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Travel behavior is the study of what people do over geography, and how people use transport.
| | This article needs additional citations for verification .(July 2015) |
Travel behavior is the study of what people do over geography, and how people use transport.
The questions studied in travel behavior are broad, and are probed through activity and time-use research studies, and surveys of travelers designed to reveal attitudes, behaviors and the gaps between them in relation to the sociological and environmental impacts of travel.
Other behavioral aspects of traveling, such as letting people get off before entering a vehicle, queueing behavior, etc. (See for example Passenger behavior in Shanghai)
These questions can be answered descriptively using a travel diary, often part of a travel survey or travel behavior inventory. Large metropolitan areas typically only do such surveys once every decade, though some cities are conducting panel surveys, which track the same people year after year. Such repeated surveys are useful because they yield different answers than surveys at a single point in time. [6]
That data is generally used to estimate transportation planning models, so that transport analysts can make predictions about people who haven't been surveyed. This is important in forecasting traffic, which depends on future changes to road networks, land use patterns, and policies.
Some years ago it was recognized that behavioral research was limited by data, and a special data set was developed to aid research: The Baltimore Disaggregate Data Set which is the result an in depth survey, ca. 1977. Its title indicates today’s emphasis on disaggregated rather than aggregated data. This particular data set is believed lost. A small program to preserve and make available on the web these travel behavior surveys, the Metropolitan Travel Survey Archive, is now under way at the University of Minnesota. There is also the National Personal Transportation Survey (later National Household Travel Survey), conducted every five years or so, but with much less spatial detail.
Today, the best source of information about travel behavior is a Household Travel Survey. In this type of data collection the sampling unit is the household and all its members because people interact the most with other people with whom they share a residence. Data on household characteristics, person characteristics, and a daily diary constitute the Household Travel Survey. The diary can be a trip diary (in which a person records every trip made in a day), or a place-based diary (in which a person record every location visited, the trips made to reach these location and the activities completed), or a time use diary (in which a person everything he/she does in day). Examples include the National Household Travel Survey, the California Household Travel Survey, The Puget Sound Travel Survey. Data from these surveys can be found at https://www.nrel.gov/transportation/secure-transportation-data/.
Analysis of travel behavior from the home can answer the question: How does the family participate in modern society. Consider two non-observable extremes. At one extreme we have the non-specialized household. It does everything for itself, and no travel is required. Ultimate specialization is the other extreme; travel is required for all things. Observed households are somewhere in between. The “in between” position of households might be thought of as the consequence of two matters.
Moore (1964) has observed that increasing specialization in all things is the chief feature of social change. Considering social changes, one might observe that 100 years ago things were less specialized compared to today. So we would expect lots of change in household travel over the time period. Data are not very good, but the travel time aspect of what’s available seems contrary to the expectation, travel hasn’t changed much. For instance, the time spent on the journey to work may have been stable for centuries (the travel budget hypothesis). Here are some travel time comparisons from John Robinson (1986).
| Men | Women | |||
|---|---|---|---|---|
| Activity | 1975 | 1985 | 1975 | 1985 |
| Work Travel | 25 | 31 | 9 | 17 |
| Family Travel | 33 | 31 | 33 | 33 |
| Leisure Travel | 27 | 33 | 21 | 23 |
| Total | 85 | 94 | 63 | 73 |
Most travel behavior analysis concerns demand issues and do not touch very much on supply issues. Yet when we observe travel from a home, we are certainly observing some sort of market clearing process – demand and supply are matched.
Analytic work on travel behavior can be dated from Liepmann (1945). Liepmann obtained and analyzed 1930s data on worker travel in England. Many of the insights current today were found by Liepmann: time spent, ride sharing, etc. Most academics date modern work from advances in mode choice analysis made in the 1970s. This created much excitement, and after some years an International Association for Travel Behaviour Research emerged. There are about 150 members of the Association; it holds a conference every three years. The proceedings of those conferences yield a nice record of advances in the field. The proceedings also provide a record of topics of lasting interest and of changing priorities. Mode choice received priority early on, but in the main today’s work is not so much on theory as it is on practice. Hagerstrand (1970) developed a time and space path analysis, often called the time-space prism.
On November 18–20, 2004, Transportation Research Board (TRB) held its third conference in Chicago, Illinois, with an interest in advancing the understanding of women’s issues in transportation. One of the presented studies, conducted by Nobis et al., [7] revealed that the gender difference in travel patterns is linked to employment status, household structure, child care, and maintenance tasks. They found that travel patterns of men and women are much similar when considering single families; the differences are greater once males and females are compared in multi-person households without children; and are the highest once they live in households with children. Over the past two decades numerous studies have been conducted on travel behavior showing gender as an influential factor in travel decision making. [8]
A travel survey is a survey of individual travel behavior. Most surveys collect information about an individual, their household, and a diary of their journeys on a given day.
In economics, induced demand – related to latent demand and generated demand – is the phenomenon whereby an increase in supply results in a decline in price and an increase in consumption. In other words, as a good or service becomes more readily available and mass produced, its price goes down and consumers are more likely to buy it, meaning that the quantity demanded subsequently increases. This is consistent with the economic model of supply and demand.
Sustainable transport refers to ways of transportation that are sustainable in terms of their social and environmental impacts. Components for evaluating sustainability include the particular vehicles used for road, water or air transport; the source of energy; and the infrastructure used to accommodate the transport. Transport operations and logistics as well as transit-oriented development are also involved in evaluation. Transportation sustainability is largely being measured by transportation system effectiveness and efficiency as well as the environmental and climate impacts of the system. Transport systems have significant impacts on the environment, accounting for between 20% and 25% of world energy consumption and carbon dioxide emissions. The majority of the emissions, almost 97%, came from direct burning of fossil fuels. In 2019, about 95% of the fuel came from fossil sources. The main source of greenhouse gas emissions in the European Union is transportation. In 2019 it contributes to about 31% of global emissions and 24% of emissions in the EU. In addition, up to the COVID-19 pandemic, emissions have only increased in this one sector. Greenhouse gas emissions from transport are increasing at a faster rate than any other energy using sector. Road transport is also a major contributor to local air pollution and smog.
Trip generation is the first step in the conventional four-step transportation forecasting process used for forecasting travel demands. It predicts the number of trips originating in or destined for a particular traffic analysis zone (TAZ). Trip generation analysis focuses on residences and residential trip generation is thought of as a function of the social and economic attributes of households. At the level of the traffic analysis zone, residential land uses "produce" or generate trips. Traffic analysis zones are also destinations of trips, trip attractors. The analysis of attractors focuses on non-residential land uses.
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.
Mode choice analysis is the third step in the conventional four-step transportation forecasting model of transportation planning, following trip distribution and preceding route assignment. From origin-destination table inputs provided by trip distribution, mode choice analysis allows the modeler to determine probabilities that travelers will use a certain mode of transport. These probabilities are called the modal share, and can be used to produce an estimate of the amount of trips taken using each feasible mode.
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.
Geographic mobility is the measure of how populations and goods move over time. Geographic mobility, population mobility, or more simply mobility is also a statistic that measures migration within a population. Commonly used in demography and human geography, it may also be used to describe the movement of animals between populations. These moves can be as large scale as international migrations or as small as regional commuting arrangements. Geographic mobility has a large impact on many sociological factors in a community and is a current topic of academic research. It varies between different regions depending on both formal policies and established social norms, and has different effects and responses in different societies. Population mobility has implications ranging from administrative changes in government and impacts on local economic growth to housing markets and demand for regional services.
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.
Sustainable tourism is a concept that covers the complete tourism experience, including concern for economic, social, and environmental issues as well as attention to improving tourists' experiences and addressing the needs of host communities. Sustainable tourism should embrace concerns for environmental protection, social equity, and the quality of life, cultural diversity, and a dynamic, viable economy delivering jobs and prosperity for all. It has its roots in sustainable development and there can be some confusion as to what "sustainable tourism" means. There is now broad consensus that tourism should be sustainable. In fact, all forms of tourism have the potential to be sustainable if planned, developed and managed properly. Tourist development organizations are promoting sustainable tourism practices in order to mitigate negative effects caused by the growing impact of tourism, for example its environmental impacts.
Transportation forecasting is the attempt of estimating the number of vehicles or people that will use a specific transportation facility in the future. For instance, a forecast may estimate the number of vehicles on a planned road or bridge, the ridership on a railway line, the number of passengers visiting an airport, or the number of ships calling on a seaport. Traffic forecasting begins with the collection of data on current traffic. This traffic data is combined with other known data, such as population, employment, trip rates, travel costs, etc., to develop a traffic demand model for the current situation. Feeding it with predicted data for population, employment, etc. results in estimates of future traffic, typically estimated for each segment of the transportation infrastructure in question, e.g., for each roadway segment or railway station. The current technologies facilitate the access to dynamic data, big data, etc., providing the opportunity to develop new algorithms to improve greatly the predictability and accuracy of the current estimations.
In urban planning, walkability is the accessibility of amenities by foot. It is based on the idea that urban spaces should be more than just transport corridors designed for maximum vehicle throughput. Instead, it should be relatively complete livable spaces that serve a variety of uses, users, and transportation modes and reduce the need for cars for travel.
Reality mining is the collection and analysis of machine-sensed environmental data pertaining to human social behavior, with the goal of identifying predictable patterns of behavior. In 2008, MIT Technology Review called it one of the "10 technologies most likely to change the way we live."
Computational sustainability is an emerging field that attempts to balance societal, economic, and environmental resources for the future well-being of humanity using methods from mathematics, computer science, and information science fields. Sustainability in this context refers to the world's ability to sustain biological, social, and environmental systems in the long term. Using the power of computers to process large quantities of information, decision making algorithms allocate resources based on real-time information. Applications advanced by this field are widespread across various areas. For example, artificial intelligence and machine learning techniques are created to promote long-term biodiversity conservation and species protection. Smart grids implement renewable resources and storage capabilities to control the production and expenditure of energy. Intelligent transportation system technologies can analyze road conditions and relay information to drivers so they can make smarter, more environmentally-beneficial decisions based on real-time traffic information.
Shared transport or shared mobility is a transportation system where travelers share a vehicle either simultaneously as a group or over time as personal rental, and in the process share the cost of the journey, thus purportedly creating a hybrid between private vehicle use and mass or public transport. It is a transportation strategy that allows users to access transportation services on an as-needed basis. Shared mobility is an umbrella term that encompasses a variety of transportation modes including carsharing, Bicycle-sharing systems, ridesharing companies, carpools, and microtransit.
The environmental impact of transport are significant because transport is a major user of energy, and burns most of the world's petroleum. This creates air pollution, including nitrous oxides and particulates, and is a significant contributor to global warming through emission of carbon dioxide. and also plant pollution, by heavy metals. Within the transport sector, road transport is the largest contributor to global warming.
Individual action on climate change is about personal choices that everyone can make to reduce the greenhouse gas emissions of their lifestyles. Such personal choices are related to the way people travel, their diet, shopping habits, consumption of goods and services, number of children they have and so on. Individuals can also get active in local and political advocacy work around climate action. People who wish to reduce their carbon footprint, can for example reduce their air travel for holidays, use bicycles instead of cars on a daily basis, eat a plant-based diet, and use consumer products for longer. Avoiding meat and dairy products has been called "the single biggest way" how individuals can reduce their environmental impacts.
Sustainable consumer behavior is the sub-discipline of consumer behavior that studies why and how consumers do or do not incorporate sustainability priorities into their consumption behavior. It studies the products that consumers select, how those products are used, and how they are disposed of in pursuit of consumers' sustainability goals.
The UC Irvine Institute of Transportation Studies (ITS), is a University of California organized research unit with sister branches at UC Berkeley, UC Davis, and UCLA. ITS was established to foster research, education, and training in the field of transportation. UC Irvine ITS is located on the fourth floor of the Anteater Instruction and Research Building at University of California, Irvine's main Campus, and also houses the UC Irvine Transportation Science graduate studies program.
Flight shame or flygskam (Swedish) is a social movement that discourages air travel due to its environmental impact, including outsized carbon emissions linked to anthropogenic climate change. Originating in Sweden, the term was popularized by climate activist Greta Thunberg, with the movement alternatively known as an anti-flying or anti-flight movement.
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