Road surfaceA road surface (English), or pavement (American), is the durable surface material laid down on an area intended to sustain vehicular or foot traffic, such as a road or walkway. In the past, gravel road surfaces, macadam, hoggin, cobblestone and granite setts were extensively used, but these have mostly been replaced by asphalt or concrete laid on a compacted base course. Asphalt mixtures have been used in pavement construction since the beginning of the 20th century and are of two types: metalled (hard-surfaced) and unmetalled roads.
RoadA road is a thoroughfare for the conveyance of traffic that mostly has an improved surface for use by vehicles (motorized and non-motorized) and pedestrians. Unlike streets, whose primary function is to serve as public spaces, 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.
Road traffic safetyRoad traffic safety refers to the methods and measures used to prevent road users from being killed or seriously injured. Typical road users include pedestrians, cyclists, motorists, vehicle passengers, horse riders, and passengers of on-road public transport (mainly buses and trams). Best practices in modern road safety strategy: The basic strategy of a Safe System approach is to ensure that in the event of a crash, the impact energies remain below the threshold likely to produce either death or serious injury.
Road surface markingRoad surface marking is any kind of device or material that is used on a road surface in order to convey official information; they are commonly placed with road marking machines (also referred to as road marking equipment or pavement marking equipment). They can also be applied in other facilities used by vehicles to mark parking spaces or designate areas for other uses. In some countries and areas (France, Italy, Czech Republic, Slovakia etc.), road markings are conceived as horizontal traffic signs, as opposed to vertical traffic signs placed on posts.
Road textureRoad surface textures are deviations from a planar and smooth surface, affecting the vehicle/tyre interaction. Pavement texture is divided into: microtexture with wavelengths from 0 mm to , macrotexture with wavelengths from to and megatexture with wavelengths from to . Microtexture (MiTx) is the collaborative term for a material's crystallographic parameters and other aspects of micro-structure: such as morphology, including size and shape distributions; chemical composition; and crystal orientation and relationships While vehicle suspension deflection and dynamic tire loads are affected by longer wavelength (roughness), road texture affects the interaction between the road surface and the tire footprint.
Gravel roadA gravel road is a type of unpaved road surfaced with gravel that has been brought to the site from a quarry or stream bed. They are common in less-developed nations, and also in the rural areas of developed nations such as Canada and the United States. In New Zealand, and other Commonwealth countries, they may be known as metal roads. They may be referred to as "dirt roads" in common speech, but that term is used more for unimproved roads with no surface material added.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Road transportRoad transport or road transportation is a type of transport using roads. Transport on roads can be roughly grouped into the transportation of goods and transportation of people. In many countries licensing requirements and safety regulations ensure a separation of the two industries. Movement along roads may be by bike, automobile, bus, truck, or by animal such as horse or oxen. Standard networks of roads were adopted by Romans, Persians, Aztec, and other early empires, and may be regarded as a feature of empires.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
Road debrisRoad debris, a form of road hazard, is debris on or off a road. Road debris includes substances, materials, and objects that are foreign to the normal roadway environment. Debris may be produced by vehicular or non-vehicular sources, but in all cases it is considered litter, a form of solid waste. Debris may tend to collect in areas where vehicles do not drive, such as on the edges (shoulder), around traffic islands, and junctions. Road spray or tire kickup is road debris (usually liquid water) that has been kicked up, pushed out, or sprayed out from a tire.
Off-road vehicleAn off-road vehicle (ORV), sometimes referred to as an off-highway vehicle (OHV), overland vehicle, or adventure vehicle, is considered to be any type of vehicle which is capable of driving off paved or gravel surfaces, such as trails and forest roads that have rough and low traction surfaces. These vehicles are generally characterized by having large tyres with deep, open treads, a flexible suspension, or even caterpillar tracks. Because of their versatility, several types of motorsports involve racing off-road vehicles.
Intelligent transportation systemAn intelligent transportation system (ITS) is an advanced application which aims to provide innovative services relating to different modes of transport and traffic management and enable users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. Some of these technologies include calling for emergency services when an accident occurs, using cameras to enforce traffic laws or signs that mark speed limit changes depending on conditions.
Hardware accelerationHardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any transformation of data that can be calculated in software running on a generic CPU can also be calculated in custom-made hardware, or in some mix of both. To perform computing tasks more quickly (or better in some other way), generally one can invest time and money in improving the software, improving the hardware, or both.
Glossary of road transport termsTerminology related to road transport—the transport of passengers or goods on paved (or otherwise improved) routes between places—is diverse, with variation between dialects of English. There may also be regional differences within a single country, and some terms differ based on the side of the road traffic drives on. This glossary is an alphabetical listing of road transport terms. 2+1 road A specific category of three-lane road, consisting of two lanes in one direction and one lane in the other, alternating every few kilometres, and separated usually with a steel cable barrier.
Support vector machineIn machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974).
PerceptronIn machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
Computer hardwareComputer hardware includes the physical parts of a computer, such as the case, central processing unit (CPU), random access memory (RAM), monitor, mouse, keyboard, computer data storage, graphics card, sound card, speakers and motherboard. By contrast, software is the set of instructions that can be stored and run by hardware. Hardware is so-termed because it is "hard" or rigid with respect to changes, whereas software is "soft" because it is easy to change. Hardware is typically directed by the software to execute any command or instruction.
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
Anti-lock braking systemAn anti-lock braking system (ABS) is a safety anti-skid braking system used on aircraft and on land vehicles, such as cars, motorcycles, trucks, and buses. ABS operates by preventing the wheels from locking up during braking, thereby maintaining tractive contact with the road surface and allowing the driver to maintain more control over the vehicle. ABS is an automated system that uses the principles of threshold braking and cadence braking, techniques which were once practiced by skillful drivers before ABS was widespread.
Unsupervised learningUnsupervised learning, is paradigm in machine learning where, in contrast to supervised learning and semi-supervised learning, algorithms learn patterns exclusively from unlabeled data. Neural network tasks are often categorized as discriminative (recognition) or generative (imagination). Often but not always, discriminative tasks use supervised methods and generative tasks use unsupervised (see Venn diagram); however, the separation is very hazy. For example, object recognition favors supervised learning but unsupervised learning can also cluster objects into groups.
