Assessment of GNSS and Map Integration for Lane-Level Applications in the Scope of Intelligent Transportation Location Based Services (ITLBS)

2018 ◽  
pp. 175-181
Author(s):  
Emerson Pereira Cavalheri ◽  
Marcelo Carvalho dos Santos
Keyword(s):  
Intelligent Transportation ◽  
Location Based Services ◽  
Map Integration

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.

A Novel Approach for Data Communication and Safety Concern in VANET Using Cognitive Radio

2017 ◽  
Vol 7 (11) ◽  
pp. 174 ◽  
Author(s):  
Ishu Bansal ◽  
Rajnish Kansal
Keyword(s):  
Routing Protocols ◽  
Intelligent Transportation System ◽  
Safety Concern ◽  
Data Communication ◽  
Intelligent Transportation ◽  
Safety Message ◽  
Novel Approach ◽  
Transmission Of Information ◽  
Minimum Delay ◽  
Road Side Units

VANET is branch of networking that is used for communication in intelligent transportation system. In this process of VANET various nodes are interconnected to each other and road side units. R2R, V2V and V2R communication has been done in VANET. Due to variouscommunications under VANET routing protocols have overhead for computation of shortest path and transmission of information with minimum delay. Delay in the network cause minimum safety. In this paper an approach has been proposed that can be used for transmission of safety message over the network with minimum delay. On the basis of proposed approach safety message can be transmitted in shortest interval of time so that safety can be achieved in the network.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.

PENGARUH MODEL PROBLEM BASED LEARNING (PBL) DIPADU MIND MAP TERHADAP KREATIVITAS DALAM MEMECAHAN MASALAH PADA KONSEP PENCEMARAN LINGKUNGAN

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Novi Tri Susanti ◽  
Anna Fitri Hindriana ◽  
Haruji Satianugraha
Keyword(s):  
Problem Solving ◽  
Environmental Pollution ◽  
Problem Based Learning ◽  
Sampling Technique ◽  
Average Score ◽  
Control Group ◽  
Learning Models ◽  
Control Group Design ◽  
Integration Effect ◽  
Map Integration

This study aim to determine the effect of Problem Based Learning (PBL) models in mind map integration to creativity of problem solving in the environmental pollution concept of graders X. The method used is a Quasi-experimental design form Nonequivalent Control Group Design (pretest- posttest). The study population is all the students of graders X academic year 2017/2018 as many as 9 classes with the number of 360 students. The sample used was 80 students from two classes as an experimental class and a control class. Sampling was done by Cluster Random Sampling technique. Instruments used include test descriptions, questionnaires and teacher observation sheets. The results of the analysis of the test descriptions creativity in problem solving obtained results of hypothesis testing (t test) i.e. 20.5 t count > t table of 2.66 means that Ho refused and Hi accepted, it means PBL learning models in Mind Map integration effect on creativity in problems solving. This is indicated by an increase in the average score on each indicator of creativity in problem solving in which students are able to grow various ideas, enrich ideas, add or detail the details of an idea and determine the truth to solve the problems. From the analysis of questionnaire data showed an interest in learning to use the PBL modela in Mind map integration, students agreed that if the model of PBL in Mind map integration may be easier to learn about the concept of Environmental Pollution. In addition, students also agreed that if the PBL models in Mind map integration effect on creativity in problems solving. The results showed that there was a significant influence between learning using PBL models in Mind map integration those not using the learning models to creativity in problems solving in the concept of environmental pollution of graders X.

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