Abstract
In recent years, cellular floating vehicle data (CFVD) has been a popular traffic information estimation technique to analyze cellular network data and to provide real-time traffic information with higher coverage and lower cost. Therefore, this study proposes vehicle positioning and speed estimation methods to capture CFVD and to track mobile stations (MS) for intelligent transportation systems (ITS). Three features of CFVD, which include the IDs, sequence, and cell dwell time of connected cells from the signals of MS communication, are extracted and analyzed. The feature of sequence can be used to judge urban road direction, and the feature of cell dwell time can be applied to discriminate proximal urban roads. The experiment results show the accuracy of the proposed vehicle positioning method, which is 100% better than other popular machine learning methods (e.g., naive Bayes classification, decision tree, support vector machine, and back-propagation neural network). Furthermore, the accuracy of the proposed method with all features (i.e., the IDs, sequence, and cell dwell time of connected cells) is 83.81% for speed estimation. Therefore, the proposed methods based on CFVD are suitable for detecting the status of urban road traffic.
Highlights
In the last few years, a technical explosion has revolutionized and supported transportation management and control for intelligent transportation systems (ITS)
A mobile stations (MS) (e.g., HTC (Taoyuan, Taiwan) M8 running the Android 2.2.2platform) is carried in a car to perform call procedures when the car is driven on urban roads, and the cellular network signals of these calls can be captured for the collection of cellular floating vehicle data (CFVD)
This study uses the packages of class [36], e1071 [37], party [38], and neuralnet [39] to implement kNN, NB, DT, SVM, and BPNN algorithms, respectively
Summary
In the last few years, a technical explosion has revolutionized and supported transportation management and control for intelligent transportation systems (ITS). ITS can estimate and obtain traffic information (e.g., traffic flow, traffic density, and vehicle speed) to road users and managers for the improvement of service levels of the road network. The traffic information can be collected and estimated by three approaches, which include: (1) vehicle detection (VD) [1,2,3]; (2) global positioning system (GPS)-equipped probe car reporting [4,5,6,7]; and (3) cellular floating vehicle data (CFVD) [8]. Collecting traffic information using CFVD is economic and low cost
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
