摘要: |
Via strong agency and non-profit collaborations, the research team seeks to leverage advances in technology and increasing access to high-resolution remote sensing and spatial data to develop methods for inventorying sidewalk characteristics and static barriers across an entire major city. Thus far, such work has only been done for relatively small areas but not yet at the city scale. In-kind data from an on-demand mobility analytics platform will then be harnessed to develop a data-driven methodology to prioritize sidewalk infrastructure investments. The team will rely on the trip data to find locations with high levels of short trips being made by automobile and combine that with crash data, socio-demographic data, socio-economic data, and land use data (such as schools) to overlay on top of the sidewalk infrastructure analysis. The project team will then conduct a life cycle assessment, coupled within a systems dynamics modeling framework, of sidewalk infrastructure to better understand, for example, the benefit of routine, preventative maintenance as compared to current practice. The result of this project will help transition the transportation community towards a state-of-the-art approach to the management and monitoring of sidewalk infrastructure. |