Showing papers on "Vehicular communication systems published in 2016"

Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures

Abstract: With the emergence of ever-growing advanced vehicular applications, the challenges to meet the demands from both communication and computation are increasingly prominent. Without powerful communication and computational support, various vehicular applications and services will still stay in the concept phase and cannot be put into practice in the daily life. Thus, solving this problem is of great importance. The existing solutions, such as cellular networks, roadside units (RSUs), and mobile cloud computing, are far from perfect because they highly depend on and bear the cost of additional infrastructure deployment. Given tremendous number of vehicles in urban areas, putting these underutilized vehicular resources into use offers great opportunity and value. Therefore, we conceive the idea of utilizing vehicles as the infrastructures for communication and computation, named vehicular fog computing (VFC), which is an architecture that utilizes a collaborative multitude of end-user clients or near-user edge devices to carry out communication and computation, based on better utilization of individual communication and computational resources of each vehicle. By aggregating abundant resources of individual vehicles, the quality of services and applications can be enhanced greatly. In particular, by discussing four types of scenarios of moving and parked vehicles as the communication and computational infrastructures, we carry on a quantitative analysis of the capacities of VFC. We unveil an interesting relationship among the communication capability, connectivity, and mobility of vehicles, and we also find out the characteristics about the pattern of parking behavior, which benefits from the understanding of utilizing the vehicular resources. Finally, we discuss the challenges and open problems in implementing the proposed VFC system as the infrastructures. Our study provides insights for this novel promising paradigm, as well as research topics about vehicular information infrastructures.

Information-centric networking for connected vehicles: a survey and future perspectives

Abstract: In the connected vehicle ecosystem, a high volume of information-rich and safety-critical data will be exchanged by roadside units and onboard transceivers to improve the driving and traveling experience. However, poor-quality wireless links and the mobility of vehicles highly challenge data delivery. The IP address-centric model of the current Internet barely works in such extremely dynamic environments and poorly matches the localized nature of the majority of vehicular communications, which typically target specific road areas (e.g., in the proximity of a hazard or a point of interest) regardless of the identity/address of a single vehicle passing by. Therefore, a paradigm shift is advocated from traditional IP-based networking toward the groundbreaking information- centric networking. In this article, we scrutinize the applicability of this paradigm in vehicular environments by reviewing its core functionalities and the related work. The analysis shows that, thanks to features like named content retrieval, innate multicast support, and in-network data caching, information-centric networking is positioned to meet the challenging demands of vehicular networks and their evolution. Interoperability with the standard architectures for vehicular applications along with synergies with emerging computing and networking paradigms are debated as future research perspectives.

Platoon based Cooperative Driving Model with Consideration of Realistic Inter-vehicle Communication

Abstract: Recent developments of information and communication technologies (ICT) have enabled vehicles to timely communicate with each other through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Nevertheless, unreliable vehicular communications also introduce packet loss and transmission delay when vehicular kinetic information or control commands are disseminated among vehicles, which brings more challenges in the system modeling and optimization. Currently, no data has been yet available for the calibration and validation of a model for ITS, and most research has been only conducted for a theoretical point of view. Along this line, this paper focuses on the (theoretical) development of a more general (microscopic) traffic model which enables the cooperative driving behavior via a so-called inter-vehicle communication (IVC). To this end, the authors design a consensus-based controller for the cooperative driving system (CDS) considering (intelligent) traffic flow that consists of many platoons moving together. More specifically, the IEEE 802.11p, the de facto vehicular networking standard required to support ITS applications, is selected as the IVC protocols of the CDS, in order to investigate how the vehicular communications affect the features of intelligent traffic flow. This study essentially explores the relationship between IVC and cooperative driving, which can be exploited as the reference for the CDS optimization and design.

SDVN: enabling rapid network innovation for heterogeneous vehicular communication

Abstract: With the advances in telecommunications, more and more devices are connected to the Internet and getting smart. As a promising application scenario for carrier networks, vehicular communication has enabled many traffic-related applications. However, the heterogeneity of wireless infrastructures and the inflexibility in protocol deployment hinder the real world application of vehicular communications. SDN is promising to bridge the gaps through unified network abstraction and programmability. In this research, we propose an SDN-based architecture to enable rapid network innovation for vehicular communications. Under this architecture, heterogeneous wireless devices, including vehicles and roadside units, are abstracted as SDN switches with a unified interface. In addition, network resources such as bandwidth and spectrum can also be allocated and assigned by the logically centralized control plane, which provides a far more agile configuration capability. Besides, we also study several cases to highlight the advantages of the architecture, such as adaptive protocol deployment and multiple tenants isolation. Finally, the feasibility and effectiveness of the proposed architecture and cases are validated through traffic-trace-based simulation.

Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication

Abstract: Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication are emerging components of intelligent transport systems (ITS) based on which vehicles can drive in a cooperative way and, hence, significantly improve traffic flow efficiency. However, due to the high vehicle mobility, the unreliable vehicular communications such as packet loss and transmission delay can impair the performance of the cooperative driving system (CDS). In addition, the downstream traffic information collected by roadside sensors in the V2I communication may introduce measurement errors, which also affect the performance of the CDS. The goal of this paper is to bridge the gap between traffic flow modelling and communication approaches in order to build up better cooperative traffic systems. To this end, we aim to develop an enhanced cooperative microscopic (car-following) traffic model considering V2V and V2I communication (or V2X for short), and investigate how vehicular communications affect the vehicle cooperative driving, especially in traffic disturbance scenarios. For these purposes, we design a novel consensus-based vehicle control algorithm for the CDS, in which not only the local traffic flow stability is guaranteed, but also the shock waves are supposed to be smoothed. The IEEE 802.11p, the defacto vehicular networking standard, is selected as the communication protocols, and the roadside sensors are deployed to collect the average speed in the targeted area as the downstream traffic reference. Specifically, the imperfections of vehicular communication as well as the measured information noise are taken into account. Numerical results show the efficiency of the proposed scheme. This paper attempts to theoretically investigate the relationship between vehicular communications and cooperative driving, which is needed for the future deployment of both connected vehicles and infrastructure (i.e. V2X).

Support for vehicle-to-everything services based on LTE

Abstract: Vehicular applications and communications technologies are often referred to as vehicle-to-everything (V2X), which is classified into four different types: vehicle-to-vehicle (V2V), vehicle- to-infrastructure (V2I), vehicle-to-network (V2N), and vehicle-to-pedestrian (V2P) [1]. V2X related research projects, field tests, and regulatory work have been promoted in different countries and regions. In May 2015, the Ministry of Industry and Information Technology (MIIT) of China explained national strategies, "Made in China 2025," about intelligent connected vehicles. In 2020 and 2025, the overall technology and key technologies for intelligent driver assistance and automatic driving will be available in China, respectively [2]. V2X solutions are the critical technologies to support the realization of such visions. Although IEEE 802.11p has been selected as the technology for V2X communications in some countries such as the United States and in Europe, the intrinsic characteristics of IEEE 802.11p have confined the technology to support low latency with high reliability [3, 4]. Standardization of Long Term Evolution (LTE)-based V2X is being actively conducted by the Third Generation Partnership Project (3GPP) to provide the solution for V2X communications that benefit from the global deployment and fast commercialization of LTE systems. Because of the wide deployment of LTE networks, V2I and V2N services can be provided with high data rate, comprehensive quality of service (QoS) support, ubiquitous coverage, and high penetration rate [5]. Meanwhile, LTE can be extended to support V2V direct communications based on device-to-device (D2D) sidelink design to satisfy the QoS requirements, such as low latency, high reliability, and high speed in the case of high vehicle density [6].

Internet of Vehicles: From intelligent grid to autonomous cars and vehicular fogs:

Abstract: Recent advances in communications, controls, and embedded systems have changed the perception of a car. A vehicle has been the extension of the man's ambulatory system, docile to the driver's commands. It is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control, and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable of making its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g. the smart building), the Internet of Vehicles will have communications, storage , intelligence, and learning capabilities to anticipate the customers' intentions. The concept that will help transition to the Internet of Vehicles is the vehicular fog, the equivalent of instantaneous Internet cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from intelligent vehicle grid to autonomous, Internet-connected vehicles, and vehicular fog.

Secure and Privacy-Aware Cloud-Assisted Video Reporting Service in 5G-Enabled Vehicular Networks

Abstract: Vehicular networks are one of the main technologies that will be leveraged by the arrival of future fifth-generation (5G) mobile cellular networks. While scalability and latency are the major drawbacks of IEEE 802.11p and fourth-generation (4G) Long-Term Evolution (LTE)-enabled vehicular communications, respectively, the 5G technology is a promising solution to empower the real-time services offered by vehicular networks. However, the security and privacy of such services in 5G-enabled vehicular networks need to be addressed first. In this paper, we propose a novel system model for a 5G-enabled vehicular network that facilitates a reliable, secure, and privacy-aware real-time video reporting service. This service is designed for participating vehicles to instantly report the videos of traffic accidents to guarantee a timely response from official vehicles and/or ambulances toward accidents. While it provides strong security and privacy guarantees for the participating vehicle's identity and the video contents, the proposed service ensures traceability of misbehaving participants through a cooperation scheme among different authorities. We show the feasibility and the fulfillment of the proposed reporting service in 5G-enabled vehicular networks in terms of security, privacy, and efficiency.

Reinforcement learning for resource provisioning in the vehicular cloud

Abstract: This article presents a concise view of vehicular clouds that incorporates various vehicular cloud models that have been proposed to date. Essentially, they all extend the traditional cloud and its utility computing functionalities across the entities in the vehicular ad hoc network. These entities include fixed roadside units, onboard units embedded in the vehicle, and personal smart devices of drivers and passengers. Cumulatively, these entities yield abundant processing, storage, sensing, and communication resources. However, vehicular clouds require novel resource provisioning techniques that can address the intrinsic challenges of dynamic demands for the resources and stringent QoS requirements. In this article, we show the benefits of reinforcement-learning-based techniques for resource provisioning in the vehicular cloud. The learning techniques can perceive long-term benefits and are ideal for minimizing the overhead of resource provisioning for vehicular clouds.

Prefetching-Based Data Dissemination in Vehicular Cloud Systems

Abstract: In the last decade, vehicular ad hoc networks (VANETs) have been widely studied as an effective method for providing wireless communication connectivity in vehicular transportation systems. In particular, vehicular cloud systems (VCSs) have received abundant interest for the ability to offer a variety of vehicle information services. We consider the data dissemination problem of providing reliable data delivery services from a cloud data center to vehicles through roadside wireless access points (APs) with local data storage. Due to intermittent wireless connectivity and the limited data storage size of roadside wireless APs, the question of how to use the limited resources of the wireless APs is one of the most pressing issues affecting data dissemination efficiency in VCSs. In this paper, we devise a vehicle route-based data prefetching scheme, which maximizes data dissemination success probability in an average sense when the size of local data storage is limited and wireless connectivity is stochastically unknown. We propose a greedy algorithm and an online learning algorithm for deterministic and stochastic cases, respectively, to decide how to prefetch a set of data of interest from a data center to roadside wireless APs. Experiment results indicate that the proposed algorithms can achieve efficient data dissemination in a variety of vehicular scenarios.

Energy harvesting in vehicular networks: a contemporary survey

Abstract: Vehicular networks have recently been witnessing an upsurge of interest in energy consumption control. Precisely, in the majority of vehicular networking scenarios, roadside units are deployed along roadways in rural areas as well as on the sides of long highways where a direct connection to the electric grid is merely available. In such situations, these roadside units will be equipped with rechargeable batteries with maintenance requiring costly human intervention. Thus far, the literature offers several proposals of efficient operation schemes for roadside units aiming at optimizing their energy consumption, hence, elongating their duration of availability and participation in the network. Energy harvesting presents itself as an appealing alternative to power/recharge nodal batteries in wireless networks. This article starts by presenting a concise general overview of energy harvesting sources, techniques, and applications. Second, it investigates the feasibility of energy harvesting in vehicular networks, specifically the different challenges confronting its applicability in vehicular environments. Finally, pending related open research problems and directions are presented.

Toward Multi-Radio Vehicular Data Piping for Dynamic DSRC/TVWS Spectrum Sharing

Abstract: Enabling high-throughput and cost-effective vehicular communications is important for many emerging vehicular applications, such as safety applications, traffic management, and mobile Internet access. However, dedicated short-range communications (DSRC), as the sole solution so far, would meet significant challenges in the foreseeable future for supporting diverse vehicular applications simply due to the spectrum scarcity. To address this issue, in this paper, we propose an adaptive vehicular data piping framework, which is assisted by a geolocation database, for the joint utilization of DSRC and TV white space (TVWS) spectrum; in this framework, three types of vehicular data pipes (DSRC, TVWS, and cellular) are considered, while the cellular data pipe is only used as a control-plane link in coordinating the dynamic DSRC and TVWS spectrum sharing happened in the data-plane operations. In order to guarantee the optimal dynamic vehicular access to the geolocation database, we first propose a log-sum-exp (LSE) approximation-based TVWS geolocation database access approach, named LSE-WS algorithm. We formulate the adaptive vehicular data piping problem for dynamic DSRC/TVWS spectrum sharing as a coalitional formation game, and it is shown that the proposed coalitional formation approach reaches the optimal and Nash-stable vehicular data pipe selection partition in a distributed way. Through extensive simulations, we demonstrate that not only the proposed LSE-WS algorithm satisfies the dynamic vehicular geolocation database access requirement but also the adaptive multi-radio vehicular data piping approach for dynamic DSRC/TVWS spectrum sharing significantly outperforms the traditional DSRC solution.

Toward Environmental-Adaptive Visible Light Communications Receivers for Automotive Applications: A Review

Abstract: Since more and more vehicles are using the transportation infrastructure, the safety and the efficiency of roads are of absolute importance. A solution to enhance the security of road transportation is by enabling wireless communications between vehicles and also with the traffic infrastructures (e.g., traffic lights, street lighting, or traffic signs). In this area, visible light communications (VLC) is considered of great perspective. A fundamental problematic in vehicular VLC is the design of a proper sensor capable to support long distance communications in dynamic traffic situations and in unfriendly atmospheric conditions. Therefore, this paper is focused on the design of the VLC sensors intended for vehicular communication applications, offering a review of the solutions found to mitigate the effect of the problematic conditions. Furthermore, this paper summarizes these solutions and proposes an environmental adaptive VLC receiver that would be capable to optimally adjust its settings in order to maximize the communication efficiency, but without affecting the communication robustness to noise.

Cooperative Intelligence of Vehicles for Intelligent Transportation Systems (ITS)

Abstract: The aim of Intelligent Transportation Systems (ITS) is to automate the interactions among vehicles and infrastructure to accomplish high levels of safety measures, comfort, and competence in vehicular communication. To utilize the future trends of increasing traffic safety and efficiency in ITS, integrating vehicles and infrastructures with the cooperative vehicular technique will be the feasible solution. In order to demonstrate the importance of cooperative communication in vehicular networks, a spectral efficient architecture has been proposed for cooperative centralized and distributed spectrum sensing in vehicular networks. We discuss the possibilities of Cognitive Radio in the cooperative vehicular environment. In order to exhibit cooperative vehicular networks, hardware modules are designed for a vehicle to vehicle, vehicle to infrastructure and infrastructure to infrastructure communications. Furthermore, quantitative analysis is made in order to calculate the energy optimization, connectivity failure probability and traffic management in cooperative vehicular networks. In addition, we test the results of the cooperative vehicular network by simulating it in NS2. In this respect, we have considered three different cases, Emergency vehicles, VIP vehicles, and normal vehicles. It is inferred from the results that end-to-end delay for emergency vehicles in the cooperative environment is considerably less as compared to VIP and normal vehicles.

Integration of congestion and awareness control in vehicular networks

Abstract: Cooperative vehicular networks require the exchange of positioning and basic status information between neighboring nodes to support vehicular applications. The exchange of information is based on the periodic transmission/reception of 1-hop broadcast messages on the so called control channel. The dynamic adaptation of the transmission parameters when broadcasting such messages will be key for the reliable and efficient operation of vehicular networks. To this aim, vehicular networks utilize congestion control protocols to control the channel load, typically through the adaptation of the transmission parameters based on certain channel load metrics. Awareness control protocols are also required to adequately support cooperative vehicular applications. These protocols typically adapt the transmission parameters of periodic broadcast messages to ensure each vehicle's capacity to detect, and possibly communicate, with the relevant vehicles and infrastructure nodes present in its local neighborhood. To date, congestion and awareness control protocols have been normally designed and evaluated separately, although both will be required for the reliable and efficient operation of vehicular networks. In this context, this paper proposes and evaluates INTERN, a new control protocol that integrates two congestion and awareness control processes. The simulation results obtained for three different scenarios demonstrate that INTERN is able to satisfy the applications' requirements of all vehicles, while effectively controlling the channel load. The results obtained highlight the challenges ahead with emerging automated vehicles.

Cost-Efficient Sensory Data Transmission in Heterogeneous Software-Defined Vehicular Networks

Abstract: Sensing and networking have been regarded as key enabling technologies of future smart vehicles. Sensing allows vehicles to be context awareness, while networking empowers context sharing among ambients. Existing vehicular communication solutions mainly rely on homogeneous network, or heterogeneous network via data offloading. However, today’s vehicular network implementations are highly heterogeneous. Therefore, conventional homogeneous communication and data offloading may not be able to satisfy the requirement of the emerging vehicular networking applications. In this paper, we apply the software-defined network (SDN) to the heterogeneous vehicular networks to bridge the gaps. With SDN, heterogeneous network resources can be managed with a unified abstraction. Moreover, we propose an SDN-based wireless communication solution, which can schedule different network resources to minimize communication cost. We investigate the problems in both single and multiple hop cases. We also evaluate the proposed approaches using traffic traces. The effectiveness and the efficiency are validated by the results.

A Vehicular Cloud-Based Framework for the Intelligent Transport Management of Big Cities

Abstract: An intelligent transport system (ITS) is intended to streamline the operations of vehicles, manage vehicle traffic, and help drivers with safety and other information, as well as supply convenient applications for passengers. This system is essential for tackling the problems of a big city, like traffic congestion and a lack of a communication infrastructure or traffic engineering, among other factors. With these challenges in mind, we propose a vehicular cloud architecture to assist in the management of large cities. This will create a framework to support different types of services as well as provide storage mechanisms, access, and information management which includes tools for different modes of transport not only for citizens but also for commercial vehicles and emergency services like ambulances. In addition, it will be possible to increase the capacity for abstraction to meet information needs through the use of vehicular networks and the integration of VANETs with other networks, so as to provide...

An Architecture of Cloud-Assisted Information Dissemination in Vehicular Networks

Abstract: Vehicular network technology allows vehicles to exchange real-time information between each other, which plays a vital role in the development of future intelligent transportation systems Existing research on vehicular networks assumes that each vehicle broadcasts collected information to neighboring vehicles, so that information is shared among vehicles. The fundamental problem of what information is delivered with which vehicle(s), however, has not been adequately studied. We propose an innovative cloud-assisted architecture to facilitate intelligent information dissemination among vehicles. Within the novel architecture, virtual social connections between vehicles are created and maintained on the cloud. Vehicles with similar driving histories are considered friends in a vehicular social network (VSN). The closeness of the relation between two vehicles in a VSN is then modeled by the three-valued subjective logic model. Based on the closeness between vehicles, only relevant information will be delivered to vehicles that are likely interested in it. The cloud-assisted architecture coordinates vehicular social connection construction, VSN maintenance, vehicle closeness assessment, and information dissemination.

Contact-Aware Data Replication in Roadside Unit Aided Vehicular Delay Tolerant Networks

Abstract: Roadside units (RSUs), which enable vehicles-to-infrastructure communications, are deployed along roadsides to handle the ever-growing communication demands caused by explosive increase of vehicular traffics. How to efficiently utilize them to enhance the vehicular delay tolerant network (VDTN) performance are the important problems in designing RSU-aided VDTNs. In this work, we implement an extensive experiment involving tens of thousands of operational vehicles in Beijing city. Based on this newly collected Beijing trace and the existing Shanghai trace, we obtain some invariant properties for communication contacts of large scale RSU-aided VDTNs. Specifically, we find that the contact time between RSUs and vehicles obeys an exponential distribution, while the contact rate between them follows a Poisson distribution. According to these observations, we investigate the problem of communication contact-aware mobile data replication for RSU-aided VDTNs by considering the mobile data dissemination system that transmits data from the Internet to vehicles via RSUs through opportunistic communications. In particular, we formulate the communication contact-aware RSU-aided vehicular mobile data dissemination problem as an optimization problem with realistic VDTN settings, and we provide an efficient heuristic solution for this NP-hard problem. By carrying out extensive simulation using realistic vehicular traces, we demonstrate the effectiveness of our proposed heuristic contact-aware data replication scheme, in comparison with the optimal solution and other existing schemes.

Intelligent Vehicle Communication: Deterministic Propagation Prediction in Transportation Systems

Abstract: Intelligent transportation systems (ITSs) are currently under intense research and development for making transportation safer and more efficient. The development of such vehicular communication systems requires accurate models for the propagation channel. A key characteristic of these channels is their temporal variability and inherent time-changing statistics, which have a major impact on electromagnetic propagation prediction.

On platooning control using IEEE 802.11p in conjunction with visible light communications

Abstract: The control of a platoon using IEEE 802.11p is an active research challenge in the field of vehicular networking and cooperative automated vehicles. IEEE 802.11p is a promising technology for direct vehicle to vehicle communication, but there are concerns about its usage for the control of platoons as it suffers packet losses due to congestion in highly dense scenarios. On the other hand, Visible Light Communication (VLC) recently gained attention as a short range technology for vehicular applications. VLC could be used to support or backup IEEE 802.11p, increasing reliability and scalability, and hence the safety of platooning systems. In this paper, we perform a large-scale simulation campaign using VLC integrated with IEEE 802.11p for platooning. We particularly demonstrate the benefits, but also the limitations, of such heterogeneous networking.

The Key to Intelligent Transportation: Identity and Credential Management in Vehicular Communication Systems

Abstract: Vehicular Communication (VC) systems will greatly enhance intelligent transportation systems. But their security and the protection of their users' privacy are a prerequisite for deployment. Efforts in industry and academia brought forth a multitude of diverse proposals. These have now converged to a common view, notably on the design of a security infrastructure, a Vehicular Public Key Infrastructure (VPKI) that shall enable secure conditionally anonymous VC. Standardization efforts and industry readiness to adopt this approach hint to its maturity. However, there are several open questions remaining, and it is paramount to have conclusive answers before deployment. In this article, we distill and critically survey the state of the art for identity and credential management in VC systems, and we sketch a roadmap for addressing a set of critical remaining security and privacy challenges.

An Empirical Study on Urban IEEE 802.11p Vehicle-to-Vehicle Communication

Abstract: IEEE 802.11p based Dedicated Short Range Communication (DSRC) has been considered as a promising wireless technology for enhancing transportation safety and traffic efficiency. However, with limited literature available, there is lack of understanding about how IEEE 802.11p performs for vehicleto-vehicle (V2V) communications in urban environments. In this paper, we conduct intensive statistical analysis on V2V communication performance, based on the empirical measurement data collected from off-the-shelf IEEE 802.11p-compatible onboard units (OBUs). We have several key insights as follows. First, both line-of- sight (LoS) and non-line-of-sight (NLoS) durations follow power law distributions, which implies that the probability of having long LoS/NLoS conditions can be relatively high. Second, the packet inter-reception (PIR) time distribution follows an exponential distribution in LoS conditions but a power law in NLoS conditions. In contrast, the packet inter-loss (PIL) time distribution in LoS condition follows a power law but an exponential in NLoS condition. Third, the overall PIR time distribution is a mix of exponential distribution and power law distribution. The presented results provide solid ground to validate models, tune VANET simulators and improve communication strategies.

Road traffic congestion management using VANET

Abstract: With the constant increase in vehicular traffic, existing traffic management solutions have become inefficient. Urbanization has led to an increase in traffic jams and accidents in major cities. In order to accommodate the growing needs of transport systems today, there is a need for an Intelligent Transport System. Vehicular Adhoc Network (VANET) is a growing technology that assists in Intelligent Transport Systems. VANETs enable communication between vehicles as well as fixed infrastructure called Road Side Units (RSU). We propose a distributed, collaborative traffic congestion detection and dissemination system that uses VANET. Each of the driver's smart phones is equipped with a Traffic App which is capable of location detection through Geographic Position based System (GPS). This information is relayed to a remote server which detects traffic congestion. Once congestion is confirmed the congestion information is disseminated to the end user phone through RSUs. The Mobile App transmits the location information at periodic intervals. Using the latitude, longitude and the current time, the location of each vehicle is traced. Using location information, the distance moved by the vehicle at a given time is monitored. If the value is below a fixed threshold, congestion is suspected in a particular area. If many vehicles in the same area send similar messages, traffic congestion is confirmed. Once traffic congestion is confirmed, the vehicles approaching the congested area are informed about the traffic through display boards that are available in the nearest RSUs (traffic signals). The congestion information is also made available through the Mobile App present in vehicles approaching the congested area. The approaching vehicles may take diversion and alleviate congestion. Thus a smart traffic congestion detection and dissemination system is developed to divert incoming vehicles and reduce congestion without human intervention. This system can be further enhanced by communicating the congestion information directly between vehicles using IEEE 802.11p protocol.

Congestion Control for Vehicular Networks With Safety-Awareness

Abstract: Vehicular safety applications require reliable and up-to-date knowledge of the local neighborhood. Under IEEE 802.11p, this is attained through single-hop broadcasts of safety beacons in the control channel. However, high transmission power and node mobility can cause regions of node density to form rapidly. In such situations, excessive load on the control channel must be avoided to prevent performance degradation for safety applications. Existing congestion control schemes aim to reach a fair distribution of available channel resources, but fail to account for the differing quality of service (QoS) requirements of vehicles in different driving contexts. This context depends on many factors, including the relative position and velocity of its neighbors. The problem of adapting each vehicle's transmission probability under a slotted p-persistent vehicular broadcast medium access control (MAC) protocol is formulated as a network utility maximization (NUM) problem which takes the driving context into account. A distributed algorithm is proposed to solve this problem in a decentralized manner, its convergence is analyzed, and its performance is evaluated through simulations.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

Abstract: Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.