scholarly journals Research about the construction of intelligent transportation system under the big data of vehicle networking

2019 ◽  
Vol 688 ◽  
pp. 022011
Author(s):  
Hongyang Su
Keyword(s):  
Big Data ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Vehicle Networking

scholarly journals Model Study for Intelligent Transportation System with Big Data

2017 ◽  
Vol 107 ◽  
pp. 418-426 ◽  
Author(s):  
Jiang Zeyu ◽  
Yu Shuiping ◽  
Zhou Mingduan ◽  
Chen Yongqiang ◽  
Liu Yi
Keyword(s):  
Big Data ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Model Study

scholarly journals Deep Intelligent Prediction Network: A Novel Deep Learning Based Prediction Model on Spatiotemporal Characteristics and Location Based Services for Big Data Driven Intelligent Transportation System

2019 ◽  
Vol 8 (11) ◽  
pp. 845-849
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Recommendation System ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Location Based Services ◽  
Traffic Data ◽  
Spatiotemporal Characteristics

The concept of big Data for intelligent transportation system has been employed for traffic management on dealing with dynamic traffic environments. Big data analytics helps to cope with large amount of storage and computing resources required to use mass traffic data effectively. However these traditional solutions brings us unprecedented opportunities to manage transportation data but it is inefficient for building the next-generation intelligent transportation systems as Traffic data exploring in velocity and volume on various characteristics. In this article, a new deep intelligent prediction network has been introduced that is hierarchical and operates with spatiotemporal characteristics and location based service on utilizing the Sensor and GPS data of the vehicle in the real time. The proposed model employs deep learning architecture to predict potential road clusters for passengers. It is injected as recommendation system to passenger in terms of mobile apps and hardware equipment employment on the vehicle incorporating location based services models to seek available parking slots, traffic free roads and shortest path for reach destination and other services in the specified path etc. The underlying the traffic data is classified into clusters with extracting set of features on it. The deep behavioural network processes the traffic data in terms of spatiotemporal characteristics to generate the traffic forecasting information, vehicle detection, autonomous driving and driving behaviours. In addition, markov model is embedded to discover the hidden features .The experimental results demonstrates that proposed approaches achieves better results against state of art approaches on the performance measures named as precision, execution time, feasibility and efficiency.

TRADING: Traffic Aware Data Offloading for Big Data Enabled Intelligent Transportation System

2020 ◽  
Vol 69 (7) ◽  
pp. 6869-6879
Author(s):  
Tasneem S. J. Darwish ◽  
Kamalrulnizam Abu Bakar ◽  
Omprakash Kaiwartya ◽  
Jaime Lloret
Keyword(s):  
Big Data ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Data Offloading

scholarly journals Traffic Big Data in the Development of Intelligent Transportation System

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Qiang Shi ◽  
Lei Wang ◽  
Taojie Wang
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Paper Briefly ◽  
System A ◽  
Basic Characteristics

With the continuous development and advancement of computer technology, big data guarantees the establishment of an urban intelligent transportation system, a solid environmental basis to reform its application, and the construction of a deeply integrated data mechanism for big data-driven traffic management. This review paper briefly elaborates on the basic characteristics and sources of traffic big data as well as expound on the problems and application mechanisms of big data in intelligent transportation systems.

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