National Science Foundation Convergence Accelerator MicroBoost Transportation Project
Project Description:
Hourly workers living in the under resourced regions that are far from jobs are increasingly vulnerable
to the spatiotemporal mismatch between housing and jobs. Whereas the existing public transportation options are neither reliable nor flexible to catch up with the irregular shifts and on-call work schedules, microtransit service has emerged as a viable option to complement the existing public transit options. Despite the initial success of the on-demand microtransit service, a salient issue is how to effectively and efficiently utilize microtransit resources to ameliorate spatiotemporal mismatch between employment and housing, particularly from riders suffered from digital divide. With increasingly available mobility and built environment big data from urban cities, our research vision is to create a human-centered Artificial Intelligence (AI) technology to determine when and where to pickup/drop low-wage workers incorporating rider's inputs and couple with a resource- and time-aware dynamic routing prediction system based on the hourly cross-region mobility patterns between mobility hubs in residential and job-rich Census Block Groups (CBGs). The human-centered AI and microtransit service hold a strong promise to produce significant impact on the vulnerable community of low-wage workers on a short timescale.
Core Function(s):
Performing Research or Evaluation, Developing & Disseminating Information, Other Direct/Model Services, Demonstration Services
Area of Emphasis
Transportation-Related Activities, Quality of Life
Target Audience:
Family Members/Caregivers, Adults with Disabilities, General Public
Unserved or Under-served Populations:
Disadvantaged Circumstances, Geographic Areas, Rural/Remote, Urban
Primary Target Audience Geographic Descriptor:
Mulit-County, Regional
COVID-19 Related Data:
N/A
