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. [1]
Traffic forecasts are used for several key purposes in transportation policy, planning, and engineering: to calculate the capacity of infrastructure, e.g., how many lanes a bridge should have; to estimate the financial and social viability of projects, e.g., using cost–benefit analysis and social impact assessment; and to calculate environmental impacts, e.g., air pollution and noise.
Within the rational planning framework, transportation forecasts have traditionally followed the sequential four-step model or urban transportation planning (UTP) procedure, first implemented on mainframe computers in the 1950s at the Detroit Metropolitan Area Traffic Study and Chicago Area Transportation Study (CATS).
Land-use forecasting starts the process. Typically, forecasts are made for the region as a whole, e.g., of population growth. Such forecasts provide control totals for the local land use analysis. Typically, the region is divided into zones and by trend or regression analysis, the population and employment are determined for each.
The four steps of the classical urban transportation planning system model are:
After the classical model, there is an evaluation according to an agreed set of decision criteria and parameters. A typical criterion is cost–benefit analysis. Such analysis might be applied after the network assignment model identifies needed capacity: is such capacity worthwhile? In addition to identifying the forecasting and decision steps as additional steps in the process, it is important to note that forecasting and decision-making permeate each step in the UTP process. Planning deals with the future, and it is forecasting dependent.
Activity-based models are another class of models that predict for individuals where and when specific activities (e.g. work, leisure, shopping, ...) are conducted.
The major premise behind activity-based models is that travel demand is derived from activities that people need or wish to perform, with travel decisions forming part of the scheduling decisions. Travel is then seen as just one of the attributes of a system. The travel model is therefore set within the context of an agenda, as a component of an activity scheduling decision.
Activity-based models offer other possibilities than four-step models, e.g. to model environmental issues such as emissions and exposure to air pollution. Although their obvious advantages for environmental purposes were recognized by Shiftan almost a decade ago, [3] applications to exposure models remain scarce. Activity-based models have recently been used to predict emissions [4] and air quality. [5] [6] They can also provide a better total estimate of exposure while also enabling the disaggregation of individual exposure over activities. [7] [8] They can therefore be used to reduce exposure misclassification and establish relationships between health impacts and air quality more precisely. [9] Policy makers can use activity-based models to devise strategies that reduce exposure by changing time activity patterns or that target specific groups in the population. [10] [11]
These models are intended to forecast the effect of changes in the transport network and operations over the future location of activities, and then forecast the effect of these new locations over the transport demand.
As data science and big data technologies become available to transport modelling, research is moving towards modelling and predicting behaviours of individual drivers in whole cities at the individual level. [12] This will involve understanding individual drivers' origins and destinations as well as their utility functions. This may be done by fusing per-driver data collected on road networks, such as by ANPR cameras, with other data on individuals, such as data from their social network profiles, store card purchase data, and search engine history. This will lead to more accurate predictions, enhanced ability to control traffic for customized prioritization of particular drivers, but also to ethical concerns as local and national governments use more data about identifiable individuals. While the integration of such partially personal data is tempting, there are considerable privacy concerns over the possibilities, related to the criticisms of mass surveillance.
Although not identified as steps in the UTP process, a lot of data gathering is involved in the UTP analysis process. Census and land use data are obtained, along with home interview surveys and journey surveys. Home interview surveys, land use data, and special trip attraction surveys provide the information on which the UTP analysis tools are exercised.
Data collection, management, and processing; model estimation; and use of models to yield plans are much used techniques in the UTP process. In the early days, in the USA, census data was augmented that with data collection methods that had been developed by the Bureau of Public Roads (a predecessor of the Federal Highway Administration): traffic counting procedures, cordon "where are you coming from and where are you going" counts, and home interview techniques. Protocols for coding networks and the notion of analysis or traffic zones emerged at the CATS.
Model estimation used existing techniques, and plans were developed using whatever models had been developed in a study. The main difference between now and then is the development of some analytic resources specific to transportation planning, in addition to the BPR data acquisition techniques used in the early days.
The sequential and aggregate nature of transportation forecasting has come under much criticism. While improvements have been made, in particular giving an activity-base to travel demand, much remains to be done. In the 1990s, most federal investment in model research went to the Transims project at Los Alamos National Laboratory, developed by physicists. While the use of supercomputers and the detailed simulations may be an improvement on practice, they have yet to be shown to be better (more accurate) than conventional models. A commercial version was spun off to IBM, [13] and an open source version is also being actively maintained as TRANSIMS Open-Source. [14] [15]
A 2009 Government Accountability Office report noted that federal review of transportation modeling focused more on process requirements (for example, did the public have adequate opportunity to comment?) than on transportation outcomes (such as reducing travel times, or keeping pollutant or greenhouse gas emissions within national standards). [16]
One of the major oversights in the use of transportation models in practice is the absence of any feedback from transportation models on land use. Highways and transit investments not only respond to land use, they shape it as well. [17]
Transportation engineering or transport engineering is the application of technology and scientific principles to the planning, functional design, operation and management of facilities for any mode of transportation in order to provide for the safe, efficient, rapid, comfortable, convenient, economical, and environmentally compatible movement of people and goods transport.
Transport economics is a branch of economics founded in 1959 by American economist John R. Meyer that deals with the allocation of resources within the transport sector. It has strong links to civil engineering. Transport economics differs from some other branches of economics in that the assumption of a spaceless, instantaneous economy does not hold. People and goods flow over networks at certain speeds. Demands peak. Advance ticket purchase is often induced by lower fares. The networks themselves may or may not be competitive. A single trip may require the bundling of services provided by several firms, agencies and modes.
Transportation planning is the process of defining future policies, goals, investments, and spatial planning designs to prepare for future needs to move people and goods to destinations. As practiced today, it is a collaborative process that incorporates the input of many stakeholders including various government agencies, the public and private businesses. Transportation planners apply a multi-modal and/or comprehensive approach to analyzing the wide range of alternatives and impacts on the transportation system to influence beneficial outcomes.
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.
Land-use forecasting undertakes to project the distribution and intensity of trip generating activities in the urban area. In practice, land-use models are demand-driven, using as inputs the aggregate information on growth produced by an aggregate economic forecasting activity. Land-use estimates are inputs to the transportation planning process.
The GEH Statistic is a formula used in traffic engineering, traffic forecasting, and traffic modelling to compare two sets of traffic volumes. The GEH formula gets its name from Geoffrey E. Havers, who invented it in the 1970s while working as a transport planner in London, England. Although its mathematical form is similar to a chi-squared test, is not a true statistical test. Rather, it is an empirical formula that has proven useful for a variety of traffic analysis purposes.
Roadway air dispersion modeling is the study of air pollutant transport from a roadway or other linear emitter. Computer models are required to conduct this analysis, because of the complex variables involved, including vehicle emissions, vehicle speed, meteorology, and terrain geometry. Line source dispersion has been studied since at least the 1960s, when the regulatory framework in the United States began requiring quantitative analysis of the air pollution consequences of major roadway and airport projects. By the early 1970s this subset of atmospheric dispersion models was being applied to real-world cases of highway planning, even including some controversial court cases.
Land transport is the transport or movement of people, animals or goods from one location to another location on land. This is in contrast with other main types of transport such as maritime transport and aviation. The two main forms of land transport can be considered to be rail transport and road transport.
TRANSIMS is an integrated set of tools developed to conduct regional transportation system analyses. With the goal of establishing TRANSIMS as an ongoing public resource available to the transportation community, TRANSIMS is made available under the NASA Open Source Agreement Version 1.3
Air pollution is the contamination of air due to the presence of substances called pollutants in the atmosphere that are harmful to the health of humans and other living beings, or cause damage to the climate or to materials. It is also the contamination of the indoor or outdoor environment either by chemical, physical, or biological agents that alters the natural features of the atmosphere. There are many different types of air pollutants, such as gases, particulates and biological molecules. Air pollution can cause diseases, allergies, and even death to humans; it can also cause harm to other living organisms such as animals and crops, and may damage the natural environment or built environment. Air pollution can be caused by both human activities and natural phenomena.
Transport or transportation is the intentional movement of humans, animals, and goods from one location to another. Modes of transport include air, land, water, cable, pipelines, and space. The field can be divided into infrastructure, vehicles, and operations. Transport enables human trade, which is essential for the development of civilizations.
Active mobility, soft mobility, active travel, active transport or active transportation is the transport of people or goods, through non-motorized means, based around human physical activity. The best-known forms of active mobility are walking and cycling, though other modes include running, rowing, skateboarding, kick scooters and roller skates. Due to its prevalence, cycling is sometimes considered separately from the other forms of active mobility.
Aimsun Live is a traffic forecasting solution based on simulation, developed and marketed by Aimsun.
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.
Public transport is a system of transport for passengers by group travel systems available for use by the general public unlike private transport, typically managed on a schedule, operated on established routes, and that may charge a posted fee for each trip. There is no rigid definition of which kinds of transport are included, and air travel is often not thought of when discussing public transport—dictionaries use wording like "buses, trains, etc." Examples of public transport include city buses, trolleybuses, trams and passenger trains, rapid transit and ferries. Public transport between cities is dominated by airlines, coaches, and intercity rail. High-speed rail networks are being developed in many parts of the world.
Traffic simulation or the simulation of transportation systems is the mathematical modeling of transportation systems through the application of computer software to better help plan, design, and operate transportation systems. Simulation of transportation systems started in the 1950s, and is an important area of discipline in traffic engineering and transportation planning today. Various national and local transportation agencies, academic institutions and consulting firms use simulation to aid in their management of transportation networks.
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.
Urban freight distribution is the system and process by which goods are collected, transported, and distributed within urban environments. The urban freight system can include seaports, airports, manufacturing facilities, and warehouse/distribution centers that are connected by a network of railroads, rail yards, pipelines, highways, and roadways that enable goods to get to their destinations.
The following outline is provided as an overview of and topical guide to transportation planning.