Accessibility refers to the possibility of accessing places with ease, and is the interaction of mobility and proximity (Silva and Larson, 2018[1]). The notion of accessibility implies that people’s well-being does not ultimately depend on how much and how far they can travel, but on the possibility to meet their needs with ease, including by not having to travel long distances, or to travel at all. The creation of proximity is a key objective of accessibility-oriented policies. Accessibility can be measured in a number of ways. Contour-based accessibility measures are one of the most commonly used (and simpler) types of accessibility indicators. They can measure the number of opportunities (e.g. jobs, green spaces, transport stations) which can be reached within a given travel time, distance or cost; or the time/cost (average) required to gain access to a fixed number of opportunities from a given location (ITF, 2017[2]). In some contexts, “connectivity” is used to describe what in this report we define as accessibility, whereas the word “accessibility” is used to describe the ease of access of the population with mobility impairments specifically.

Car independent systems are those in which a bulk of daily activities can be done without a car or a motorcycle. People only move from less emitting and space intensive modes (e.g. active, then micro-mobility and public transport/ micro-transit) to the more emitting and space intensive ones (e.g. cars or motorcycles), as they make less frequent trips. Car and motorcycle use is reserved for those trips that can create more value than the costs they impose to society (i.e. reserved for specific purposes or circumstances); but they are not systematically the most convenient, nor the only, available option in most places. In these systems, distances between people and places are short (there is proximity), and public space is organised in such a way that active and shared modes (including public transport) are the fastest and safest modes for most people (including children) to get to places.

Car dependency is defined as the combination of “high levels of per capita automobile travel, automobile-oriented land-use patterns, and reduced transport alternatives” (Litman, 2002[3]). Throughout this report, the term is used to refer to dependency over cars and other private motorised vehicles such as motorcycles and sport utility vehicle (SUVs). The term also includes the notion of the overuse of private motorised vehicles.

Car overuse refers to the situation in which the harmful consequences of car use are greater than its benefits.

Community severance “describes the effects of transport infrastructure or motorised traffic as a physical or psychological barrier separating one built-up area from another built-up area or open space”. It “occurs when transport infrastructure or motorised traffic divides space and people” (Anciaes, Jones and Mindell, 2015[4]). Community severance is also described as the “barrier effect” resulting from transport systems that limit, rather than facilitate, people’s mobility (Anciaes, Jones and Mindell, 2015[4]).

Feedback loop. A feedback loop is a non-linear cause-effect relationship. A linear causal relationship is one in which a variable affects a second variable, and the cause-effect chain stops there. In non-linear cause-effect relationships, a variable affects a second variable, which in turn affects the first variable again. The variables feed into each other, leading to circular – rather than linear – cause-effect chains. Feedback loops (i.e. non-linear cause-effect chains) can be reinforcing or balancing. In reinforcing feedback loops, the effect of the first variable alters the second, which feeds back to affect the first variable again, in the same direction. For example, the more eggs, the more chickens, which leads to even more eggs and more chickens. In balancing feedback loops, variables affect each other in opposite directions. For example, the more foxes the less rabbits. The number of rabbits (the food stock of foxes) then affects the number of foxes: the less rabbits, the less foxes. And the less foxes, the more rabbits, as rabbits can reproduce more with less predators. Note that reinforcing feedback loops lead to acceleration, while balancing feedback loops lead to equilibrium. If the results of feedback loops are observed over time, reinforcing feedback loops lead to exponential curves (positive or negative) and balancing feedback loops to cyclical curves.

Incremental change refers to change to the properties of the parts or elements within a system not affecting the system’s organisation or functioning (Systems Innovation, 2020[5]).

Induced demand is a key dynamic underlying car dependency and high-emissions transport systems and is the phenomenon by which road expansion increases car traffic (WSP and RAND Europe, 2018[6]).

Leverage points are places to intervene in a system’s structure (Meadows, 1999[7]), and are based on the idea that “different types of solutions have different amounts of leverage to change the system” (Hinton, 2021[8]). Low leverage points refer to places where an action generates little change in the system’s behaviour and results. High leverage points are places where an action triggers important changes in the system’s behaviour and results. The closer to the root causes of a problem, the higher the leverage. For more, see Meadows (1999[7]).

Mobility is used in this report to designate physical movement, which can be measured in terms of vehicle-kilometres, passenger-kilometres (passenger), tonne-kilometres (freight) or number of trips.

Multimodal planning refers to planning that considers various modes (walking, cycling, automobile, public transit, etc.) and connections among modes (Litman, 2020[9]).

Road space management strategies are alternatives to the construction of new road infrastructure. These aim to ensure the enhanced and more efficient utilisation of existing roadways while reducing or eliminating the costs associated with building new roads (Sharma, 2017[10]).

Root cause analysis is a tool aimed at identifying the root causes of problems. The idea behind root cause analysis is that to solve a problem, the root causes need to be identified and solved, as opposed to addressing intermediate causes or “fixing” the problem’s symptoms.

Single-use development (and logic) refers to a type of urban development in which each area focuses on a specific land use, e.g. suburbs tend to be residential neighbourhoods, places of interest are often concentrated in city centres or in specific areas (e.g. shopping malls), and offices are clustered in working districts.

System. A system is a set of elements whose interconnections determine its structure and behaviour. Elements are things, people, factories, bikes. Interconnections are the way the elements are organised: rules, incentives, sanctions, information.

Systems thinking is a way of thinking that allows us to see systems, rather than just parts.

System dynamics is an approach for understanding the cause-effect relationships that lead systems to behave as they do, and thus produce the results that we observe (e.g. unsustainable levels of emissions, traffic volume increase, etc.) (Sterman, 2002[11]).

Transit-oriented development “is commonly defined as a type of mixed-use urban development within close proximity (walking distance) to mass transit facilities. Transit-oriented development principles are based on organising new development and redevelopment along mass transit corridors that serve as main transport axes, building high-density development along these corridors and fostering mixed land use and jobs.” (OECD (2019[12]), based on ITF (2017[2])).

Transformational change refers to change in the way a system is organised and functions (Systems Innovation, 2020[5]).

Urban sprawl is defined as the rapid and scattered expansion of development and is a key dynamic underlying car dependency and high-emissions transport systems.

Well-being. The concept of well-being incorporates aspects such as health, education, security, environmental quality, and political and social rights (OECD, 2019[12]). It goes beyond economic welfare, (i.e. beyond gross domestic product) and comprises both current well-being outcomes and the resources that help sustain these outcomes over time (OECD, 2019[12]). Well-being outcomes are captured in frameworks such as the Sustainable Development Goals and the OECD Well-being Framework (OECD, 2011[13]).


[4] Anciaes, P., P. Jones and J. Mindell (2015), “Community severance: Where is it found and at what cost?”, Transport Reviews, Vol. 36/3, pp. 293-317,

[8] Hinton, J. (2021), Relationship-to-Profit: A Theory of Business, Markets, and Profit for Social Ecological Economics, Thesis for Degree of Doctor of Philosophy in Sustainability Science and Economics, Stockholm University, (accessed on 5 July 2021).

[14] ITF (2021), ITF Transport Outlook 2021, OECD Publishing, Paris,

[2] ITF (2017), Income Inequality, Social Inclusion and Mobility, ITF Roundtable Reports, No. 164, OECD Publishing, Paris,

[9] Litman, T. (2020), Introduction to Multi-modal Transportation Planning: Principles and Practices, Victoria Transport Policy Institute, Victoria, British Columbia,

[3] Litman, T. (2002), The Costs of Automobile Dependency and the Benefits of Balanced Transportation, Victoria Transport Policy Institute, Victoria, British Columbia,

[7] Meadows, D. (1999), Leverage Points: Places to Intervene in a System, The Sustainability Institute, Hartland, VT, (accessed on 16 June 2021).

[12] OECD (2019), Accelerating Climate Action: Refocusing Policies through a Well-being Lens, OECD Publishing, Paris,

[13] OECD (2011), How’s Life?: Measuring Well-being, OECD Publishing, Paris,

[10] Sharma, S. (2017), “Optimal corridor selection for a road space management strategy: Methodology and tool”, Journal of Advanced Transportation, Vol. 2017, pp. 1-12,

[1] Silva, C. and A. Larson (2018), “Challenges for accessibility planning and research in the context of sustainable mobility”, International Transport Forum Discussion Papers, No. 2018/07, OECD Publishing, Paris,

[11] Sterman, J. (2002), “Systems dynamics modeling: Tools for learning in a complex world”, IEEE Engineering Management Review, Vol. 30/1, pp. 42-52,

[5] Systems Innovation (2020), Introduction to Systems Innovation, Systems Innovation, (accessed on 29 March 2021).

[6] WSP and RAND Europe (2018), Latest Evidence on Induced Travel Demand: An Evidence Review, UK Department for Transport, London,

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