Authors: Si Chen*, Informatics, University of Illinois at Champaign and Urbana, Shaowen Wang, Department of Geography and Geographic Information Science, UIUC
Topics: Transportation Geography, Urban and Regional Planning, Urban Geography
Keywords: Last mile problem, Public Transit, User Interface, Spatial data analysis
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Congressional B, Omni, West
Presentation File: No File Uploaded
The ‘last mile problem’ refers to the final leg of a network delivery system, typically the final delivery to end-users (customers). In urban transit parlance it is the final leg of a commute; i.e. the journey home from a public transit stop. Some research suggests that the last mile problem (LMP) can play an important role in how public transit systems are perceived and used (Zellner et.al., 2016). Prior studies have typically focused on walking/biking/feeder bus strategies for improving the last mile experience (Tight et.al., 2016). Missing however, has been a standardized way for identifying the areas that warrant last mile strategic or design intervention on a large scale. The ability to do this would enable designers to focus specific strategic intervention to specific places.
This paper describes a large-scale approach for identifying residential areas that have the characteristics of LMPs. We use the City of Chicago to test and evaluate the performance of an LMP identification model. Transit, transportation, land use and Yelp data are used to identify transit routes and potential travel routes to popular destinations for each residential parcel. An easy to navigate, user interface is also developed to help visualize the assessment scores and collect public feedback. The model has been made publically available. Feedback has suggested that the model does reasonably well in assessing the LMPs in most areas of the city. We suggest the process is important for planning and urban design support systems and for citizens to assess suitable living areas.