Vehicle Cardinality Estimation in VANETs by Using RFID Tag Estimator

Abstract

Nowadays, many vehicles equipped with RFID-enabled chipsets traverse the Electronic Toll Collection (ETC) systems. Here, we present a scheme to estimate the vehicle cardinality with high accuracy and efficiency. A unique RFID tag is attached to a vehicle, so we identify vehicles through RFID tags. With RFID signal, the location of vehicles can be detected remotely. Our scheme makes the vehicle cardinality estimation based on the location distance of the first vehicle and the second vehicle. Specifically, it derives the relationship between the distance and the number of vehicles. Then, it deduces the optimal parameter settings under certain requirement. According to the actual estimated traffic flow, we put forward a mechanism to improve the estimation efficiency. Conducting extensive experiments, the presented scheme is proven to be outstanding in two aspects. One is the deviation rate of our model is 50% of FNEB algorithm that is the classical scheme. The other is our efficiency is 1.5 times higher than that of FNEB algorithm. Keywords: Vehicle Estimation, VANETs, RFID tag, Privacy Preservation IntroductionThe automobile popularity provides much convenience for people, together with significant serious traffic problems , the traffic manager can evaluate the traffic situation through estimating the number of vehicles and thus make more effective traffic management. Meanwhile, the drivers can access current traffic situation to adjust more effective transportation plan in time.