Real-time traffic distribution prediction protocol (TDPP) for vehicular networks
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ORIGINAL RESEARCH
Real‑time traffic distribution prediction protocol (TDPP) for vehicular networks Maram Bani Younes1 Received: 27 February 2020 / Accepted: 28 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Over downtown and highway road scenarios several applications have been proposed to enhance the quality of driving trips there. Safety, efficiency and entertainment services are provided to vehicles through several advanced technologies. Many of these applications require accurate investigation of the traffic characteristics and distributions over the area of interest in order to successfully provide the targeted services. To mention a few, path recommendation protocols, traffic light scheduling algorithms and driving assistance techniques need specific, detailed and accurate traffic distribution reports regarding the investigated area of interest. Several traffic prediction and evaluation protocols have been proposed in the literature using historical, visual and wireless connecting technologies to gather the real-time basic traffic data. Accuracy, delay, bandwidth consumption and high cost required equipments are the main challenges of the previous protocols. In this paper, we aim to propose a real-time traffic distribution prediction protocol (TDPP) using the vehicular network technology. The proposed protocol aims to produce accurate traffic evaluation and distribution of the investigated area of interest based on gathering the basic traffic data of some traveling vehicles there. From the experimental results we can infer that the TDPP protocol provides more accurate traffic evaluation in the case that only a few vehicles are equipped with wireless transceivers. Moreover, it requires less bandwidth and time to evaluate the traffic characteristics compared to traditional protocols in this field, since it only processes the basic traffic data of the small selected set of vehicles there. Keywords TDPP · Traffic prediction · VANETs · Road network
1 Introduction Daily drivers can expect the traffic distributions over any road network based on their visual assessments and historical driving experience there. During peak hours, regular daily hours and night hours the traffic distributions are completely different and drivers usually choose their path or trip time based on his/her traffic assessment experience. In some scenarios, un-expected situations such as traffic accidents, irregular events or even new special targeted destination over the investigated area change the traffic distributions there for short or long term. In the presence of the recent advanced technologies and communications, several traffic distribution and evaluation protocols for road networks are introduced in a real-time * Maram Bani Younes [email protected] 1
Computer Science Department, Information Technology Faculty, Philadelphia University, Amman, Jordan
fashion. Thus, these information are provided to drivers and passengers before they leave their starting positions, in order to help them
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