# Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments
## 1 Introduction  
Road maintenance companies keep a record of the location and date of installation of all the traffic signs placed on the roadways, which helps to determine which of them have to be replaced for age reasons, as well as to plan the installation of new traffic sign infrastructure. These records soon become out of date because a large number of traffic signs disappear annually due to accidents or acts of vandalism. To keep the inventory system updated, traffic routes are regularly inspected by vehicles equipped with video cameras. Traditionally, the detection of the traffic signs in the images has been performed offline by human operators, which is expensive and time-consuming. Computer-based traffic sign detection and recognition seems to be an interesting alternative that has been widely used for applications such as speed control [1] or detection of road intersections [2] and lanes [3]. However, its performance can be degraded when the signs are partially hidden, as often occurs with urban facilities [4], or if the quality of the images is poor, which happens, for example, when the weather is adverse or in conditions of darkness [5]. Therefore, recent research has been proposed to overcome these limitations, by proposing novel approaches, such as those based on 3D recognition and location of traffic signs [6], redundant multiple-view architectures combining 2D and 3D techniques [7],or by collecting information from databases such as Google Street View with location purposes [8]. These approaches have also contributed to automatize all the inventory process and reduce the need for manual assessments of the captured images, thus reducing the post-processing times and costs, as well as the sensitivity to human errors, increasing the number of inspections that can be performed. However, even though accurate detection has been reported (94.63% in [8]), the computational burden of image-processing approaches still remains as a limiting factor, especially when implementing the most novel and accurate techniques, such as 3D reconstruction algorithms [6]. Furthermore, note that the inspection vehicle usually travels at a low speed, around 60 Km/h on roadways, because it also has to measure the camber of the road and other parameters. Therefore, to prevent affecting the traffic flow, it would be desirable to conduct the inspections at right; however, this is hardly compatible with capturing accurate images, which are detected at day in the previously referenced works [6; 7; 8]. The alternative to video-based inventory systems may be based on radio-frequency identification (RFID) technology. Basically, it requires placing a RFID tag at each traffic sign or urban facility, and a RFID reader in the inspection vehicle, whose purpose is to scan for RFID tags in its coverage area. RFID is a mature technology that is successfully used in many industries to track and manage goods and merchandise, while avoiding the inherent disadvantages of video-based systems. More specifically, the last decade has witnessed a flurry of research for applying RFID technology to the development of smart roads, incorporating RFID to traffic management applications. For example, the use of RFID for electronic toll collection at highways, for access control systems of vehicles in parking lots, to control traffic congestion, or to restrict traffic in designated areas in cities are well-known. A summary of different RFID based recent approaches for road applications is listed in Table 1.  
In particular, RFID technology has been proposed to traffic sign detection in the last decade [9; 10; 11; 12; 24], as part of the new-generation driving-aid systems. Specifically, [9] presents an advanced driver-assistance system (ADAS) in which in-pavement passive RFID tags transmit information about the road conditions (speed limits, curve warnings,...) to the passing vehicles, which can automatically adapt their speed in response.