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 50i¾?% of FNEB algorithm, which is the classical scheme. The other is our efficiency is 1.5 times higher than that of FNEB algorithm.

[1]  Jeng-Farn Lee,et al.  PPAS: A privacy preservation authentication scheme for vehicle-to-infrastructure communication networks , 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet).

[2]  Hao Jin,et al.  Intelligent transportation system based on ARM , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[3]  Lin Sun,et al.  The architecture design of a cross-domain context management system , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[4]  Juan C. Velez,et al.  RFID system on electrical substation equipment , 2015, 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC).

[5]  Qiaoling Tong,et al.  Bayesian estimation in dynamic framed slotted ALOHA algorithm for RFID system , 2012, Comput. Math. Appl..

[6]  Lei Shu,et al.  A Novel Two-Tier Cooperative Caching Mechanism for the Optimization of Multi-Attribute Periodic Queries in Wireless Sensor Networks , 2015, Sensors.

[7]  Der-Jiunn Deng,et al.  Optimal Dynamic Framed Slotted ALOHA Based Anti-collision Algorithm for RFID Systems , 2011, Wirel. Pers. Commun..

[8]  Francesca Pianosi,et al.  Global sensitivity analysis using a new approach based on cumulative distribution functions , 2014 .

[9]  Yunhao Liu,et al.  Cardinality Estimation for Large-Scale RFID Systems , 2011, IEEE Trans. Parallel Distributed Syst..

[10]  M. Bolic,et al.  Novel Semi-Passive RFID System for Indoor Localization , 2013, IEEE Sensors Journal.

[11]  Trevor Jackson,et al.  Traffic congestion , 2003, BMJ : British Medical Journal.

[12]  Nai-Wei Lo,et al.  An analysis framework for information loss and privacy leakage on Android applications , 2014, 2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE).

[13]  Frank L. Lewis,et al.  Discrete-Event Shop-Floor Monitoring System in RFID-Enabled Manufacturing , 2014, IEEE Transactions on Industrial Electronics.

[14]  ChunYi Wang,et al.  An Enhanced Dynamic Framed Slotted ALOHA Anti-Collision Method for Mobile RFID Tag Identification , 2011 .

[15]  Jiafu Wan,et al.  IoT sensing framework with inter-cloud computing capability in vehicular networking , 2014, Electron. Commer. Res..

[16]  Yoshitsugu Hayashi,et al.  Strategies and instruments for low-carbon urban transport: An international review on trends and effects , 2013 .

[17]  Anjana Jain,et al.  Higher order statistics for discrete Weibull fading channel: An alternate formulation , 2014, 2014 9th International Conference on Industrial and Information Systems (ICIIS).

[18]  Qian Zhang,et al.  Code-Centric RFID System Based on Software Agent Intelligence , 2010, IEEE Intelligent Systems.

[19]  Bo Sheng,et al.  Counting RFID Tags Efficiently and Anonymously , 2010, 2010 Proceedings IEEE INFOCOM.

[20]  Wolfram Burgard,et al.  An evaluation of the RGB-D SLAM system , 2012, 2012 IEEE International Conference on Robotics and Automation.

[21]  Yu Cong,et al.  Performance Evaluation of RFID Anti-Collision Algorithm with FPGA Implementation , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[22]  C. Subbe,et al.  Predicting speed at traffic lights--the problem with static assessments of frailty. , 2015, Age and ageing.

[23]  Chris H. Q. Ding,et al.  Nonnegative matrix factorization using a robust error function , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[24]  Murat Sincan,et al.  Sensitive quantification of mosaicism using high density SNP arrays and the cumulative distribution function. , 2012, Molecular genetics and metabolism.

[25]  Balachander Krishnamurthy,et al.  Privacy leakage vs . Protection measures : the growing disconnect , 2011 .

[26]  Kiseok Choi,et al.  A privacy data leakage prevention method in P2P networks , 2016, Peer-to-Peer Netw. Appl..

[27]  Shiping Chen,et al.  Efficient missing tag detection in RFID systems , 2011, 2011 Proceedings IEEE INFOCOM.

[28]  Nathan Halko,et al.  Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions , 2009, SIAM Rev..

[29]  Harry M. Markowitz,et al.  Mean-variance approximations to expected utility , 2014, Eur. J. Oper. Res..

[30]  Mo Li,et al.  Towards More Efficient Cardinality Estimation for Large-Scale RFID Systems , 2014, IEEE/ACM Transactions on Networking.

[31]  Alex X. Liu,et al.  Fast and Accurate Estimation of RFID Tags , 2015, IEEE/ACM Transactions on Networking.

[32]  Yanmin Zhu,et al.  A Unified Approach for Fast and Accurate Cardinality Estimation in RFID Systems , 2014, 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems.