By publishing this data story, we hope the development community will help us innovate solutions to identify transit options that meet the transportation needs of older residents of underserved communities who do not drive cars in order to connect them to critical destinations. Successful solutions will help route users to appropriate transit options based on their mobility ability, using static and dynamic data sources.
To solve the challenge, successful teams will need to identify concentrations of older adults in areas of the community that are characterized as underserved based on density and vulnerability data. From that population, the team should be prepared to capture personal mobility information from individual end users to help tailor transit recommendations. The team will need to identify key destinations for these travelers (workplaces, shopping, food, healthcare, religious centers, social spaces, recreation, leisure facilities, etc) and include dynamic age-friendliness data about destinations that help inform choice and scheduling (e.g. accessibility information, crowd levels, appointment times, etc.).