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. 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 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 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 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
tyre 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 roadside collected acoustic, image and sensor data has been shown to combine the advantages of the different individual methods. ==Intelligent transportation applications==