Development of a GIS-Based Decision Support System for Prioritizing Transit Facility Investments for Disabled Riders
or Dr. David Shen, (305) 348-1869, email@example.com
In a major report released on June 13, 2005 recently, the National Council on Disability concluded that disabled people who need to use public transit systems are not being well served despite billions of dollars spent to improve transportation for the disabled. The council, a federal agency that advises the president and Congress, found persistent problems for disabled people who use public transportation despite years of federal efforts to make buses and trains more accessible. This particular project scope was prepared to meet a major need identified by this report, i.e., how to improve accessibility to transit systems for our disabled people who, according to Census 2000, made up about 20% of the total population.
One way for transit agencies to improve accessibility to transit systems for the disabled is clearly to add ADA-compliant features such as curb-cuts, sidewalks, loading pads, etc., as well as auditory messages such as talking signs and voice announcement. More often than not, agencies have only a limited budget to install such facilities at select transit stop locations. As such, these facilities should be installed at locations where the maximum benefits to the disabled patrons may be realized. In practice, locations for improvements are usually selected based on existing information, staff experience, requests from elected officials, etc. However, it is very difficult to identify locations that will benefit most from improvements under the constraints of available funds, transit patronage, and facilities already in existence.
A decision-making tool is needed to more accurately identify the type of improvements needed and the right locations for the improvements. This can be accomplished with an optimization model with the aid of a Geographic Information System (GIS). The model will make use of information in existing transit databases (bus stop inventory, transit ridership, wheelchair ridership, customer complaints, accidents, etc.), facility deployment costs, service area demographic information, and land use parcel data for work place locations. As can be seen, optimum investment decisions depend on many factors that cannot be obtained using ordinary approaches. Additionally, the number of variables involved makes it difficult to process the information easily. The proposed model will promote better management of the agency’s financial resources as well as improve service to disabled customers.