Spatial competition between parking garages and downtown parking policy

This paper looks at optimal parking policy in dense urban districts (“downtown”), where spatial competition between parking garages is a key feature, from the perspective of economic theory. The paper has four parts. The first looks at the “parking garage operator's problem”. The second derives equilibrium in the parking garage market when there is no on-street parking, compares the equilibrium to the social optimum, and examines optimal parking policy in this context. Since parking garage operators have market power, the spatial competition equilibrium is generally inefficient, and parking policy can be used to mitigate the distortion. The third adds on-street parking and considers how its underpricing affects second-best parking policy. The fourth adds mass transit, and considers how economies of scale in mass transit interact with minimum and maximum off-street parking standards.Preliminary draft: Please do not cite or quote without the permission of the author.     

Response to cash outs for work place parking and work place parking charges

Free work place parking has long been considered to have a strong influence on whether or not individuals use their car for their trips to work. A survey of local authority employees was conducted to examine their potential responses to the removal of free work place parking spaces, how they would respond to parking cash-out policies and to work place parking charges, and finally their responses to specific values of cash out payments. It was found that as age increases individuals are less likely to accept any form of cash out. When individuals have one or more cars available they are more likely to opt for a cash out scheme. Females are more likely to opt for the various cash out schemes than males. The results seem to suggest that if an individual has a higher income it does not necessarily mean they will opt to keep their space.     

A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus,Ohio

Improving job accessibility based on transport connectivity helps to address equity issues. Spatial autocorrelation (SA) is also a focus of interest in transportation planning, but has been neglected in analyzing job accessibility in metropolitan areas. In this study, GIS-based job accessibilities by walking, transit, and car are computed for the metropolitan area of Columbus, Ohio, and three transport-based spatial autoregressive (SAR) models are estimated to account for the SA of job accessibility among neighboring block groups, while controlling for built-environment and socioeconomic factors. SA intensities and extents are compared in order to better understand local spatial clusters of job accessibility across the region. Direct and indirect spillover effects due to an investment change in transportation facilities are estimated and provide important transportation planning information. The results also show that walking-accessed jobs are primarily related to physical settings (e.g., land uses) at the local level. Locations with a higher share of zero-vehicle housing units have better job accessibility by transit. There is a spatial mismatch between Asian population clusters and transit-accessed jobs, possibly because of the car-oriented residential clusters around Honda of America Manufacturing in suburban areas. More importantly, locations with a higher share of single-parent households are at a disadvantage in overall job accessibility. Due to its complex transportation needs, a society friendly to single parents should spatially integrate accessible jobs with other needed activities via land-use and transportation planning. Alternatively, car-ownership programs and non-spatial social supports also might be effective to help secure job opportunities and perform daily life activities.     

Data-mining,GIS and multicriteria analysis in a comprehensive method for bicycle network planning and design

In many Brazilian cities, the most common procedure for planning cycling networks is using aggregated population data in census tracts, which may not take into account the true origin and destination of trips. It may also not identify potential users of a particular mode of transport. This is particularly important considering that implementing cycling infrastructures should be based on the assumption that they are able to meet the users' needs. Therefore, the aim of this study is to develop and adopt an objective method to design and compare cycling networks based on data-mining of disaggregated origin-destination data, GIS resources, and multicriteria analysis techniques. The method follows three steps: 1) identifying potential users based on real user profiles, 2) designing proposed cycling networks and 3) a comparison between the networks proposed in this study and those developed by the municipality selected as a case study, considering real and potential users, as well as cost and benefit criteria. As a positive outcome, using disaggregated data allows for a reasonable estimate of the number of people served by the networks, a detailed analysis of their proximity to the infrastructure, as well as identifying potential users. Comparing cycling networks considering cost and benefit criteria shows that the chosen criteria were effective. It was also determined that the cycling network of the studied city poorly serves bicycle transport users, if compared to the proposed networks. These findings indicate that appropriate methods for planning cycling networks are still needed.