Association for Public Policy Analysis & Management

As US is constantly building intra-city rail transit system in over 50 city/metropolitans, around 7500 miles and over 3500 stations of intra-city rail systems, one of the questions for either policy makers and the public is what and how do we measure the success of rail transit system. As previous research has done cost-effectiveness and self-liquidating rate, they might not be the only way to measure how what make a rail system successful.

Vehicle Miles Traveled (VMT) might be the alternative way for measuring the contribution of intra-city rail system to ease congestion and decrease total social cost. Using two data processing methods (aggregation and census area data), Geographic Information System (GIS) technology and fixed effect with (1) VMT, (2) ridership (3) demographic change from 2000 to 2015 at system-level. The author tries to find what might be the alternative ways to measure the factors that contribute to the success of rail transit system. The author categorizes these intra-city rail system into five sub-systems: Hybrid, Commuter Rail, Light Rail, Street Car and People Movers (Monorail) and analyzes the five category under different internal and external factors. Geographically the stations are categorized into near Central Business District (CBD), urban and suburban areas with the help of GIS and Google Street view.

This research uses different distance (.25, .5 and 1 mile) of aggregation area and different levels of data: census tract, parcel group and parcel (if available) around rail station to compare the different effect with rail transit and help to define the best affected area in different geographic areas.

The preliminary result shows that length and station numbers of intra-city rail system are negatively associate with VMT; approximation to suburban commuter rail system is positively associate with housing price, major events, total track length and numbers of stations and total service of time, but negatively associate with service interval within trains, existence of park and ride facility and ticket price. However, in some urban areas housing price does seem to have positive effect along rail transit station but the relationship in between is spatial dependent and unique around different areas. Also, in suburban areas with park and ride, the affected areas would be larger than urban or CBD areas.