Vehicle Cardinality Estimation in VANETs by Using RFID Tag Estimator

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 can identify vehicles through RFID tags. With RFID signal, the location of vehicles can be detected remotely. Our scheme makes vehicle cardinality estimation based on the location distance between the first vehicle and second vehicle. Specifically, it derives the relationship between the distance and number of vehicles. Then, it deduces the optimal parameter settings used in the estimation model 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, which is the classical scheme. The other is our efficiency is 1.5 times higher than that of FNEB algorithm.