A comparing analysis of traffic monitoring systems

The measurement of traffic data can be made with sensors, detectors and other various techniques with differences due to their applications, performance and costs, being these last related mainly to purchase, installation and maintenance.

At present, the main available instruments can be classified in the following typologies:

a) Pneumatic instruments (traditional)
b) Inductive loops or inductive loop detectors
c) Magnetometers or magnetic sensors
d) Piezoelectric sensors
e) Microwave detectors
f) Infrared detectors
g) Ultrasound detectors or ultrasonic sensors
h) Passive acoustic array sensors
i) Video detection systems.

Two primary categories of these technologies can be distinguished: intrusive and nonintrusive. Monitoring sensors and detectors listed as a, b, c and d are typically intrusive to install above or inside the road surface, while the others are usually non-intrusive so they do not require disrupting the traffic flow during installation and maintenance operations. A differentiation in their applications can consist of the characteristics of the flow that has to be measured and the features of the place where they need to be installed, as well as specific project requirements. It is possible to identify high or low volume scenarios, high or low velocity scenarios, among which also situations of accidents, at certain conditions.

Pneumatic instruments

The pneumatic road tube was the first intrusive traffic detector that was used and is still employed today, generally for the short-term counting of the traffic flow thanks to its simplicity and low cost. These detectors must be installed on the road surface, perpendicularly to the traffic flow direction (see Figure 1). When the axles of a vehicle pass over a tube, a burst of air pressure takes place along it, and this pulse of air closes an air switch, producing thereafter an electrical signal that has to be transmitted to an analysis system.

Figure 1 Road tube configurations for single and multilane highways

Inductive loop detectors

The inductive loop detector (ILD) is probably the most common sensor used in traffic control and management applications around the world. The ILD consists of one or more turns of an insulated wire laid out in, for example, 1.8m / 6-foot diameter circles or even wider rectangles of variable length (see Figure 2). The square or rectangular loops are usually easier to install on the ground than the circular ones, so they are the most common, even if the optimal shape of a loop would be circular.

Figure 2 Examples for inductive loops, applied on a motorway (Munich, Germany) and close to the entrance of a road tunnel (Mont Blanc/Monte Bianco, between Italy and France)

In various applications, we may distinguish three kinds of loop detectors: saw cut, trenchedin and preformed. In the first case, the loops are buried in a shallow saw-cut in the roadway, the trenched-in loops are installed below the pavement, and the preformed loops are not imbedded in the pavement but put above, enclosed in a special pipe (for example PVC) in order to protect them.

Inductive-loop traffic detector systems operate by sensing disturbances to the electromagnetic field over a coil of wire built into the roadway (see Figure 2).

The accuracy of the inductive loop may vary according to stop-and-go phenomena occurring on the pavement and, in particular cases, with environmental conditions. Adjusting sensitivity on the loop amplifier can affect the loop speed accuracy. A main drawback of this technology is the disruption of the traffic during the operation of installation and maintenance.

Magnetic sensors

Magnetic sensors measure the disruption in the earth’s magnetic field caused by the presence of a metal mass, like that of a vehicle. Many magnetic sensors have often been used in place of inductive loops on bridge decks, where ILDs cannot be installed, and in heavily reinforced pavement. More recently they are applied in little cylinders (see Figure 3) for wireless sensor networks (WSN). The WSN paradigm consists in a large ensemble of heterogeneous, battery or self-powered sensors, interconnected to one another by means of wireless technology. The use of such interconnected wireless devices generates a widely and densely deployed infrastructure of sensors which collect information about the utilisation of the road surface by the vehicles, their number and speed (couples of sensors), as well as the environment conditions, in case they are equipped with thermometers, hygrometers and the like.

Figure 3 Example of a magnetic sensor belonging to the wireless sensor network of a logistic centre (freight village ‘Interporto di Torino’, Italy).

Two types of magnetic field sensors are normally used for traffic flow parameter measurement. The first one, the two-axis fluxgate magnetometer, detects changes in the vertical and horizontal components of the earth’s magnetic field. Fluxgate magnetometers operated in the pulse output mode sense the passage of a vehicle, yielding count data. When operated in the presence output mode, magnetometers give a continuous output as long as a vehicle occupies the detection zone, thus measures vehicle presence (see Figure 4).

Figure 4 Example of a fluxgate magnetometer

The second type of magnetic field sensor detects perturbations in the earth’s magnetic field produced when a moving vehicle passes over the detection zone (see Figure 5). These magnetic sensors are induction magnetometers; most of them cannot detect stopped vehicles nor provide presence measurements because motion is required for the sensor to produce an output signal.

Figure 5 Example of a magnetic field sensor

Piezoelectric sensors

When the axle of a vehicle passes over a piezoelectric sensor, it generates a voltage by causing electrical charges of opposite polarity to appear at the parallel faces of the piezoelectric crystalline material. The measured voltage is proportional to the force or weight of the vehicle. As the piezoelectric effect is dynamic, the initial charge will decay if the force remains constant.

The adoption of this kind of detection system (called Weigh In Motion, WIM; see Figure 6) enables to acquire information on the typology of the vehicles (load axles, overall weight, wheel track) which, mated to the more conventional ones (traffic flows, occupation rates, headways or distance between the vehicles, speed and length of the vehicles themselves) result to be essential not only for more complete information on the traffic and different flow modalities, but are also functional to new strategies for the right management of the road infrastructures: maintenance, safety in circulation and reduction of the polluting agents.

Figure 6 Piezoelectric instruments: the installation of a quartz-based sensor close to an intermodal terminal for weighing heavyduty vehicles in motion (at the ‘Interporto di Torino’, Italy)

Microwave radar detectors

Two main types of microwave detectors may be distinguished: Doppler Microwave Detectors and Frequency Modulated Continuous Wave (FMCW) Detectors.

The Doppler principle is used to calculate vehicle speed from continuous wave (CW) microwave radar that transmits electromagnetic energy at a constant frequency, as shown in Figure 7.

Figure 7Waveforms used with microwave traffic sensors

Vehicle speed is proportional to the change in frequency between the received and transmitted signals, thus is determined by measuring the frequency change. The passage of a vehicle produces a frequency shift. Because only moving vehicles are detected by a CW Doppler radar, vehicle presence cannot be measured with this waveform but it can only detect volume, occupancy, classification and speed.

FMCW detectors, sometimes referred to as true-presence microwave detectors, transmit continuous frequency-modulated waves at the detection zone and can detect both speed and presence. As shown in Figure 7 opposite (bottom graph), the presence of a vehicle is determined by measuring the change in range that occurs when a vehicle enters the field of view of the radar.

The size of the radar beam projected on the road surface, called a footprint, and mounting geometry are varied to monitor single or multiple lanes of traffic (see Figure 8).

Figure 8 Example of possible applications of microwave systems

Forward-looking wide beam radars permit more than one lane of traffic flowing in one direction to be monitored. Forward-looking narrow beam radars monitor a single lane of traffic flowing in one direction.

Infrared detectors

Infrared detectors or sensors can operate either in active or in passive mode. In the active mode, detection zones are illuminated with infrared energy transmitted from laser diodes operating in the near infrared spectrum (see Figure 9). A portion of the transmitted energy is reflected by vehicles travelling through the zones.

Figure 9 Active infrared sensors: a scheme

Vehicle speed is measured by using two fixed beams, one pointed slightly ahead of the other. The vehicle may be also classified by using an algorithm that compares the profile of the vehicle against stored profiles for various vehicle classes.

Passive sensors do not transmit energy; rather, they detect the energy that is emitted or reflected from vehicles, road surfaces and other objects in the field of view and from the atmosphere. When a vehicle enters the field of view of a sensor, a signal is generated, proportional to the product of an emissivity difference term and a temperature difference term, assuming the surface temperatures of the vehicle and roads are equal.

Ultrasonic sensors

Ultrasonic sensors transmit pressure waves of sound energy at frequencies typically between 25 and 50 KHz, which are above the human audible range. Most ultrasonic sensors operate with pulse-waveforms, such as those shown in Figure 10, and they may provide vehicle count, presence and occupancy information.

Pulse-waveforms are used to measure distances to the road surface and vehicle surface by detecting the portion of the transmitted energy that is reflected towards the sensor. When a distance other than that to the background road surface is measured, the sensor interprets that measurement as the presence of a vehicle.

Figure 10 Pulse-waveform as used in an ultrasonic traffic sensor

Acoustic sensors

Acoustic sensors measure vehicle flow rate, occupancy and speed by detecting acoustic energy in the form of audible sounds. The sounds are produced from a variety of sources within each vehicle and from the interaction of tires with the road. When a vehicle passes through the detection zone, a signal-processing algorithm recognises an increase in sound energy and generates a vehicle presence signal. When the vehicle leaves the detection zone, the sound energy level drops below the detection threshold and the vehicle presence signal is terminated.

Video image processor and video detection systems

Video image processors (VIP) detect vehicles by analysing video images to determine changes between successive frames. A VIP system typically consists of one or more cameras, a microprocessor-based computer for digitising and processing the video imagery and software for interpreting the images and converting them into traffic flow data. The image processing algorithms in the computer analyse the variation of grey levels in groups of pixels contained in the video image frames (see Figure 11). By filtering out grey level variations resulting from weather conditions, shadows and daytime or night-time artefacts, the image background can be removed and the objects identified as automobiles, trucks, motorcycles and bicycles retained. By analysing successive video frames, the VIP is able to calculate traffic flow information.

Figure 11Video image processing (‘ITS’ e-learning platform, Politecnico di Torino)

Video detection systems can be deployed to view upstream or downstream traffic. The primary advantage of upstream viewing is that incidents are not blocked by the resultant traffic queues. However, tall vehicles such as trucks may block the line of sight and headlights may cause blooming of the imagery at night. With upstream viewing, headlight beams can be detected as vehicles in adjacent lanes on curved road sections. Downstream viewing conceals cameras mounted on overpasses so that driver behaviour is not altered. Downstream viewing also makes vehicle identification easier at night through the information available in the taillights and enhances track initiation because vehicles are first detected when close to camera.

Summary of technologies and systems for vehicle counting and traffic monitoring

Sensors should be selected based on the particular requirements of the application and the maturity of the measurement technology at the time the system is specified and designed.

Most overhead sensors are compact and not roadway-invasive, making installation and maintenance relatively easy. All of these technologies are mature with respect to traffic management applications, although some may not provide the data required for a specific application or may not be accurate enough. Others, such as video image processing, are continuing to evolve, with new capabilities being added to measure additional traffic parameters, track vehicles or link data among the available cameras.

No single detection technology can be considered the most suitable for all applications: each one may have good performance or some limits, depending on various factors and a successful application of a detection system largely depends on proper matching between the established requirements and the tech – nology selection.

Useful References

1. Dalla Chiara B., “Telematica per i Trasporti”, ISBN: 978-88-8482-339-7, 176 pp., Ed. EGAF, Marzo 2010

2. Klein L .A., Sensor technologies and data requirements for ITS, Artech House, ISBN: 1-58053-077-X, 2001

3. Martin P.T., Feng Y.,Wang X., Detector technology evaluation, Department of Civil and Environmental Engineering, University of Utah, Traffic Lab, 2003

4. Mussone L., Deflorio F. P., Mascia M., “Potenzialità di sistemi di monitoraggio veicolare basati su Floating Car Data”, T&T Trasporti e Trazione, pp. 51-59, 2001, Vol. Aprile 2001, ISSN: 1120-8732

5. Ozbay K., Ozguven E. E. Tolga S., Manual of guidelines for inspection of ITS equipment and facilities, Final report, September 2008