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Security and privacy issues in VANET
Published in Muhammad Arif, Guojun Wang, Mazin Abed Mohammed, Md Tabrez Nafis, Vehicular Ad Hoc Networks, 2023
Aqeel Khalique, M. Afshar Alam, Imran Hussain, Safdar Tanweer, Tabrej A. Khan
VANET will ultimately result in solving traffic problems to an extent and hence may also improve the problems we face such as fuel wastage, excessive time delays, economic losses, and environmental pollution and hence increase the sustainability of smart transportation. VANET application areas include but are not limited to the following: Smart transportationIntelligent transport system (ITS)Active road safety applicationsSmart traffic light systemParking guidance systemDynamic traffic management systemInfotainment applicationsVehicle monitoring and navigation
Fog Computing Applications
Published in Sudip Misra, Subhadeep Sarkar, Subarna Chatterjee, Sensors, Cloud, and Fog: The Enabling Technologies for the Internet of Things, 2019
Sudip Misra, Subhadeep Sarkar, Subarna Chatterjee
As an alternative solution, Truong et al. [28] proposed an SDN-supported VANET to leverage the benefits of fog computing and enable seamless vehicle-to-vehicle communications. In the fog-based SDN structure (FSDN) proposed in the work, the authors envision the mobile vehicles acting as edge devices. The vehicles are connected to the regional fog instances by the cellular network and the fog instances constantly supported by an SDN controller. At the core of the network remains the cloud, which is also connected to the SDN controller. This model does not put much computational load of the vehicular resources, and with the SDN acting as an orchestrator between the fog and cloud tiers service classification, data processing and integration operations can be performed seamlessly and very quickly. Smart traffic light system: Improving the traffic management system is an important component of a smart transportation system, and smart traffic light control plays a crucial role. Bonomi et al. [1] presented an outline of a smart traffic light system (STLS), the primary objective of which is to maintain a steady flow of traffic along the main roads and prevent road accidents. At the bottom-most tier of the system model, a pre-deployed set of sensors is envisaged as the edge devices along with the mobile vehicles. The sensors operating as the edge devices are responsible for two primary phenomena – measuring the distance and speed of vehicles approaching the sensor from every possible direction and detecting pedestrians, cyclists, and individuals in wheelchairs near the roadside footpaths and crossing the roads. The operating principle is to determine in real time the optimal signal-change cycle based on the traffic flow pattern (i.e., the traffic density, the on-road vehicles’ speed approaching from different directions, proximity of the vehicles, and the positions of the pedestrians and other slow moving entities). Clearly, as the system deals with mobile vehicles and involves human lives, the decision making is unambiguous, precise, and instantaneous. The location of the decision maker (DM) module, hence, must be closer to the edge in order to minimize the decision-making time. Alternatively, the DM can be conceptualized in a hierarchical manner, where a few modules are kept closer to the edge as part of the fog tier, while the others can be moved to the cloud. The four key attributes of the STLS, as envisaged by the authors, are: (i) support for wide geo-distribution of mobile devices (vehicles), (ii) predictable and low-latency services, (iii) consistent and unambiguous decision making, and (iv) multi-agency orchestration.
Security Concerns in Cooperative Intelligent Transportation Systems
Published in Georgios Kambourakis, Asaf Shabtai, Constantinos Kolias, Dimitrios Damopoulos, Intrusion Detection and Prevention for Mobile Ecosystems, 2017
Konstantinos Fysarakis, Ioannis Askoxylakis, Vasilios Katos, Sotiris Ioannidis, Louis Marinos
In ITS environments, V2V interactions typically rely on the instantiation of vehicular ad-hoc networks (VANETs), a sub-type of self-organized, large-scale mobile ad-hoc networks (MANETs), with single-hop and/or multi-hop and broadcasting or multicasting communications. Since VANETs feature vehicles as the mobile nodes, they come with all the associated intricacies compared to typical MANETs; for example, not as resource-constrained as a sensor, high speed and large-scale mobility, highly dynamic contact between numerous nodes, and privacy concerns. Nevertheless, a fully featured ITS deployment, or cooperative intelligent transportation system (C-ITS), as it may be referred to, is not limited to communications between vehicles but also includes other heterogeneous devices and the services and applications that run on top of those. In this context, VANETs are only part of the communication infrastructure of the ecosystem. A C-ITS features a multi-communication model that, in addition to communications between vehicles, also features communications between other forms of transport (e.g., trains, buses, motorcycles, and bicycles) and even other objects such as flying drones and other autonomous systems (referred to as vehicle-to-everything communications, or V2X). Other types of communications can include pedestrians (vehicle-to-pedestrians, V2P) as well as interactions with the infrastructure and other parts of the road network (vehicle-to-infrastructure, V2I), such as fixed road-side units (RSUs) and mobile RSUs. Moreover, communication between infrastructure entities is needed (infrastructure-to-infrastructure, I2I), for example, a smart traffic light communicating with a smart road lamp, as well as the presence of backend systems (e.g., for traffic management). The RSUs will typically also feature direct communication with the backend infrastructure, via a backbone network. One or more trusted authorities (TAs), or certificate authorities (CAs), can also be present at the backend for the registration, issuance, and validation of certificates of the involved entities, an integral part of vehicular public key infrastructure (VPKI) setups. Other than the above entities, another important element in the C-ITS landscape are the services themselves, including enhanced version of existing services (e.g., tolling) as well as novel transport-related services (e.g., safety systems, fleet management, and travel planning) and the associated infrastructures that support them. Consequently, a C-ITS may also involve a variety of service providers (e.g., fleet management and leasing companies), ICT systems and communication networks that enable the corresponding applications, as well as the data generated and operated upon in the context of these services. The coordination and integration of said services aims to bring major social and economic benefits, by maximizing the benefits of transportation to both commercial users and the general public, leading to greater transport efficiency, minimized environmental impact, and increased safety.
Dynamic bus dispatching using multiple types of real-time information
Published in Transportmetrica B: Transport Dynamics, 2019
Xinggang Luo, Yingxin Liu, Yang Yu, Jiafu Tang, Wei Li
The IoT provides windows of opportunity for public transportation systems to obtain various types of real-time information. As is well-known, the IoT is a new paradigm in information technology based on the internet and wireless telecommunication. The components in the IoT have unique identities and they can interact and cooperate with each other to achieve common goals. The IoT plays an important role in many industrial fields such as manufacturing, logistics, transportation, and health care and will result in a revolutionary change in our daily life. Under the context of the IoT, various types of real-time information can be obtained for public transportation systems, which is very useful for reducing the uncertainty of the system and increasing the ability of a quick response; this will enable the precise control and management of public transportation systems. Another benefit of the IoT is that a sub-system of transportation based on the IoT has the ability of self-coordination and self-autonomy, which can reduce the quantity of data transmission and alleviate the computational burden of the transit control center. For example, a smart traffic light controller perceives the approach of several buses at a crossroad and adjusts the times of the traffic signal phases. An automatic passenger counter (APC) on a bus perceives the existence of passengers, computes the number of passengers by using its embedded identification algorithm, and sends the counting results to the terminal box of the bus. Therefore, by using the IoT, a public transportation system can provide better control strategies and scheduling schemes, thus it utilizes the transportation resources more efficiently and improves the quality of public transportation.