Accessibility (transport)

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Access to jobs by public transit in Toronto Toronto transit access to jobs 2550x1650.png
Access to jobs by public transit in Toronto

In transport planning, accessibility refers to a measure of the ease of reaching (and interacting with) destinations [1] or activities distributed in space, [2] [3] e.g. around a city or country. [4] [5] Accessibility is generally associated with a place (or places) of origin. A place with "high accessibility" is one from which many destinations can be reached or destinations can be reached with relative ease. "Low accessibility" implies that relatively few destinations can be reached for a given amount of time/effort/cost or that reaching destinations is more difficult or costly from that place.

Contents

The concept can also be defined in the other direction, and we can speak of a place having accessibility from some set of surrounding places. For example, one could measure the accessibility of a store to customers as well as the accessibility of a potential customer to some set of stores.

In time geography, accessibility has also been defined as "person based" rather than "place based", where one would consider a person's access to some type of amenity through the course of their day as they move through space. [6] For example, a person might live in a food desert but have easy access to a grocery store from their place of work.

Accessibility is often calculated separately for different modes of transport. [7]

Mathematical definition

In general, accessibility is defined as:

where:

Cost metrics

Travel cost metrics ( in the equation above) can take a variety of forms such as:

Cost metrics may also be defined using any combination of these or other metrics. For a non-motorized mode of transport, such as walking or cycling, the generalized travel cost may include additional factors such as safety or gradient. The essential idea is to define a function that describes the ease of travelling from any origin to any destination .

A large compendium of such cost metrics used in practice was developed in 2012, under the framework of Cost Action TU1002, and is available online. [12]

Impedance functions

The function on the travel cost determines how accessible a destination is based on the travel cost associated with reaching that destination. Two common impedance functions are "cumulative opportunities" and a negative exponential function. Cumulative opportunities [13] [8] is a binary function [14] yielding 1 if an opportunity can be reached within some threshold and 0 otherwise. It is defined as:

where is the threshold parameter.

A negative exponential [13] impedance function can be defined as:

where is a parameter defining how quickly the function decays with distance.

Relation to land use

Accessibility has long been associated with land-use; [15] [16] as accessibility increases in a given place, the utility of developing the land increases. [17] [2] This association is often used in integrated transport and landuse forecasting models. At the same time, the accessibility of a place can not only be changed through a modification of the transport infrastructure, but also as a consequence of a changed spatial structure / distribution of destinations.

In practice

Transport agencies

Transport for London utilize a calculated approach known as Public Transport Accessibility Level (PTAL) that uses the distance from any point to the nearest public transport stops, and service frequency at those stops, to assess the accessibility of a site to public transport services. Destination-based accessibility measures are an alternate approach that can be more sophisticated to calculate. These measures consider not just access to public transport services (or any other form of travel), but the resulting access to opportunities that arises from it. For example, using origin-based accessibility (PTAL) we can understand how many buses one may be able to be access. Using destination-based measures we can calculate how many schools, hospitals, jobs, restaurants (etc..) can be accessed. [18]

In urban planning

Accessibility-based planning is a spatial planning methodology that centralises goals of people and businesses and defines accessibility policy as enhancing people and business opportunities. [19]

Traditionally, urban transportation planning has mainly focused on the efficiency of the transport system itself and is often responding to plans made by spatial planners. Such an approach neglects the influence of interventions in the transport system on broader and often conflicting economic, social and environmental goals. Accessibility based planning defines accessibility as the amount of services and jobs people can access within a certain travel time, considering one or more modes of transport such as walking, cycling, driving or public transport. Using this definition accessibility does not only relate to the qualities of the transport system (e.g. travel speed, time or costs), but also to the qualities of the land use system (e.g. densities and mixes of opportunities). It thus provides planners with the possibility to understand interdependencies between transport and land use development. Accessibility planning opens the floor to a more normative approach to transportation planning involving different actors. [20] For politicians, citizens and firms it might be easier to discuss the quality of access to education, services and markets than it is to discuss the inefficiencies of the transport system itself. Accessibility is also defined as "the potential for interaction".

Despite the high potential of accessibility in integrating the different components of urban planning, such as land use and transportation and the large number of accessibility instruments available in the research literature, the latter are not widely used to support urban planning practices yet. [21] By keeping the accessibility language out of the practice level, older paradigms resist the more informed and people-centred approaches. The existence of accessibility instruments is fairly acknowledged, but practitioners do not appear to have found them useful or usable enough for addressing the tasks of sustainable urban management. [22]

See also

Related Research Articles

<span class="mw-page-title-main">Travelling salesman problem</span> NP-hard problem in combinatorial optimization

The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?" It is an NP-hard problem in combinatorial optimization, important in theoretical computer science and operations research.

<span class="mw-page-title-main">Assignment problem</span> Combinatorial optimization problem

The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows:

<span class="mw-page-title-main">Trip distribution</span>

Trip distribution is the second component in the traditional four-step transportation forecasting model. This step matches tripmakers’ origins and destinations to develop a “trip table”, a matrix that displays the number of trips going from each origin to each destination. Historically, this component has been the least developed component of the transportation planning model.

<span class="mw-page-title-main">Transit-oriented development</span> Urban planning prioritising transit

In urban planning, transit-oriented development (TOD) is a type of urban development that maximizes the amount of residential, business and leisure space within walking distance of public transport. It promotes a symbiotic relationship between dense, compact urban form and public transport use. In doing so, TOD aims to increase public transport ridership by reducing the use of private cars and by promoting sustainable urban growth.

<span class="mw-page-title-main">Paratransit</span> Transportation service for people with disabilities

Paratransit is the term used in North America, also known by other names such as community transport (UK), for transportation services that supplement fixed-route mass transit by providing individualized rides without fixed routes or timetables. Paratransit services may vary considerably on the degree of flexibility they provide their customers. At their simplest they may consist of a taxi or small bus that will run along a more or less defined route and then stop to pick up or discharge passengers on request. At the other end of the spectrum—fully demand responsive transport—the most flexible paratransit systems offer on-demand call-up door-to-door service from any origin to any destination in a service area. In addition to public transit agencies, paratransit services may be operated by community groups or not-for-profit organizations, and for-profit private companies or operators.

Route assignment, route choice, or traffic assignment concerns the selection of routes between origins and destinations in transportation networks. It is the fourth step in the conventional transportation forecasting model, following trip generation, trip distribution, and mode choice. The zonal interchange analysis of trip distribution provides origin-destination trip tables. Mode choice analysis tells which travelers will use which mode. To determine facility needs and costs and benefits, we need to know the number of travelers on each route and link of the network. We need to undertake traffic assignment. Suppose there is a network of highways and transit systems and a proposed addition. We first want to know the present pattern of traffic delay and then what would happen if the addition were made.

<span class="mw-page-title-main">Public transport accessibility level</span>

The public transport accessibility level (PTAL) is a method sometimes used in United Kingdom transport planning to assess the access level of geographical areas to public transport.

<span class="mw-page-title-main">Transportation demand management</span> Policies to reduce transportation demands

Transportation demand management or travel demand management (TDM) is the application of strategies and policies to increase the efficiency of transportation systems, that reduce travel demand, or to redistribute this demand in space or in time.

<span class="mw-page-title-main">Generalised cost</span>

In transport economics, the generalised cost is the sum of the monetary and non-monetary costs of a journey. It is sometimes used as a basis for judgements of transit accessibility and equitable distribution of public transit resources.

In mathematics, the Wasserstein distance or Kantorovich–Rubinstein metric is a distance function defined between probability distributions on a given metric space . It is named after Leonid Vaseršteĭn.

<span class="mw-page-title-main">Vehicle routing problem</span> Optimization problem

The vehicle routing problem (VRP) is a combinatorial optimization and integer programming problem which asks "What is the optimal set of routes for a fleet of vehicles to traverse in order to deliver to a given set of customers?" It generalises the travelling salesman problem (TSP). It first appeared in a paper by George Dantzig and John Ramser in 1959, in which the first algorithmic approach was written and was applied to petrol deliveries. Often, the context is that of delivering goods located at a central depot to customers who have placed orders for such goods. The objective of the VRP is to minimize the total route cost. In 1964, Clarke and Wright improved on Dantzig and Ramser's approach using an effective greedy algorithm called the savings algorithm.

<span class="mw-page-title-main">Car dependency</span> Concept that city layouts favor automobiles over other modes of transportation

Car dependency is the concept that some city layouts cause cars to be favoured over alternate forms of transportation, such as bicycles, public transit, and walking.

<span class="mw-page-title-main">Walkability</span> How accessible a space is to walking

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Arc routing problems (ARP) are a category of general routing problems (GRP), which also includes node routing problems (NRP). The objective in ARPs and NRPs is to traverse the edges and nodes of a graph, respectively. The objective of arc routing problems involves minimizing the total distance and time, which often involves minimizing deadheading time, the time it takes to reach a destination. Arc routing problems can be applied to garbage collection, school bus route planning, package and newspaper delivery, deicing and snow removal with winter service vehicles that sprinkle salt on the road, mail delivery, network maintenance, street sweeping, police and security guard patrolling, and snow ploughing. Arc routings problems are NP hard, as opposed to route inspection problems that can be solved in polynomial-time.

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<span class="mw-page-title-main">GTFS</span> Data standard for public transport information

GTFS, which stands for General Transit Feed Specification or (originally) Google Transit Feed Specification, defines a common format for public transportation schedules and associated geographic information. GTFS contains only static or scheduled information about public transport services, and is sometimes known as GTFS Static or GTFS Schedule to distinguish it from the GTFS Realtime extension, which defines how information on the realtime status of services can be shared.

<span class="mw-page-title-main">Isochrone map</span> Map that depicts the area accessible from a point within a time threshold

An isochrone map in geography and urban planning is a map that depicts the area accessible from a point within a certain time threshold. An isochrone is defined as "a line drawn on a map connecting points at which something occurs or arrives at the same time". In hydrology and transportation planning isochrone maps are commonly used to depict areas of equal travel time. The term is also used in cardiology as a tool to visually detect abnormalities using body surface distribution.

<span class="mw-page-title-main">Efficiency (network science)</span>

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Transport divide refers to unequal access to transportation. It can result in the social exclusion of disadvantaged groups.

References

  1. 1 2 Farber, Steven; Fu, Liwei (2017-03-01). "Dynamic public transit accessibility using travel time cubes: Comparing the effects of infrastructure (dis)investments over time". Computers, Environment and Urban Systems. 62: 30–40. doi:10.1016/j.compenvurbsys.2016.10.005. ISSN   0198-9715.
  2. 1 2 3 El-Geneidy, Ahmed; Levinson, David (2006-05-01). "Access to Destinations: Development of Accessibility Measures".{{cite journal}}: Cite journal requires |journal= (help)
  3. Song, Ying; Miller, Harvey; Stempihar, Jeff; Zhou, Xuesong (2017-10-01). "Green accessibility: Estimating the environmental costs of network-time prisms for sustainable transportation planning". Journal of Transport Geography. 64: 109–119. doi: 10.1016/j.jtrangeo.2017.08.008 . ISSN   0966-6923.
  4. Andrew, Owen; Brendan, Murphy (2018). "Access Across America: Transit 2017".{{cite journal}}: Cite journal requires |journal= (help)
  5. Owen, Andrew; Levinson, David M. (2016-10-08), "Developing a Comprehensive U.S. Transit Accessibility Database", Springer Geography, Springer International Publishing, pp. 279–290, doi:10.1007/978-3-319-40902-3_16, hdl: 11299/180074 , ISBN   9783319409009
  6. Miller, Harvey J. (2005-12-06), "Place-Based Versus People-Based Accessibility", Access to Destinations, Emerald Group Publishing Limited, pp. 63–89, doi:10.1108/9780080460550-004, ISBN   9780080446783
  7. Iacono, Michael; Krizek, Kevin; El-Gemeidy, Ahmed (2010-01-01). "Measuring non-motorized accessibility: issues, alternatives, and execution". Journal of Transport Geography. 18 (1): 133–140. CiteSeerX   10.1.1.558.6960 . doi:10.1016/j.jtrangeo.2009.02.002. ISSN   0966-6923.
  8. 1 2 Andrew, Owen; Brendan, Murphy (2018). "Access Across America: Transit 2017 Methodology".{{cite journal}}: Cite journal requires |journal= (help)
  9. El-Geneidy, Ahmed; Levinson, David; Diab, Ehab; Boisjoly, Genevieve; Verbich, David; Loong, Charis (2016-09-01). "The cost of equity: Assessing transit accessibility and social disparity using total travel cost". Transportation Research Part A: Policy and Practice. 91: 302–316. doi:10.1016/j.tra.2016.07.003. hdl: 11299/179814 . ISSN   0965-8564.
  10. Nassir, Neema; Hickman, Mark; Malekzadeh, Ali; Irannezhad, Elnaz (2016-06-01). "A utility-based travel impedance measure for public transit network accessibility". Transportation Research Part A: Policy and Practice. 88: 26–39. doi:10.1016/j.tra.2016.03.007. ISSN   0965-8564.
  11. Levinson, David; Cui, Mengying (2018-10-05). "Full cost accessibility". Journal of Transport and Land Use. 11 (1). doi: 10.5198/jtlu.2018.1042 . hdl: 11299/200629 . ISSN   1938-7849.
  12. "Accessibility Instruments". accessibilityplanning.eu.
  13. 1 2 Allen, Jeff; Farber, Steven (2018). "Generating measures of access to employment for Canada's eight largest urban regions". doi:10.31235/osf.io/pvrd9. S2CID   242032557 . Retrieved 13 October 2018.{{cite journal}}: Cite journal requires |journal= (help)
  14. Fayyaz S., S. Kiavash; Liu, Xiaoyue Cathy; Zhang, Guohui (2017-10-05). "An efficient General Transit Feed Specification (GTFS) enabled algorithm for dynamic transit accessibility analysis". PLOS ONE. 12 (10): e0185333. Bibcode:2017PLoSO..1285333F. doi: 10.1371/journal.pone.0185333 . ISSN   1932-6203. PMC   5628824 . PMID   28981544.
  15. Hansen, Walter G. (1959). "How Accessibility Shapes Land Use". Journal of the American Institute of Planners. 25 (2): 73–76. doi:10.1080/01944365908978307. ISSN   0002-8991.
  16. Geurs, Karst T.; Van Wee, Bert (2004-06-01). "Accessibility evaluation of land-use and transport strategies: review and research directions". Journal of Transport Geography. 12 (2): 127–140. doi:10.1016/j.jtrangeo.2003.10.005. ISSN   0966-6923.
  17. Iacono, Michael; Levinson, David (2017-02-01). "Accessibility dynamics and location premia: Do land values follow accessibility changes?". Urban Studies. 54 (2): 364–381. CiteSeerX   10.1.1.226.4890 . doi:10.1177/0042098015595012. ISSN   0042-0980. S2CID   9437962.
  18. Lock, Oliver; Pinnegar, Simon; Z Leao, Simone; Pettit, Christopher (18 February 2020). "'Chapter 28: The making of a mega-region: evaluating and proposing long-term transport planning strategies with open-source data and transport accessibility tools.". In Geertman, S; Stillwell, J (eds.). Handbook of Planning Support Science. Edward Elgar Publishing. pp. 442–457. ISBN   9781788971072.
  19. Proffitt, David G.; Bartholomew, Keith; Ewing, Reid; Miller, Harvey J. (2017-06-13). "Accessibility planning in American metropolitan areas: Are we there yet?". Urban Studies. 56: 167–192. doi: 10.1177/0042098017710122 .
  20. "Planning for Sustainable Travel - Key Themes - Accessibility of Key Facilities". plan4sustainabletravel.org. Archived from the original on 2018-02-08. Retrieved 2018-07-02.
  21. Hull, Angela; Silva, Cecília; Bertolini, Luca (June 2012). Accessibility Instruments for Planning Practice (PDF). COST Office. ISBN   978-989-20-3210-8.
  22. "COST Action TU1002 | EDGE". tut.fi. Retrieved 2018-07-02.