Intelligent transportation system


An intelligent transportation system is an advanced application that aims to provide 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 many situations, i.e. road transport, traffic management, mobility, etc. ITS technology is being adopted across the world to increase the capacity of busy roads, reduce journey times and enable the collection of information on unsuspecting road users.

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 centres 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 incorporate a wide range of technologies, from basic management systems such as car navigation, traffic signal control, and variable-message signs, to more advanced, interconnected applications. These technologies can be broadly categorized into several key areas:
A foundational component of modern operations is the use of telematics systems, with GPS devices
  • Monitoring and Enforcement Systems: This category includes technologies like automatic number plate recognition, speed cameras, and security CCTV systems used for traffic monitoring and law enforcement.
  • Data Collection and Analysis Systems: These systems gather and process information from various sources. Examples include parking guidance and information systems and Road Weather Information Systems. A major application is providing real-time information to passengers, such as predicting the arrival time of public transport. This is achieved by processing data collected from transit vehicles with telematics and GPS tracking units. This data supports vehicle tracking, emergency services like eCall, and usage-based insurance policies. These systems are distinct from in-vehicle infotainment systems, which focus on entertainment and smartphone integration.
  • Management Applications: These applications use ITS data for operational control. Examples include container management and intelligent fleet management systems, which leverage telematics to optimize routes, improve fuel efficiency, and enhance the safety of logistics and public transport fleets.
  • Cooperative Systems: A significant trend in ITS is the development of Cooperative ITS, where vehicles and infrastructure are interconnected. Data is shared through vehicle-to-vehicle and vehicle-to-infrastructure communication. This cooperative data exchange allows for real-time hazard warnings and coordinated traffic flow, enhancing safety and efficiency beyond the capabilities of stand-alone systems.
Additionally, predictive techniques are being developed to allow for advanced modelling and comparison with historical baseline data. Specific technologies are described in more detail in the following sections of this article.

Wireless communications

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 or the dedicated short-range communications 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. 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

"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, 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 with a frontage road, a motorway . 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 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 transponders.
  • GPS based methods. An increasing number of vehicles are equipped with in-vehicle satnav/GPS 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
  • Faster to set up and less maintenance
  • Works in all weather conditions, including heavy rain

    Sensing

Technological advances in telecommunications and information technology, coupled with ultramodern/state-of-the-art microchip, RFID, 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 devices that are installed or embedded in the road or surrounding the road, 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.