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Transit-based job accessibility and urban spatial structure
Abstract Job accessibility is a measure of people, opportunities, and transportation system that are fundamental elements of urban spatial structure. Therefore, job accessibility can be used as a tool to understand urban spatial structure. Studying transit-based job accessibility can provide more insight into inner cities. To study transit-based job accessibility, a person-based approach is needed in order to take full consideration of the elements. However, person-based approaches are substantially restricted by the availability of individual trip data. This paper takes a simulation approach to study transit-based job accessibility. First, transit-dependent worker agents are generated using a population synthesis. Then the agents are enabled with job search and commuting capabilities. Once the agents are deployed in a commuting simulation, individual commuting trips are recorded. An individual job accessibility index is developed based on simulated commuting trips. The index is normalized with an expected value of 1.0 and a measurable uncertainty level, which makes it easy to interpret and suitable for cross-regional studies. A case study is conducted in Tucson, Arizona, where about 10,000 transit-dependent worker agents produce more than 600,000 individual commuting trips during morning and afternoon peak hours. Census block, group-level job accessibility shows a random spatial pattern that coincides with a dispersed urban spatial structure of the case study area.
Transit-based job accessibility and urban spatial structure
Abstract Job accessibility is a measure of people, opportunities, and transportation system that are fundamental elements of urban spatial structure. Therefore, job accessibility can be used as a tool to understand urban spatial structure. Studying transit-based job accessibility can provide more insight into inner cities. To study transit-based job accessibility, a person-based approach is needed in order to take full consideration of the elements. However, person-based approaches are substantially restricted by the availability of individual trip data. This paper takes a simulation approach to study transit-based job accessibility. First, transit-dependent worker agents are generated using a population synthesis. Then the agents are enabled with job search and commuting capabilities. Once the agents are deployed in a commuting simulation, individual commuting trips are recorded. An individual job accessibility index is developed based on simulated commuting trips. The index is normalized with an expected value of 1.0 and a measurable uncertainty level, which makes it easy to interpret and suitable for cross-regional studies. A case study is conducted in Tucson, Arizona, where about 10,000 transit-dependent worker agents produce more than 600,000 individual commuting trips during morning and afternoon peak hours. Census block, group-level job accessibility shows a random spatial pattern that coincides with a dispersed urban spatial structure of the case study area.
Transit-based job accessibility and urban spatial structure
Huang, Ruihong (author)
2020-05-19
Article (Journal)
Electronic Resource
English
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