Query: Intelligent Transport System

title: Vehicle detection in intelligent transport system under a hazy environment: a survey
abstract: Developing an intelligent transportation system has attracted a lot of attention in the recent past. Moreover, with the growing number of vehicles on the road most nations are adopting an intelligent transport system (ITS) for handling issues like traffic flow density, queue length, the average speed of the traffic, and total vehicles passing through a point in a specific time interval and so on. ITS by capturing traffic images and videos through cameras, helps the traffic control centres in monitoring and managing the traffic. Efficient and unfailing vehicle detection is a crucial step for the ITS. This study reviews different techniques and applications used around the world for vehicle detection under various environmental conditions based on video processing systems. This study also discusses the types of cameras used for vehicle detections, and the classification of vehicles for traffic monitoring and controlling. This study finally highlights the problems encountered during surveillance under extreme weather conditions.

title: IoT Based Context Aware Intelligent Public Transport System in a Metropolitan Area
abstract: The public transportation system (PTS) in a metropolitan area is a nonlinear, dynamic, and complex system. Managing and providing suitable public transportation services are difficult. In this article, we propose an Internet of Things based intelligent PTS (IoT IPTS) in a metropolitan area. An IoT is used to interconnect transportation entities, such as vehicles, commuters (mobile phones) routes (sensors) roadside units (RSUs) etc. in a metropolitan area. The IoT provides the seamless connectivity between different networking technologies whenever the commuters or vehicles move from one location to another location. Hence, IoT provides the suitable seamless public transportation services in the metropolitan area. In addition, we have used context information of transportation entities, such as routes condition, traffic density, number of routes available, traffic congestion, vehicles' movement, and their mobility, which are stored in the cloud. The stored context information in cloud along with the IoTs are used to find the relevant routes, alternative modes, departure times, and many more for providing public transportation services in a metropolitan area. The proposed IoT IPTS makes use of static and mobile agents with the emergent intelligence technique (EIT) for collecting, analyzing, and sharing context information. The analyzed context information is used to form the policies to provide the best available public transportation services to the commuters in a metropolitan area. The software defined network is used to enable the cloud computing and EI network to manage the public transportation services to the commuters.

title: Intelligent Transport System Based on Bluetooth
abstract: A Cooperative Intelligent Transport System (C ITS) is a system where mobile stations OBU (On Board Units) exchange messages with other ITSS V (Intelligent Transport System Station Vehicle) or RSU (Road Side Units) Messages are sent through a specific WIFI (IEEE 802.11p) denoted also ETSI ITS G5. The efficiency of this technology has been proven in terms of latency. However, RSU are common everywhere and stations equipped with G5 interface are not widely deployed. For this reason we look for another mean to guarantee this communication. Bluetooth Low Energy (BLE) is deployed on smartphones. We take advantage of this deployment to propose an architecture based on this protocol in order to build a Cooperative Intelligent Transport System. Cellular networks are widely deployed and can support these communications. We have adapted the ITS stack provided by the ETSI (designed for G5) to the BLE protocol.

title: Experimental Evaluation of Intelligent Transport System with VLC Vehicle to Vehicle Communication
abstract: Visible light communication (VLC) is suitable and natural candidate for vehicular communication. This paper presents the vehicle to vehicle communication system based on VLC technology utilizing light emitting diodes (LEDs) as a transmitter and photodiode as a receiver. The LEDs are present everywhere in outdoor and vehicles utilizing those for communication. Vehicular ad hoc networks are facilitated by empowering enormous applications to require both proficient and reliable data delivery. Low latency, simple and cost effective system is designed with less complexity and high consistency by employing off the shelf LEDs and photodiodes which mitigates the implementation of complex protocols of typical wireless communication systems. The signal is transmitted from one vehicle that will be received by another vehicle to make sensible steps and to maintain strategic distance to avoid accidents. In this paper, the performance analysis of VLC based vehicle to vehicle communication (V2V) is presented. The results show that 3.5 Mbps and 500 kbps of data rates have been achieved over the distance of 0.5 and 15 m respectively. Amplitude shift keying, frequency shift keying (FSK) and phase shift keying schemes are tested with non return zero coding scheme. Bit error rate, received optical power and received signal voltages are measured and analyzed in this paper for V2V communication. The FSK modulation is an efficient technique for long distance as it has lower losses compared to other techniques. Warning messages are displayed on liquid crystal display. The prototype is evaluated experimentally over the distance of 15 m using an array of LEDs to reduce the chances of accidents. Bit error rate of 10 11 for FSK modulation has been achieved with the signal to noise ratio value of 13 dB in this work. The results confirmed the performance of the proposed system and presented that VLC is a feasible technology for vehicular communication.

title: A Computer Vision Based Roadside Occupation Surveillance System for Intelligent Transport in Smart Cities
abstract: In digital and green city initiatives, smart mobility is a key aspect of developing smart cities and it is important for built up areas worldwide. Double parking and busy roadside activities such as frequent loading and unloading of trucks, have a negative impact on traffic situations, especially in cities with high transportation density. Hence, a real time internet of things (IoT) based system for surveillance of roadside loading and unloading bays is needed. In this paper, a fully integrated solution is developed by equipping high definition smart cameras with wireless communication for traffic surveillance. Henceforth, this system is referred to as a computer vision based roadside occupation surveillance system (CVROSS) Through a vision based network, real time roadside traffic images, such as images of loading or unloading activities, are captured automatically. By making use of the collected data, decision support on roadside occupancy and vacancy can be evaluated by means of fuzzy logic and visualized for users, thus enhancing the transparency of roadside activities. The CVROSS was designed and tested in Hong Kong to validate the accuracy of parking gap estimation and system performance, aiming at facilitating traffic and fleet management for smart mobility.

title: Methodology and trends for an intelligent transport system in developing countries
abstract: Increasingly, the technologies that are used in telecommunications contribute to improve intelligent transport systems. These technologies are systems that offer several concepts like vehicular ad hoc networks, which allow reduction of traffic accidents, traffic congestion and consequently increase road safety and the comfort of road users. Developing countries in general and those of sub Sahara in particular do not have telecommunication infrastructures, even road infrastructures for the implementation of an intelligent transport system. Moreover, with the serious increase in vehicles in these countries, the problem of traffic regulation arise especially in the inter urban context. One of the consequences of this problem is the high rate of road traffic accidents. Several models of traffic regulation as well as modeling systems of urban transport networks are presented in the literature. Unfortunately these models are intended for developed countries. The aim of this paper is to present, firstly the problems of the implementation of intelligent transport systems in developing countries like sub Saharan Africa. Secondly, we present a survey of a road traffic model and an urban transport network models. Finally, we propose solutions, which provide methodologies for the modeling of a system and monitor traffic on inter urban road transport networks in developing countries.

title: Intelligent Transport System in Smart Cities
abstract: Transportation systems constitute an essential part of modern life and large urban centers. These systems have emerged as major players in enabling the mobility of not only vehicles but also people residing in cities, playing a part in all issues related to mobility within urban environments. Owing to the unprecedented growth of urban centers and the introduction of new services that have emerged as a result of technological advancements, these systems have been increasingly requiring considerable support to manage resources and vehicles. Transportation systems play a role in coordinating vehicle traffic and guaranteeing safety, which involves tackling many challenging issues commonly observed in large urban centers. The advancements and support of information and communication technologies have enabled the design and implementation of transportation solutions, which led to the development of intelligent transportation systems (ITSs) and the provision of many innovative services, such as those related to guaranteeing safety, providing useful information to drivers, enabling greater flow of movement on streets, and avoiding congestion. ITSs combine various technologies and services to optimize urban mobility and reduce both the financial and environmental damage caused by the demand for vehicles in urban centers. This chapter describes the fundamental concept of ITSs in the context of big cities.

title: SPATA: Strong Pseudonym Based AuthenTicAtion in Intelligent Transport System
abstract: Intelligent transport system (ITS) is generally deployed to improve road safety, comfort, security, and traffic efficiency. A robust mechanism of authentication and secure communication is required to protect privacy and conditional resolution of pseudonyms to revoke malicious vehicles. In a typical ITS framework, a station can be a vehicle, road side unit, or a server that can participate in communication. During authentication, the real identity of an intelligent transport system station, referred to as a vehicle, should not be revealed in order to preserve its privacy. In this paper, we propose a Strong Pseudonym based AutenTicAtion (SPATA) framework for preserving the real identity of vehicles. The distributed architecture of SPATA allows vehicles to generate pseudonyms in a very private and secure way. In the absence of a distributed architecture, the privacy cannot be preserved by storing information regarding vehicles in a single location. Therefore, the concept of linkability of certificates based on single authority is eliminated. This is done by keeping the real identity to pseudonym mappings distributed. Furthermore, the size of the certificate revocation list (CRL) is kept small, as only the most recent revoked communication pseudonyms are kept in the CRL. The privacy of the vehicle is preserved during the revocation and resolution phase through the distributed mechanism. Empirical results show that SPATA is a lightweight framework with low computational overhead, average latency, overhead ratio, and stable delivery ratio in both sparse and dense network scenarios.

title: Adaptive Security for Intelligent Transport System Applications
abstract: The transportation system is gradually migrating toward autonomous, electric and intelligent vehicles. Wireless enabled vehicles along with infrastructure units on the road are connected with traffic management centers that use intelligent data analysis tools to efficiently manage city's traffic. However, such wireless connectivity can make the ITS networks vulnerable to security threats; thus, impacting the application's reliability. On the other hand, the use of robust security techniques could hamper applications' quality of service (QoS) To understand the interplay between these two conflicting requirements, this article reviews the security and QoS design challenges in the ITS aspect of smart cities. Using an experimental test bed, we evaluate the standard compliant security processing delays, develop an on line tool that presents detailed security benchmark results, and study the impact of security on QoS using simulation results. We also discuss how machine learning based adaptive signature verification techniques can enhance QoS in ITS. We further present future opportunities to optimize the security QoS balance for ITS applications.

title: Vector Based Trajectory Storage and Query for Intelligent Transport System
abstract: With the developing of smart sensors and mobile devices produces an increasing volume of data, and it captures the states of transportation infrastructures. Such data are collected and uploaded frequently, which forms the heavy data calculation and storage. Moreover, state of monitored object may be keeping the same or slight change according to a certain state during a period, such as moving vehicles on a certain path with a basic uniform speed. Therefore, if trajectory pattern of vehicles can be obtained through the state change mode, scale and update frequency of the data can be greatly reduced. Based on the above mentioned ideas, we are aware that the trajectory data storage is divided into traceability storage and vector storage, where original sampled data from sensing device, and state vectors are extracted from the analysis of the original sample data. In this way, only a relatively small amount of vector data is stored. The system will not only effectively reduce the frequency of sampling data storage, but also reduce query and analysis operations involved with the amount of data. The vector function is used to represent road network with indexes, and the data query based on the road network is used to extract the semantic information. Our experimental results show that our proposed methodologies have significant improvements in intelligent transportation.