A Review of Intelligent Transport System and Its People's Needs Considerations for Traffic Management's Policy Framework in a Developing Country

Global Advancements in Connected and Intelligent Mobility - Advances in Mechatronics and Mechanical Engineering ◽

10.4018/978-1-5225-9019-4.ch005 ◽

2020 ◽

pp. 166-195 ◽

Cited By ~ 1

Author(s):

Ayodele Adekunle Faiyetole

Keyword(s):

Developing Country ◽

Transport System ◽

Traffic Management ◽

Policy Framework ◽

Management Systems ◽

Intelligent Transport System ◽

Traveler Information ◽

Intelligent Transport ◽

Policy Direction ◽

Context Specific

This chapter prospects on the desirability of deployable Intelligent Transport System (ITS) solutions that can improve on the existing traffic management systems in a developing country. The chapter unveils that there is little or no specific plan targeted at any future deployment in Nigeria, for instance. Revealing that a systematic deployment of ITS applications, with candid appreciations from the citizenries, could follow the order of advanced public transport system trailed by advanced traffic management systems, advanced vehicle communication systems or advanced traveler information systems, and intelligent transport pricing systems. It concludes that the country could develop context-specific evidence-based policies toward the deployment of ITS, capable of intuitively adapting to the future traffic demands and inclusively improve transport efficiency and safety. The chapter also provide a conceptual policy framework considering people's needs as context-specific, which facilitates constructive discussion informing policy direction.

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A Hybrid Convolutional Neural Network-Gradient Boosted Classifier for Vehicle Classification

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1016.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 213-216

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Transport System ◽

Traffic Management ◽

Vehicle Tracking ◽

Vehicle Classification ◽

Intelligent Transport System ◽

Hybrid Classifier ◽

New Approach ◽

Intelligent Transport

Vehicle tracking and classification are used for intelligent transport system to provide data in terms of traffic management, routing, vehicle volume and others. A new approach will be introduced in this paper, a hybrid classifier that would detect vehicles that would be adaptable to Philippine settings. A combination of convolutional neural network and gradient boosted classifier would boost the classifying accuracy. In the discussion, CNN has outperformed other classifier in terms of accuracy while GBC got the highest AUROC and highest accuracy in terms of classifying. Although CNN and GBC is prone to overfitting, the dataset that will be used contains 1 hour of video.

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Big Data Architecture for Intelligent Transport Systems

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.i8119.078919 ◽

2019 ◽

Vol 8 (9) ◽

pp. 1281-1286

Keyword(s):

Big Data ◽

Transport System ◽

Traffic Management ◽

Structured Data ◽

Transport Systems ◽

Intelligent Transport System ◽

Intelligent Transport ◽

Related Data ◽

Data Architecture ◽

Smart Traffic

Day by day as the volume of data is being generated massively, storing of data and processing of data becomes a ever growing challenge in intelligent transport system (ITS). In intelligent transport system there are different areas to concentrate like smart parking systems, dynamic toll charging, smart traffic management etc. This paper is mainly focused on big data architecture for intelligent transport system for dynamic toll charging, traffic management and traffic analysis related data collection from various sources. The data collected from various sources can be in the form of structured data, semi structured data and unstructured data. Because of verity of data collected, this paper gives an idea about which data model is appropriate depending on data collected for transportation system.

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Issues, Challenges, and Research Opportunities in Intelligent Transport System for Security and Privacy

Applied Sciences ◽

10.3390/app8101964 ◽

2018 ◽

Vol 8 (10) ◽

pp. 1964 ◽

Cited By ~ 8

Author(s):

Qazi Ali ◽

Naveed Ahmad ◽

Abdul Malik ◽

Gauhar Ali ◽

Waheed Rehman

Keyword(s):

Transport System ◽

Traffic Management ◽

Location Privacy ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Computational Cost ◽

Security And Privacy ◽

Communication Overhead ◽

Intelligent Transport System ◽

Intelligent Transport

Intelligent transport system (ITS), owing to their potential to enhance road safety and improve traffic management, have attracted attention from automotive industries and academia in recent years. The underlying technology—i.e., vehicular ad-hoc networks (VANETs)—provide a means for vehicles to intelligently exchange messages regarding road and traffic conditions to enhance safety. The open nature of ITS as wireless communication technology leads to many security and privacy challenges. These challenges pertain to confidentiality, authentication, integrity, non-repudiation, location privacy, identity privacy, anonymity, certificate revocation, and certificate resolution. This article aims to propose a novel taxonomy of security and privacy issues and solutions in ITS. Furthermore, categorization of security and privacy schemes in ITS and their limitations are discussed with various parameters—scalability, privacy, computational cost, communication overhead, latency—and various types of security attacks has been analyzed. This article leverages new researchers for challenges and opportunities related to security and privacy in ITS.

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