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Transportation Forecasting
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 i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Road Space Requirements
A road is a linear way for the conveyance of traffic that mostly has an improved surface for use by vehicles (motorized and non-motorized) and pedestrians. Unlike streets, the main function of roads is transportation. There are many types of roads, including parkways, avenues, controlled-access highways (freeways, motorways, and expressways), tollways, interstates, highways, thoroughfares, and local roads. The primary features of roads include lanes, sidewalks (pavement), roadways (carriageways), medians, shoulders, verges, bike paths (cycle paths), and shared-use paths. Definitions Historically many roads were simply recognizable routes without any formal construction or some maintenance. The Organization for Economic Co-operation and Development (OECD) defines a road as "a line of communication (travelled way) using a stabilized base other than rails or air strips open to public traffic, primarily for the use of road motor vehicles running on their own wheels", which ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Iterative Proportional Fitting
The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output analysis, etc.), RAS algorithm in economics, raking in survey statistics, and matrix scaling in computer science) is the operation of finding the fitted matrix X which is the closest to an initial matrix Z but with the row and column totals of a target matrix Y (which provides the constraints of the problem; the interior of Y is unknown). The fitted matrix being of the form X=PZQ, where P and Q are diagonal matrices such that X has the margins (row and column sums) of Y. Some algorithms can be chosen to perform biproportion. We have also the entropy maximization, information loss minimization (or cross-entropy) or RAS which consists of factoring the matrix rows to match the specified row totals, then factoring its columns to match the specified column totals; each step usually disturbs the previous step’s match, so these steps are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automatic Number-plate Recognition
Automatic number-plate recognition (ANPR; see also other names below) is a technology that uses optical character recognition on images to read vehicle registration plates to create vehicle location data. It can use existing closed-circuit television, road-rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check if a vehicle is registered or licensed. It is also used for electronic toll collection on pay-per-use roads and as a method of cataloguing the movements of traffic, for example by highways agencies. Automatic number-plate recognition can be used to store the images captured by the cameras as well as the text from the license plate, with some configurable to store a photograph of the driver. Systems commonly use infrared lighting to allow the camera to take the picture at any time of day or night. ANPR technology must take into account plate variations fr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Road Network
A street network is a system of interconnecting lines and points (called ''edges'' and ''nodes'' in network science) that represent a system of streets or roads for a given area. A street network provides the foundation for network analysis; for example, finding the best route or creating service areas.Wade, T. and Sommer, S. eds. A to Z GIS' They greatly affect in-town movement and traffic. Street networks can become very complex in cities. Street networks are very often localized, because there is little non-highway transportation from town to town. The U.S. Highway System is like a street network, but it is national, and consists of highways instead of streets and roads. See also * Braess's paradox * Transport network * International E-road network * Inca road system * Traffic analysis ** Traffic flow ** Permeability * Grid plan * List of cities that are inaccessible by road References {{Authority control Network Network, networking and networked may refer to: Scien ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Big Data
Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe Big data is the one associated with large body of information that we could not comprehend when used only in smaller amounts. In it primary definition though, Big data refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: ''volume'', ''variety'', and ''velocity''. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains. Data science is related to data mining, machine learning, big data, computational statistics and analytics. Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyse actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about scien ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bilevel Optimization
Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred to as the upper-level optimization task, and the inner optimization task is commonly referred to as the lower-level optimization task. These problems involve two kinds of variables, referred to as the upper-level variables and the lower-level variables. Mathematical formulation of the problem A general formulation of the bilevel optimization problem can be written as follows: \min\limits_\;\; F(x,y) subject to: G_i(x,y) \leq 0, for i \in \ y \in \arg \min \limits_ \ where : F,f: R^ \times R^ \to R : G_i,g_j: R^ \times R^ \to R : X \subseteq R^ : Y \subseteq R^. In the above formulation, F represents the upper-level objective function and f represents the lower-level objective function. Similarly x represents the upper-level decision vector and y represents the lower-level decision vector. G_i and g_j represent th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nash Equilibrium
In game theory, the Nash equilibrium, named after the mathematician John Nash, is the most common way to define the solution of a non-cooperative game involving two or more players. In a Nash equilibrium, each player is assumed to know the equilibrium strategies of the other players, and no one has anything to gain by changing only one's own strategy. The principle of Nash equilibrium dates back to the time of Cournot, who in 1838 applied it to competing firms choosing outputs. If each player has chosen a strategy an action plan based on what has happened so far in the game and no one can increase one's own expected payoff by changing one's strategy while the other players keep their's unchanged, then the current set of strategy choices constitutes a Nash equilibrium. If two players Alice and Bob choose strategies A and B, (A, B) is a Nash equilibrium if Alice has no other strategy available that does better than A at maximizing her payoff in response to Bob choosing B, and Bo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
User Equilibrium
John Glen Wardrop (1922–1989), born in Warwick, England, was an English mathematician and transport analyst who developed what became known as Wardrop's first and second principles of equilibrium in the field of traffic assignment. He studied at Downing College, Cambridge, and worked in Operational Research at British Bomber Command during the Second World War. He then helped to set up, and later headed, the Traffic Section of the Road Research Laboratory near Slough (Part of the Directorate of Scientific and Industrial Research within the UK Civil Service) where he published his work on equilibrium. He subsequently followed Dr Reuben Smeed to University College London, becoming Reader Emeritus in Traffic Studies. Wardrop equilibria In studies about traffic assignment, network equilibrium models are commonly used for the prediction of traffic patterns in transportation networks that are subject to congestion. The idea of traffic equilibrium originated as early as 1924, with ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Glen Wardrop
John Glen Wardrop (1922–1989), born in Warwick, England, was an English mathematician and transport analyst who developed what became known as Wardrop's first and second principles of equilibrium in the field of Traffic assignment#Equilibrium assignment, traffic assignment. He studied at Downing College, Cambridge, and worked in Operations Research, Operational Research at British Bomber Command during the Second World War. He then helped to set up, and later headed, the Traffic Section of the Road Research Laboratory near Slough (Part of the Directorate of Scientific and Industrial Research within the UK Civil Service) where he published his work on equilibrium. He subsequently followed Dr Reuben Smeed to University College London, becoming Reader Emeritus in Traffic Studies. Wardrop equilibria In studies about Traffic assignment#Equilibrium assignment, traffic assignment, network equilibrium models are commonly used for the prediction of traffic patterns in transportation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Route Assignment
Route assignment, route choice, or traffic assignment concerns the selection of routes (alternative called paths) 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 (a route is simply a chain of links between an origin and destination). We need to undertake traffic (or trip) 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. General Approaches Long-standing techniques The problem of esti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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