Accessibility Futures

Abstract

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. For roadway modeling, zone-to-zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person-weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.

Primal and Dual Access

“…The time-weighted accessibility score for primal accessibility, proposed by Anderson et al (2013), combines different time thresholds into a complete measure and scores the accessibility for ranking each block. It applies a decay factor showing that accessibility decreases with a longer time from the origin (Hansen, 1959), which can be written as,…”

“…The exponential travel time decay function is also tested, which is commonly used in previous studies for time-weighted primal accessibility calculations (Anderson et al, 2013, Cui and Levinson, 2018b, Owen and Murphy, 2017b, to compare the weighted primal and dual accessibility scores, replacing the power function. A similar clustered pattern is displayed, which could be explained by a power format function as well (R 2 =0.832).…”

Multi‐temporal transport network models for accessibility studies

“…Accessibility, as a concept, was seldom employed as a performance measure to evaluate policies (Handy & Niemeier, 1997), and the academic community still investigates the incorporation of accessibility measures into transportation plans (Boisjoly & El-Geneidy, 2017). According to Anderson, Levinson, and Parthasarathi (2013), accessibility can be used as a measure of the efficiency of a city, since it is a function of both transport network and land use. To Proffitt, Bartholomew, Ewing, and Miller (2019), when it comes to improving accessibility, increasing travel speed is not the only solution.…”

Future accessibility impacts of transport policy scenarios: equity and sensitivity to travel time thresholds for Bus Rapid Transit expansion in Rio de Janeiro

“…Previous studies have conducted accessibility analysis to examine how people's access to jobs by car or public transport can be affected by future transport and land-use scenarios (Anderson et al, 2013;Geurs & va Eck, 2003;Tilahun & Fan, 2014). Some studies have also focused specifically on different scenarios of alternative public transport projects, looking at their accessibility impacts across racial/ethnic and income groups (El-Geneidy et al, 2011;Farber & Grandez, 2017;Manaugh & El-Geneidy, 2012;Niehaus et al, 2016).…”