Although the problem was efficiently solved for one object, the method is not applicable to a multiple-object environment, because all the robots need to detect and track the same object simultaneously. The main drawback of these methods, intended to detect and track a single object by its simultaneous observation by several robots, is that they cannot be extrapolated to detect and track multiple objects.The problem of simultaneously tracking several objects has been addressed in the work of Chau et al. [26], in which multiple object tracking is achieved by using a multiple features similarity methodology comparing color images. Multiple object tracking using multiple cameras for surveillance applications has been addressed by Kachhava et al. [27].
A procedure for tracking multiple walkers with multiple robots equipped with 2D LIDAR sensors has been recently proposed by Tsokas et al. [28].Another possibility for tracking multiple targets would be the use of particle filters [29,30] to combine observations from multiple robots, increasing in that way the quality of the tracking. This technique shows several advantages over other estimators; it is certainly well suited to accommodate the types of uncertainty that arise in the distributed surveillance scenario and allows for estimating future states. Nevertheless, although the previously referred solutions show an important reduction in the bandwidth required by reducing the number of particl
Over the past decades, sensor manufacturers have developed various technologies for vehicle detection (see e.g., [1]).
It is common to separate vehicle detection sensors into two categories based on their installation position relative to the pavement: (i) in-roadway sensors; and (ii) over-roadway sensors.In-roadway sensors are embedded in the pavement layers or the subgrade. The main types of in-roadway sensors are the inductive loop detectors, piezoelectric sensors, magnetometers and other type of detectors. Because these sensors are installed in the traffic lanes, vehicle must pass over them in order to be detected. The installation and maintenance of such devices, therefore, requires lane or road closure, effectively stopping or impeding traffic flow. The operational conditions of in-roadway sensors can be degraded with pavement deterioration, improper installation and weather-related effects, and may be damaged by street and utility repairs.
As a result, in-roadway sensor technologies require effective and careful installation, testing, and repair [2].Over-roadway sensors are mounted either alongside or above the traffic lanes. Video detection systems, active and passive infrared, microwave radar, Dacomitinib ultrasonic, and passive acoustic sensors belong to this category [3]. Video cameras are commonly mounted on tall poles or on traffic signal mast arms above the road. Other over-roadway sensors are installed at lower heights alongside the road.