their respective areas.Item The effectiveness of jobs-housing balance as a strategy for reducing traffic congestion: a study of metropolitan Bangkok(Texas A&M University, 2006-10-30) Lobyaem, SonchaiBangkok is widely known for its severe traffic congestion. The Thai government advocates the concept of jobs and housing balance (JHB) as a strategy for reducing traffic congestion in Metropolitan Bangkok. The basic idea is to decentralize the jobs to the neighboring provinces so that the commuters would live closer to their workplaces and thereby alleviate traffic congestion. The main purpose of this research is to examine empirically the effectiveness of JHB in reducing the severity of traffic congestion in the Bangkok Metropolitan Region. For this purpose, three data sets derived from the Bangkok Metropolitan Region Extended City Model (BMR-ECM) were obtained from the Office of the Commission for the Management of Land Traffic and the National Statistical Office of Thailand. Travel time index (TTI) was developed to measure congestion. In addition to JHB, a number of land use variables were included in the analysis. They are population density, school density, and job accessibility index. Multiple regression models of TTI as functions of JHB and other variables were estimated at two geographic scales: subsector and traffic analysis zone (TAZ). The study finds JHB is significant in influencing congestion levels in the Bangkok Metropolitan Region. Other influential factors include the population density, school density, and job accessibility. All of these factors are found to be statistically significant in explaining the variation of traffic congestion at the traffic analysis zone level, but not at the subsector level, however.