Intelligent transportation system

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Intelligent_transportation_system 

ITS graphical user interface displaying the Hungarian highway network and its data points

An 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.

Although ITS may refer to all modes of transport, the directive of the European Union 2010/40/EU, made on July 7, 2010, defined ITS as systems in which information and communication technologies are applied in the field of road transport, including infrastructure, vehicles and users, and in traffic management and mobility management, as well as for interfaces with other modes of transport. ITS may be used to improve the efficiency and safety of transport in a number of situations, i.e. road transport, traffic management, mobility, etc. ITS technology is being adopted across the world to increase capacity of busy roads and reduce journey times.

Background

Governmental activity in the area of ITS is further motivated by an increasing focus on homeland security. Many of the proposed ITS systems also involve surveillance of the roadways, which is a priority of homeland security. Funding of many systems comes either directly through homeland security organisations or with their approval. Further, ITS can play a role in the rapid mass evacuation of people in urban centers after large casualty events such as a result of a natural disaster or threat. Much of the infrastructure and planning involved with ITS parallels the need for homeland security systems.

In the developing world, the migration from rural to urbanized habitats has progressed differently. Many areas of the developing world have urbanised without significant motorisation and the formation of suburbs. A small portion of the population can afford automobiles, but the automobiles greatly increase congestion in these multimodal transportation systems. They also produce considerable air pollution, pose a significant safety risk, and exacerbate feelings of inequities in the society. High population density could be supported by a multimodal system of walking, bicycle transportation, motorcycles, buses, and trains.

Other parts of the developing world, such as China, India and Brazil remain largely rural but are rapidly urbanising and industrialising. In these areas a motorised infrastructure is being developed alongside motorisation of the population. Great disparity of wealth means that only a fraction of the population can motorise, and therefore the highly dense multimodal transportation system for the poor is cross-cut by the highly motorised transportation system for the rich.

Intelligent transportation technologies

Intelligent transport systems vary in technologies applied, from basic management systems such as car navigation; traffic signal control systems; container management systems; variable message signs; automatic number plate recognition or speed cameras to monitor applications, such as security CCTV systems, and automatic incident detection or stopped vehicle detection systems; to more advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems; weather information; bridge de-icing (US deicing) systems; and the like. Additionally, predictive techniques are being developed to allow advanced modelling and comparison with historical baseline data. Some of these technologies are described in the following sections.

Wireless communications

Traffic monitoring gantry with wireless communication dish antenna

Various forms of wireless communications technologies have been proposed for intelligent transportation systems. Radio modem communication on UHF and VHF frequencies are widely used for short and long range communication within ITS.

Short-range communications of 350 m can be accomplished using IEEE 802.11 protocols, specifically 802.11p (WAVE) or the dedicated short-range communications (DSRC) 802.11bd standard being promoted by the Intelligent Transportation Society of America and the United States Department of Transportation. Theoretically, the range of these protocols can be extended using mobile ad hoc networks or mesh networking.

Longer range communications use infrastructure networks such as 5G. Long-range communications using these methods are well established, but, unlike the short-range protocols, these methods require extensive and very expensive infrastructure deployment.

Computational technologies

Recent advances in vehicle electronics have led to a move towards fewer, more capable computer processors on a vehicle. A typical vehicle in the early 2000s would have between 20 and 100 individual networked microcontroller/programmable logic controller modules with non-real-time operating systems. The current trend is toward fewer, more costly microprocessor modules with hardware memory management and real-time operating systems. The new embedded system platforms allow for more sophisticated software applications to be implemented, including model-based process control, artificial intelligence, and ubiquitous computing. Perhaps the most important of these for intelligent transportation systems is artificial intelligence.

Floating car data/floating cellular data

Main article: Floating car data

RFID E-ZPass reader attached to the pole and its antenna (right) used in traffic monitoring in New York City by using vehicle re-identification method

"Floating car" or "probe" data collected other transport routes. Broadly speaking, four methods have been used to obtain the raw data:

• Triangulation method. In developed countries a high proportion of cars contain one or more mobile phones. The phones periodically transmit their presence information to the mobile phone network, even when no voice connection is established. In the mid-2000s, attempts were made to use mobile phones as anonymous traffic probes. As a car moves, so does the signal of any mobile phones that are inside the vehicle. By measuring and analysing network data using triangulation, pattern matching or cell-sector statistics (in an anonymous format), the data was converted into traffic flow information. With more congestion, there are more cars, more phones, and thus, more probes.

In metropolitan areas, the distance between antennas is shorter and in theory accuracy increases. An advantage of this method is that no infrastructure needs to be built along the road; only the mobile phone network is leveraged. But in practice the triangulation method can be complicated, especially in areas where the same mobile phone towers serve two or more parallel routes (such as a motorway (freeway) with a frontage road, a motorway (freeway) and a commuter rail line, two or more parallel streets, or a street that is also a bus line). By the early 2010s, the popularity of the triangulation method was declining.

• Vehicle re-identification. Vehicle re-identification methods require sets of detectors mounted along the road. In this technique, a unique serial number for a device in the vehicle is detected at one location and then detected again (re-identified) further down the road. Travel times and speed are calculated by comparing the time at which a specific device is detected by pairs of sensors. This can be done using the MAC addresses from Bluetooth or other devices, or using the RFID serial numbers from electronic toll collection (ETC) transponders (also called "toll tags").
• GPS based methods. An increasing number of vehicles are equipped with in-vehicle satnav/GPS (satellite navigation) systems that have two-way communication with a traffic data provider. Position readings from these vehicles are used to compute vehicle speeds. Modern methods may not use dedicated hardware but instead Smartphone based solutions using so called Telematics 2.0 approaches.
• Smartphone-based rich monitoring. Smartphones having various sensors can be used to track traffic speed and density. The accelerometer data from smartphones used by car drivers is monitored to find out traffic speed and road quality. Audio data and GPS tagging of smartphones enables identification of traffic density and possible traffic jams. This was implemented in Bangalore, India as a part of a research experimental system Nericell.

Floating car data technology provides advantages over other methods of traffic measurement:

• Less expensive than sensors or cameras
• More coverage (potentially including all locations and streets)
• Faster to set up and less maintenance
• Works in all weather conditions, including heavy rain

Sensing

An active RFID tag used for electronic toll collection

Technological advances in telecommunications and information technology, coupled with ultramodern/state-of-the-art microchip, RFID (Radio Frequency Identification), and inexpensive intelligent beacon sensing technologies, have enhanced the technical capabilities that will facilitate motorist safety benefits for intelligent transportation systems globally. Sensing systems for ITS are vehicle- and infrastructure-based networked systems, i.e., intelligent vehicle technologies. Infrastructure sensors are indestructible (such as in-road reflectors) devices that are installed or embedded in the road or surrounding the road (e.g., on buildings, posts, and signs), as required, and may be manually disseminated during preventive road construction maintenance or by sensor injection machinery for rapid deployment. Vehicle-sensing systems include deployment of infrastructure-to-vehicle and vehicle-to-infrastructure electronic beacons for identification communications and may also employ video automatic number plate recognition or vehicle magnetic signature detection technologies at desired intervals to increase sustained monitoring of vehicles operating in critical zones of world.

Inductive loop detection

Saw cut loop detectors for vehicle detection buried in the pavement at this intersection as seen by the rectangular shapes of loop detector sealant at the bottom part of this picture

Inductive loops can be placed in a roadbed to detect vehicles as they pass through the loop's magnetic field. The simplest detectors simply count the number of vehicles during a unit of time (typically 60 seconds in the United States) that pass over the loop, while more sophisticated sensors estimate the speed, length, and class of vehicles and the distance between them. Loops can be placed in a single lane or across multiple lanes, and they work with very slow or stopped vehicles as well as vehicles moving at high speed.

Video vehicle detection

Traffic-flow measurement and automatic incident detection using video cameras is another form of vehicle detection. Since video detection systems such as those used in automatic number plate recognition do not involve installing any components directly into the road surface or roadbed, this type of system is known as a "non-intrusive" method of traffic detection. Video from cameras is fed into processors that analyse the changing characteristics of the video image as vehicles pass. The cameras are typically mounted on poles or structures above or adjacent to the roadway. Most video detection systems require some initial configuration to "teach" the processor the baseline background image. This usually involves inputting known measurements such as the distance between lane lines or the height of the camera above the roadway. A single video detection processor can detect traffic simultaneously from one to eight cameras, depending on the brand and model. The typical output from a video detection system is lane-by-lane vehicle speeds, counts, and lane occupancy readings. Some systems provide additional outputs including gap, headway, stopped-vehicle detection, and wrong-way vehicle alarms.

Bluetooth detection

Bluetooth is an accurate and inexpensive way to transmit position from a vehicle in motion. Bluetooth devices in passing vehicles are detected by sensing devices along the road. If these sensors are interconnected they are able to calculate travel time and provide data for origin and destination matrices. Compared to other traffic measurement technologies, Bluetooth measurement has some differences:

• Accurate measurement points with absolute confirmation to provide to the second travel times.
• Is non-intrusive, which can lead to lower-cost installations for both permanent and temporary sites.
• Is limited to how many Bluetooth devices are broadcasting in a vehicle so counting and other applications are limited.
• Systems are generally quick to set up with little to no calibration needed.

Since Bluetooth devices become more prevalent on board vehicles and with more portable electronics broadcasting, the amount of data collected over time becomes more accurate and valuable for travel time and estimation purposes, more information can be found in.

It is also possible to measure traffic density on a road using the audio signal that consists of the cumulative sound from tire noise, engine noise, engine-idling noise, honks and air turbulence noise. A roadside-installed microphone picks up the audio that comprises the various vehicle noise and audio signal processing techniques can be used to estimate the traffic state. The accuracy of such a system compares well with the other methods described above.

Radar detection

Radars are mounted on the side of the road to measure traffic flow and for stopped and stranded vehicle detection purposes. Like video systems, radar learns its environment during set up so can distinguish between vehicles and other objects. It can also operate in conditions of low visibility. Traffic flow radar uses a "side-fire" technique to look across all traffic lanes in a narrow band to count the number of passing vehicles and estimate traffic density. For stopped vehicle detection (SVD) and automatic incident detection, 360 degree radar systems are used as they scan all lanes along large stretches of road. Radar is reported to have better performance over longer ranges than other technologies. SVD radar will be installed on all Smart motorways in the UK.

Information fusion from multiple traffic sensing modalities

The data from the different sensing technologies can be combined in intelligent ways to determine the traffic state accurately. A data fusion based approach that utilizes the road side collected acoustic, image and sensor data has been shown to combine the advantages of the different individual methods.

Intelligent transportation applications

Emergency vehicle notification systems

In 2015, the EU passed a law required automobile manufacturers to equip all new cars with eCall, a European initiative that assists motorists in the case of a collision. The in-vehicle eCall is generated either manually by the vehicle occupants or automatically via activation of in-vehicle sensors after an accident. When activated, the in-vehicle eCall device will establish an emergency call carrying both voice and data directly to the nearest emergency point (normally the nearest E1-1-2 public safety answering point, PSAP). The voice call enables the vehicle occupant to communicate with the trained eCall operator. At the same time, a minimum set of data will be sent to the eCall operator receiving the voice call.

The minimum set of data contains information about the incident, including time, precise location, the direction the vehicle was traveling, and vehicle identification. The pan-European eCall aims to be operative for all new type-approved vehicles as a standard option. Depending on the manufacturer of the eCall system, it could be mobile phone based (Bluetooth connection to an in-vehicle interface), an integrated eCall device, or a functionality of a broader system like navigation, Telematics device, or tolling device. eCall is expected to be offered, at earliest, by the end of 2010, pending standardization by the European Telecommunications Standards Institute and commitment from large EU member states such as France and the United Kingdom.

Congestion pricing gantry at North Bridge Road, Singapore

The EC funded project SafeTRIP is developing an open ITS system that will improve road safety and provide a resilient communication through the use of S-band satellite communication. Such platform will allow for greater coverage of the Emergency Call Service within the EU.

Automatic road enforcement

Main article: Traffic enforcement camera

Automatic speed enforcement gantry or lombada eletrônica with ground sensors at Brasilia, D.F.

A traffic enforcement camera system, consisting of a camera and a vehicle-monitoring device, is used to detect and identify vehicles disobeying a speed limit or some other road legal requirement and automatically ticket offenders based on the license plate number. Traffic tickets are sent by mail. Applications include:

• Speed cameras that identify vehicles traveling over the legal speed limit. Many such devices use radar to detect a vehicle's speed or electromagnetic loops buried in each lane of the road.
• Red light cameras that detect vehicles that cross a stop line or designated stopping place while a red traffic light is showing.
• Bus lane cameras that identify vehicles traveling in lanes reserved for buses. In some jurisdictions, bus lanes can also be used by taxis or vehicles engaged in car pooling.
• Level crossing cameras that identify vehicles crossing railways at grade illegally.
• Double white line cameras that identify vehicles crossing these lines.
• High-occupancy vehicle lane cameras that identify vehicles violating HOV requirements.

Variable speed limits

Further information: Speed limit § Variable speed limits

Example variable speed limit sign in the United States

Recently some jurisdictions have begun experimenting with variable speed limits that change with road congestion and other factors. Typically such speed limits only change to decline during poor conditions, rather than being improved in good ones. One example is on Britain's M25 motorway, which circumnavigates London. On the most heavily traveled 14-mile (23 km) section (junction 10 to 16) of the M25 variable speed limits combined with automated enforcement have been in force since 1995. Initial results indicated savings in journey times, smoother-flowing traffic, and a fall in the number of accidents, so the implementation was made permanent in 1997. Further trials on the M25 have been thus far proven inconclusive.

Collision avoidance systems

Japan has installed sensors on its highways to notify motorists that a car is stalled ahead.

Cooperative systems on the road

Communication cooperation on the road includes car-to-car, car-to-infrastructure, and vice versa. Data available from vehicles are acquired and transmitted to a server for central fusion and processing. These data can be used to detect events such as rain (wiper activity) and congestion (frequent braking activities). The server processes a driving recommendation dedicated to a single or a specific group of drivers and transmits it wirelessly to vehicles. The goal of cooperative systems is to use and plan communication and sensor infrastructure to increase road safety. The definition of cooperative systems in road traffic is according to the European Commission:

"Road operators, infrastructure, vehicles, their drivers and other road users will cooperate to deliver the most efficient, safe, secure and comfortable journey. The vehicle-vehicle and vehicle-infrastructure co-operative systems will contribute to these objectives beyond the improvements achievable with stand-alone systems."

World Congress on Intelligent Transport Systems (ITS World Congress) is an annual trade show to promote ITS technologies. ERTICO– ITS Europe, ITS America and ITS AsiaPacific sponsor the annual ITS World Congress and exhibition. Each year the event takes place in a different region (Europe, Americas or Asia-Pacific). The first ITS World Congress was held in Paris in 1994.

Smart transportation – new business models

New mobility and smart transportation models are emerging globally. Bike sharing, car sharing and scooter sharing schemes like Lime or Bird are continuing to gain popularity; electric vehicle charging schemes are taking off in many cities; the connected car is a growing market segment; while new, smart parking solutions are being used by commuters and shoppers all over the world. All these new models provide opportunities for solving last mile issues in urban areas.

ITS in the connected world

Mobile operators are becoming a significant player in these value chains (beyond providing just connectivity). Dedicated apps can be used to take mobile payments, provide data insights and navigation tools, offer incentives and discounts, and act as a digital commerce medium.

Payments and billing flexibility

These new mobility models call for high monetization agility and partner management capabilities. A flexible settlements and billing platform enables revenues to be shared quickly and easily and provides an overall better customer experience. As well as a better service, users can also be rewarded by discounts, loyalty points and rewards, and engaged via direct marketing.

Europe

The Network of National ITS Associations is a grouping of national ITS interests. It was officially announced 7 October 2004 in London. The secretariat is at ERTICO – ITS Europe.

ERTICO – ITS Europe is a public/private partnership promoting the development and deployment of ITS. They connect public authorities, industry players, infrastructure operators, users, national ITS associations and other organisations together. The ERTICO work programme focuses on initiatives to improve transport safety, security and network efficiency whilst taking into account measures to reduce environmental impact.

United States

In the United States, each state has an ITS chapter that holds a yearly conference to promote and showcase ITS technologies and ideas. Representatives from each Department of Transportation (state, cities, towns, and counties) within the state attend this conference.

Latin America

Colombia

In the intermediate cities of Colombia, where the Strategic Public Transportation Systems are implemented, the urban transportation networks must operate under parameters that improve the quality of service provision. Several of the challenges faced by the transportation systems in these cities are aimed at increasing the number of passengers transported in the system and the technological adoption that must be integrated for the management and control of public transportation fleets. Achieving this requires strategic systems to integrate solutions based on intelligent transportation systems and information and communication technologies to optimize fleet control and management, electronic fare collection, road safety, and the delivery of information to users. The functionalities to be covered by the technology in these transportation systems include: fleet scheduling; vehicle location and traceability; cloud storage of operational data; interoperability with other information systems; centralization of operations; passenger counting; data control and visualization.

Feature-oriented programming

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Feature-oriented_programming

In computer programming, feature-oriented programming (FOP) or feature-oriented software development (FOSD) is a programming paradigm for program generation in software product lines (SPLs) and for incremental development of programs.

History

Connection between layer stacks and transformation compositions

FOSD arose out of layer-based designs and levels of abstraction in network protocols and extensible database systems in the late-1980s. A program was a stack of layers. Each layer added functionality to previously composed layers and different compositions of layers produced different programs. Not surprisingly, there was a need for a compact language to express such designs. Elementary algebra fit the bill: each layer was a function (a program transformation) that added new code to an existing program to produce a new program, and a program's design was modeled by an expression, i.e., a composition of transformations (layers). The figure to the left illustrates the stacking of layers i, j, and h (where h is on the bottom and i is on the top). The algebraic notations i(j(h)), i•j•h, and i+j+h have been used to express these designs.

Over time, layers were equated to features, where a feature is an increment in program functionality. The paradigm for program design and generation was recognized to be an outgrowth of relational query optimization, where query evaluation programs were defined as relational algebra expressions, and query optimization was expression optimization. A software product line is a family of programs where each program is defined by a unique composition of features. FOSD has since evolved into the study of feature modularity, tools, analyses, and design techniques to support feature-based program generation.

The second generation of FOSD research was on feature interactions, which originated in telecommunications. Later, the term feature-oriented programming was coined; this work exposed interactions between layers. Interactions require features to be adapted when composed with other features.

A third generation of research focussed on the fact that every program has multiple representations (e.g., source, makefiles, documentation, etc.) and adding a feature to a program should elaborate each of its representations so that all are consistent. Additionally, some of representations could be generated (or derived) from others. In the sections below, the mathematics of the three most recent generations of FOSD, namely GenVoca, AHEAD, and FOMDD are described, and links to product lines that have been developed using FOSD tools are provided. Also, four additional results that apply to all generations of FOSD are: FOSD metamodels, FOSD program cubes, and FOSD feature interactions.

GenVoca

GenVoca (a portmanteau of the names Genesis and Avoca) is a compositional paradigm for defining programs of product lines. Base programs are 0-ary functions or transformations called values:

  f      -- base program with feature f
  h      -- base program with feature h

and features are unary functions/transformations that elaborate (modify, extend, refine) a program:

  i + x  -- adds feature i to program x
  j + x  -- adds feature j to program x

where + denotes function composition. The design of a program is a named expression, e.g.:

  p1 = j + f       -- program p1 has features j and f
  p2 = j + h       -- program p2 has features j and h
  p3 = i + j + h   -- program p3 has features i, j, and h

A GenVoca model of a domain or software product line is a collection of base programs and features (see MetaModels and Program Cubes). The programs (expressions) that can be created defines a product line. Expression optimization is program design optimization, and expression evaluation is program generation.

Note: GenVoca is based on the stepwise development of programs: a process that emphasizes design simplicity and understandability, which are key to program comprehension and automated program construction. Consider program p₃ above: it begins with base program h, then feature j is added (read: the functionality of feature j is added to the codebase of h), and finally feature i is added (read: the functionality of feature i is added to the codebase of j•h).

Note: not all combinations of features are meaningful. Feature models (which can be translated into propositional formulas) are graphical representations that define legal combinations of features.

Note: A more recent formulation of GenVoca is symmetric: there is only one base program, 0 (the empty program), and all features are unary functions. This suggests the interpretation that GenVoca composes program structures by superposition, the idea that complex structures are composed by superimposing simpler structures. Yet another reformulation of GenVoca is as a monoid: a GenVoca model is a set of features with a composition operation (•); composition is associative and there is an identity element (namely 1, the identity function). Although all compositions are possible, not all are meaningful. That's the reason for feature models.

GenVoca features were originally implemented using C preprocessor (#ifdef feature ... #endif) techniques. A more advanced technique, called mixin layers, showed the connection of features to object-oriented collaboration-based designs.

AHEAD

Algebraic Hierarchical Equations for Application Design (AHEAD) generalized GenVoca in two ways. First, it revealed the internal structure of GenVoca values as tuples. Every program has multiple representations, such as source, documentation, bytecode, and makefiles. A GenVoca value is a tuple of program representations. In a product line of parsers, for example, a base parser f is defined by its grammar g_f, Java source s_f, and documentation d_f. Parser f is modeled by the tuple f=[g_f, s_f, d_f]. Each program representation may have subrepresentations, and they too may have subrepresentations, recursively. In general, a GenVoca value is a tuple of nested tuples that define a hierarchy of representations for a particular program.

Hierarchical relationships among program artifacts

Example. Suppose terminal representations are files. In AHEAD, grammar g_f corresponds to a single BNF file, source s_f corresponds to a tuple of Java files [c₁…c_n], and documentation d_f is a tuple of HTML files [h₁…h_k]. A GenVoca value (nested tuples) can be depicted as a directed graph: the graph for parser f is shown in the figure to the right. Arrows denote projections, i.e., mappings from a tuple to one of its components. AHEAD implements tuples as file directories, so f is a directory containing file g_f and subdirectories s_f and d_f. Similarly, directory s_f contains files c₁…c_n, and directory df contains files h₁…h_k.

Note: Files can be hierarchically decomposed further. Each Java class can be decomposed into a tuple of members and other class declarations (e.g., initialization blocks, etc.). The important idea here is that the mathematics of AHEAD are recursive.

Second, AHEAD expresses features as nested tuples of unary functions called deltas. Deltas can be program refinements (semantics-preserving transformations), extensions (semantics-extending transformations), or interactions (semantics-altering transformations). We use the neutral term “delta” to represent all of these possibilities, as each occurs in FOSD.

To illustrate, suppose feature j extends a grammar by Δg_j (new rules and tokens are added), extends source code by Δs_j (new classes and members are added and existing methods are modified), and extends documentation by Δd_j. The tuple of deltas for feature j is modeled by j=[Δg_j,Δs_j,Δd_j], which we call a delta tuple. Elements of delta tuples can themselves be delta tuples. Example: Δs_j represents the changes that are made to each class in s_f by feature j, i.e., Δs_j=[Δc₁…Δc_n]. The representations of a program are computed recursively by nested vector addition. The representations for parser p₂ (whose GenVoca expression is j+f) are:

  p2 = j + f                           -- GenVoca expression
     = [Δgj, Δsj, Δdj] + [gf, sf, df]   -- substitution
     = [Δgj+gf, Δsj+sf, Δdj+df]         -- compose tuples element-wise

That is, the grammar of p₂ is the base grammar composed with its extension (Δg_j+g_f), the source of p₂ is the base source composed with its extension (Δs_j+s_f), and so on. As elements of delta tuples can themselves be delta tuples, composition recurses, e.g., Δs_j+s_f= [Δc₁…Δc_n]+[c₁…c_n]=[Δc₁+c₁…Δc_n+c_n]. Summarizing, GenVoca values are nested tuples of program artifacts, and features are nested delta tuples, where + recursively composes them by vector addition. This is the essence of AHEAD.

The ideas presented above concretely expose two FOSD principles. The Principle of Uniformity states that all program artifacts are treated and modified in the same way. (This is evidenced by deltas for different artifact types above). The Principle of Scalability states all levels of abstractions are treated uniformly. (This gives rise to the hierarchical nesting of tuples above).

The original implementation of AHEAD is the AHEAD Tool Suite and Jak language, which exhibits both the Principles of Uniformity and Scalability. Next-generation tools include CIDE  and FeatureHouse.

FOMDD

Derivational and refinement relationships among program artifacts

Feature-Oriented Model-Driven Design (FOMDD) combines the ideas of AHEAD with Model-Driven Design (MDD) (a.k.a. Model-Driven Architecture (MDA)). AHEAD functions capture the lockstep update of program artifacts when a feature is added to a program. But there are other functional relationships among program artifacts that express derivations. For example, the relationship between a grammar g_f and its parser source s_f is defined by a compiler-compiler tool, e.g., javacc. Similarly, the relationship between Java source s_f and its bytecode b_f is defined by the javac compiler. A commuting diagram expresses these relationships. Objects are program representations, downward arrows are derivations, and horizontal arrows are deltas. The figure to the right shows the commuting diagram for program p₃ = i+j+h = [g₃,s₃,b₃].

A fundamental property of a commuting diagram is that all paths between two objects are equivalent. For example, one way to derive the bytecode b₃ of parser p₃ (lower right object in the figure to the right) from grammar g_h of parser h (upper left object) is to derive the bytecode b_h and refine to b₃, while another way refines g_h to g₃, and then derive b₃, where + represents delta composition and () is function or tool application:

b₃ = Δb_j + Δb_i + javacc( javac( g_h ) ) = javac( javacc( Δg_i + Δg_j + g_h ) )

There are ${\displaystyle (\genfrac{}{}{0ex}{}{4}{2})}$ possible paths to derive the bytecode b₃ of parser p₃ from the grammar g_h of parser h. Each path represents a metaprogram whose execution generates the target object (b₃) from the starting object (g_f). There is a potential optimization: traversing each arrow of a commuting diagram has a cost. The cheapest (i.e., shortest) path between two objects in a commuting diagram is a geodesic, which represents the most efficient metaprogram that produces the target object from a given object.

Note: A “cost metric” need not be a monetary value; cost may be measured in production time, peak or total memory requirements, power consumption, or some informal metric like “ease of explanation”, or a combination of the above (e.g., multi-objective optimization). The idea of a geodesic is general, and should be understood and appreciated from this more general context.

Note: It is possible for there to be m starting objects and n ending objects in a geodesic; when m=1 and n>1, this is the Directed Steiner Tree Problem, which is NP-hard.

Commuting diagrams are important for at least two reasons: (1) there is the possibility of optimizing the generation of artifacts (e.g., geodesics) and (2) they specify different ways of constructing a target object from a starting object. A path through a diagram corresponds to a tool chain: for an FOMDD model to be consistent, it should be proven (or demonstrated through testing) that all tool chains that map one object to another in fact yield equivalent results. If this is not the case, then either there is a bug in one or more of the tools or the FOMDD model is wrong.

Intelligent transportation system

From Wikipedia, the free encyclopedia

(Redirected from Intelligent Transportation System)

ITS graphical user interface displaying the Hungarian highway network and its data points

An 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.

Although ITS may refer to all modes of transport, the directive of the European Union 2010/40/EU, made on July 7, 2010, defined ITS as systems in which information and communication technologies are applied in the field of road transport, including infrastructure, vehicles and users, and in traffic management and mobility management, as well as for interfaces with other modes of transport. ITS may be used to improve the efficiency and safety of transport in a number of situations, i.e. road transport, traffic management, mobility, etc. ITS technology is being adopted across the world to increase capacity of busy roads and reduce journey times.

Background

Governmental activity in the area of ITS is further motivated by an increasing focus on homeland security. Many of the proposed ITS systems also involve surveillance of the roadways, which is a priority of homeland security. Funding of many systems comes either directly through homeland security organisations or with their approval. Further, ITS can play a role in the rapid mass evacuation of people in urban centers after large casualty events such as a result of a natural disaster or threat. Much of the infrastructure and planning involved with ITS parallels the need for homeland security systems.

In the developing world, the migration from rural to urbanized habitats has progressed differently. Many areas of the developing world have urbanised without significant motorisation and the formation of suburbs. A small portion of the population can afford automobiles, but the automobiles greatly increase congestion in these multimodal transportation systems. They also produce considerable air pollution, pose a significant safety risk, and exacerbate feelings of inequities in the society. High population density could be supported by a multimodal system of walking, bicycle transportation, motorcycles, buses, and trains.

Other parts of the developing world, such as China, India and Brazil remain largely rural but are rapidly urbanising and industrialising. In these areas a motorised infrastructure is being developed alongside motorisation of the population. Great disparity of wealth means that only a fraction of the population can motorise, and therefore the highly dense multimodal transportation system for the poor is cross-cut by the highly motorised transportation system for the rich.

Intelligent transportation technologies

Intelligent transport systems vary in technologies applied, from basic management systems such as car navigation; traffic signal control systems; container management systems; variable message signs; automatic number plate recognition or speed cameras to monitor applications, such as security CCTV systems, and automatic incident detection or stopped vehicle detection systems; to more advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems; weather information; bridge de-icing (US deicing) systems; and the like. Additionally, predictive techniques are being developed to allow advanced modelling and comparison with historical baseline data. Some of these technologies are described in the following sections.

Wireless communications

Traffic monitoring gantry with wireless communication dish antenna

Various forms of wireless communications technologies have been proposed for intelligent transportation systems. Radio modem communication on UHF and VHF frequencies are widely used for short and long range communication within ITS.

Short-range communications of 350 m can be accomplished using IEEE 802.11 protocols, specifically 802.11p (WAVE) or the dedicated short-range communications (DSRC) 802.11bd standard being promoted by the Intelligent Transportation Society of America and the United States Department of Transportation. Theoretically, the range of these protocols can be extended using mobile ad hoc networks or mesh networking.

Longer range communications use infrastructure networks such as 5G. Long-range communications using these methods are well established, but, unlike the short-range protocols, these methods require extensive and very expensive infrastructure deployment.

Computational technologies

Recent advances in vehicle electronics have led to a move towards fewer, more capable computer processors on a vehicle. A typical vehicle in the early 2000s would have between 20 and 100 individual networked microcontroller/programmable logic controller modules with non-real-time operating systems. The current trend is toward fewer, more costly microprocessor modules with hardware memory management and real-time operating systems. The new embedded system platforms allow for more sophisticated software applications to be implemented, including model-based process control, artificial intelligence, and ubiquitous computing. Perhaps the most important of these for intelligent transportation systems is artificial intelligence.

Floating car data/floating cellular data

Main article: Floating car data

RFID E-ZPass reader attached to the pole and its antenna (right) used in traffic monitoring in New York City by using vehicle re-identification method

"Floating car" or "probe" data collected other transport routes. Broadly speaking, four methods have been used to obtain the raw data:

• Triangulation method. In developed countries a high proportion of cars contain one or more mobile phones. The phones periodically transmit their presence information to the mobile phone network, even when no voice connection is established. In the mid-2000s, attempts were made to use mobile phones as anonymous traffic probes. As a car moves, so does the signal of any mobile phones that are inside the vehicle. By measuring and analysing network data using triangulation, pattern matching or cell-sector statistics (in an anonymous format), the data was converted into traffic flow information. With more congestion, there are more cars, more phones, and thus, more probes.

In metropolitan areas, the distance between antennas is shorter and in theory accuracy increases. An advantage of this method is that no infrastructure needs to be built along the road; only the mobile phone network is leveraged. But in practice the triangulation method can be complicated, especially in areas where the same mobile phone towers serve two or more parallel routes (such as a motorway (freeway) with a frontage road, a motorway (freeway) and a commuter rail line, two or more parallel streets, or a street that is also a bus line). By the early 2010s, the popularity of the triangulation method was declining.

• Vehicle re-identification. Vehicle re-identification methods require sets of detectors mounted along the road. In this technique, a unique serial number for a device in the vehicle is detected at one location and then detected again (re-identified) further down the road. Travel times and speed are calculated by comparing the time at which a specific device is detected by pairs of sensors. This can be done using the MAC addresses from Bluetooth or other devices, or using the RFID serial numbers from electronic toll collection (ETC) transponders (also called "toll tags").
• GPS based methods. An increasing number of vehicles are equipped with in-vehicle satnav/GPS (satellite navigation) systems that have two-way communication with a traffic data provider. Position readings from these vehicles are used to compute vehicle speeds. Modern methods may not use dedicated hardware but instead Smartphone based solutions using so called Telematics 2.0 approaches.
• Smartphone-based rich monitoring. Smartphones having various sensors can be used to track traffic speed and density. The accelerometer data from smartphones used by car drivers is monitored to find out traffic speed and road quality. Audio data and GPS tagging of smartphones enables identification of traffic density and possible traffic jams. This was implemented in Bangalore, India as a part of a research experimental system Nericell.

Floating car data technology provides advantages over other methods of traffic measurement:

• Less expensive than sensors or cameras
• More coverage (potentially including all locations and streets)
• Faster to set up and less maintenance
• Works in all weather conditions, including heavy rain

Sensing

An active RFID tag used for electronic toll collection

Technological advances in telecommunications and information technology, coupled with ultramodern/state-of-the-art microchip, RFID (Radio Frequency Identification), and inexpensive intelligent beacon sensing technologies, have enhanced the technical capabilities that will facilitate motorist safety benefits for intelligent transportation systems globally. Sensing systems for ITS are vehicle- and infrastructure-based networked systems, i.e., intelligent vehicle technologies. Infrastructure sensors are indestructible (such as in-road reflectors) devices that are installed or embedded in the road or surrounding the road (e.g., on buildings, posts, and signs), as required, and may be manually disseminated during preventive road construction maintenance or by sensor injection machinery for rapid deployment. Vehicle-sensing systems include deployment of infrastructure-to-vehicle and vehicle-to-infrastructure electronic beacons for identification communications and may also employ video automatic number plate recognition or vehicle magnetic signature detection technologies at desired intervals to increase sustained monitoring of vehicles operating in critical zones of world.

Inductive loop detection

Saw cut loop detectors for vehicle detection buried in the pavement at this intersection as seen by the rectangular shapes of loop detector sealant at the bottom part of this picture

Inductive loops can be placed in a roadbed to detect vehicles as they pass through the loop's magnetic field. The simplest detectors simply count the number of vehicles during a unit of time (typically 60 seconds in the United States) that pass over the loop, while more sophisticated sensors estimate the speed, length, and class of vehicles and the distance between them. Loops can be placed in a single lane or across multiple lanes, and they work with very slow or stopped vehicles as well as vehicles moving at high speed.

Video vehicle detection

Traffic-flow measurement and automatic incident detection using video cameras is another form of vehicle detection. Since video detection systems such as those used in automatic number plate recognition do not involve installing any components directly into the road surface or roadbed, this type of system is known as a "non-intrusive" method of traffic detection. Video from cameras is fed into processors that analyse the changing characteristics of the video image as vehicles pass. The cameras are typically mounted on poles or structures above or adjacent to the roadway. Most video detection systems require some initial configuration to "teach" the processor the baseline background image. This usually involves inputting known measurements such as the distance between lane lines or the height of the camera above the roadway. A single video detection processor can detect traffic simultaneously from one to eight cameras, depending on the brand and model. The typical output from a video detection system is lane-by-lane vehicle speeds, counts, and lane occupancy readings. Some systems provide additional outputs including gap, headway, stopped-vehicle detection, and wrong-way vehicle alarms.

Bluetooth detection

Bluetooth is an accurate and inexpensive way to transmit position from a vehicle in motion. Bluetooth devices in passing vehicles are detected by sensing devices along the road. If these sensors are interconnected they are able to calculate travel time and provide data for origin and destination matrices. Compared to other traffic measurement technologies, Bluetooth measurement has some differences:

• Accurate measurement points with absolute confirmation to provide to the second travel times.
• Is non-intrusive, which can lead to lower-cost installations for both permanent and temporary sites.
• Is limited to how many Bluetooth devices are broadcasting in a vehicle so counting and other applications are limited.
• Systems are generally quick to set up with little to no calibration needed.

Since Bluetooth devices become more prevalent on board vehicles and with more portable electronics broadcasting, the amount of data collected over time becomes more accurate and valuable for travel time and estimation purposes, more information can be found in.

It is also possible to measure traffic density on a road using the audio signal that consists of the cumulative sound from tire noise, engine noise, engine-idling noise, honks and air turbulence noise. A roadside-installed microphone picks up the audio that comprises the various vehicle noise and audio signal processing techniques can be used to estimate the traffic state. The accuracy of such a system compares well with the other methods described above.

Radar detection

Radars are mounted on the side of the road to measure traffic flow and for stopped and stranded vehicle detection purposes. Like video systems, radar learns its environment during set up so can distinguish between vehicles and other objects. It can also operate in conditions of low visibility. Traffic flow radar uses a "side-fire" technique to look across all traffic lanes in a narrow band to count the number of passing vehicles and estimate traffic density. For stopped vehicle detection (SVD) and automatic incident detection, 360 degree radar systems are used as they scan all lanes along large stretches of road. Radar is reported to have better performance over longer ranges than other technologies. SVD radar will be installed on all Smart motorways in the UK.

Information fusion from multiple traffic sensing modalities

The data from the different sensing technologies can be combined in intelligent ways to determine the traffic state accurately. A data fusion based approach that utilizes the road side collected acoustic, image and sensor data has been shown to combine the advantages of the different individual methods.

Intelligent transportation applications

Emergency vehicle notification systems

In 2015, the EU passed a law required automobile manufacturers to equip all new cars with eCall, a European initiative that assists motorists in the case of a collision. The in-vehicle eCall is generated either manually by the vehicle occupants or automatically via activation of in-vehicle sensors after an accident. When activated, the in-vehicle eCall device will establish an emergency call carrying both voice and data directly to the nearest emergency point (normally the nearest E1-1-2 public safety answering point, PSAP). The voice call enables the vehicle occupant to communicate with the trained eCall operator. At the same time, a minimum set of data will be sent to the eCall operator receiving the voice call.

The minimum set of data contains information about the incident, including time, precise location, the direction the vehicle was traveling, and vehicle identification. The pan-European eCall aims to be operative for all new type-approved vehicles as a standard option. Depending on the manufacturer of the eCall system, it could be mobile phone based (Bluetooth connection to an in-vehicle interface), an integrated eCall device, or a functionality of a broader system like navigation, Telematics device, or tolling device. eCall is expected to be offered, at earliest, by the end of 2010, pending standardization by the European Telecommunications Standards Institute and commitment from large EU member states such as France and the United Kingdom.

Congestion pricing gantry at North Bridge Road, Singapore

The EC funded project SafeTRIP is developing an open ITS system that will improve road safety and provide a resilient communication through the use of S-band satellite communication. Such platform will allow for greater coverage of the Emergency Call Service within the EU.

Automatic road enforcement

Main article: Traffic enforcement camera

Automatic speed enforcement gantry or lombada eletrônica with ground sensors at Brasilia, D.F.

A traffic enforcement camera system, consisting of a camera and a vehicle-monitoring device, is used to detect and identify vehicles disobeying a speed limit or some other road legal requirement and automatically ticket offenders based on the license plate number. Traffic tickets are sent by mail. Applications include:

• Speed cameras that identify vehicles traveling over the legal speed limit. Many such devices use radar to detect a vehicle's speed or electromagnetic loops buried in each lane of the road.
• Red light cameras that detect vehicles that cross a stop line or designated stopping place while a red traffic light is showing.
• Bus lane cameras that identify vehicles traveling in lanes reserved for buses. In some jurisdictions, bus lanes can also be used by taxis or vehicles engaged in car pooling.
• Level crossing cameras that identify vehicles crossing railways at grade illegally.
• Double white line cameras that identify vehicles crossing these lines.
• High-occupancy vehicle lane cameras that identify vehicles violating HOV requirements.

Variable speed limits

Further information: Speed limit § Variable speed limits

Example variable speed limit sign in the United States

Recently some jurisdictions have begun experimenting with variable speed limits that change with road congestion and other factors. Typically such speed limits only change to decline during poor conditions, rather than being improved in good ones. One example is on Britain's M25 motorway, which circumnavigates London. On the most heavily traveled 14-mile (23 km) section (junction 10 to 16) of the M25 variable speed limits combined with automated enforcement have been in force since 1995. Initial results indicated savings in journey times, smoother-flowing traffic, and a fall in the number of accidents, so the implementation was made permanent in 1997. Further trials on the M25 have been thus far proven inconclusive.

Collision avoidance systems

Japan has installed sensors on its highways to notify motorists that a car is stalled ahead.

Cooperative systems on the road

Communication cooperation on the road includes car-to-car, car-to-infrastructure, and vice versa. Data available from vehicles are acquired and transmitted to a server for central fusion and processing. These data can be used to detect events such as rain (wiper activity) and congestion (frequent braking activities). The server processes a driving recommendation dedicated to a single or a specific group of drivers and transmits it wirelessly to vehicles. The goal of cooperative systems is to use and plan communication and sensor infrastructure to increase road safety. The definition of cooperative systems in road traffic is according to the European Commission:

"Road operators, infrastructure, vehicles, their drivers and other road users will cooperate to deliver the most efficient, safe, secure and comfortable journey. The vehicle-vehicle and vehicle-infrastructure co-operative systems will contribute to these objectives beyond the improvements achievable with stand-alone systems."

World Congress on Intelligent Transport Systems (ITS World Congress) is an annual trade show to promote ITS technologies. ERTICO– ITS Europe, ITS America and ITS AsiaPacific sponsor the annual ITS World Congress and exhibition. Each year the event takes place in a different region (Europe, Americas or Asia-Pacific). The first ITS World Congress was held in Paris in 1994.

Smart transportation – new business models

New mobility and smart transportation models are emerging globally. Bike sharing, car sharing and scooter sharing schemes like Lime or Bird are continuing to gain popularity; electric vehicle charging schemes are taking off in many cities; the connected car is a growing market segment; while new, smart parking solutions are being used by commuters and shoppers all over the world. All these new models provide opportunities for solving last mile issues in urban areas.

ITS in the connected world

Mobile operators are becoming a significant player in these value chains (beyond providing just connectivity). Dedicated apps can be used to take mobile payments, provide data insights and navigation tools, offer incentives and discounts, and act as a digital commerce medium.

Payments and billing flexibility

These new mobility models call for high monetization agility and partner management capabilities. A flexible settlements and billing platform enables revenues to be shared quickly and easily and provides an overall better customer experience. As well as a better service, users can also be rewarded by discounts, loyalty points and rewards, and engaged via direct marketing.

Europe

The Network of National ITS Associations is a grouping of national ITS interests. It was officially announced 7 October 2004 in London. The secretariat is at ERTICO – ITS Europe.

ERTICO – ITS Europe is a public/private partnership promoting the development and deployment of ITS. They connect public authorities, industry players, infrastructure operators, users, national ITS associations and other organisations together. The ERTICO work programme focuses on initiatives to improve transport safety, security and network efficiency whilst taking into account measures to reduce environmental impact.

United States

In the United States, each state has an ITS chapter that holds a yearly conference to promote and showcase ITS technologies and ideas. Representatives from each Department of Transportation (state, cities, towns, and counties) within the state attend this conference.

Latin America

Colombia

In the intermediate cities of Colombia, where the Strategic Public Transportation Systems are implemented, the urban transportation networks must operate under parameters that improve the quality of service provision. Several of the challenges faced by the transportation systems in these cities are aimed at increasing the number of passengers transported in the system and the technological adoption that must be integrated for the management and control of public transportation fleets. Achieving this requires strategic systems to integrate solutions based on intelligent transportation systems and information and communication technologies to optimize fleet control and management, electronic fare collection, road safety, and the delivery of information to users. The functionalities to be covered by the technology in these transportation systems include: fleet scheduling; vehicle location and traceability; cloud storage of operational data; interoperability with other information systems; centralization of operations; passenger counting; data control and visualization.