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Accessibility

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===Using the street network===
Some tools use the street network to estimate travel time between origin or destination and the transit station. This calculation can much more accurately determine the first mile and last mile travel time and therefore yield a more accurate total travel time. It avoids the pitfalls of cutting off people or destinations just outside of a buffer and effectively recognizes relative distances from stations. However, it requires an individual calculation from each origin to each destination, rather than reserving calculations to between stations, hence a much more computationally intensive process. It also requires an accurate street network that includes pedestrian paths.
 
==Destinations==
Accessibility analysis measures how long it takes to arrive at certain types of destinations. The most common destination that is measured is jobs. Access to jobs is crucial for employers and employees to maintain a robust economy, and peak commute hours tend to be the most congested times of the week, so increasing accessibility to jobs via transit is particularly important. Data sources for jobs are also easy to acquire through the publicly available LODES and LEHD data.
Other destinations are also often sought out. These can include restaurants, grocery stores, schools, health facilities, parks, etc. Accessibility to these types of amenities has a serious impact on quality of life, and is therefore important in evaluating transit effects on a community. Also, since only 20% of trips are for a home-to-work commute<ref>Commuting in America 2013:​​ The National Report on​ Commuting Patterns and Trends​. American Association of State Highway and Transportation Officials. http://traveltrends.transportation.org/Pages/default.aspx</ref>​, factoring in other trip destinations has a big impact on how much people will use a transit system. There are no government generated sources for these databases. Some tools use open source options, such as [[OpenstreetMap]], while other acquire proprietary databases. A challenge when working with other destinations is how to group them or weight them. Analyzing accessibility to grocery stores might be relatively easy (although even in this example, classifying grocery stores might be difficult). However, analyzing accessibility to amenities broadly raises questions of which amenities count and which amenities are most important.
 
==Population Analysis==
In order to address equity issues and to comply with [[Title VI]], accessibility measurements seek to display how accessibility will change for different segments of the population. This can include relative effects on low-income households, different racial minorities, people with disabilities, households without cars or with fewer cars than workers, among others. Demographic data can be fairly easily acquired in the US through the Census and/or ACS. A simple visual analysis layers a demographic map and an accessibility map. A more complicated analysis would actually calculate the changes in accessibility to census blocks or block groups of varying demographic characteristics and measure relative effects.
 
==Example Tools==
Some tools that measure accessibility are discussed below
 
*[[Sugar Access]] is a tool offered by [[Citilabs]]. It measures access using decay functions, creating an access score. Sugar incorporates first and last mile travel on a the pedestrian street network in measuring its total travel time. It offers accessibility measures to many types of destinations using destination data from navigation company HERE and allows for custom weighting of destination data. Sugar allows for easy layering of demographic data, but does not include demographic based calculations.
*[[Transport Analyst]] offered by [[Conveyal]] is an open source tool. It offers accessibility information for various cut-off points and creates spectrograms that show the change in accessibility as travel time increases, but does not create a related score. Analyst offers accessibility measures for a number of different destination types, acquired from [[OpenStreetMap]], and allows for demographic overlays.
*[[TBEST]] is a tool mostly used for estimating transit boardings that was developed by [[FDOT]]. TBEST includes an accessibility analysis function, but it is limited in destination options, and only calculates stop to stop travel times.
==References==
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