A Fuzzy Based Distributed Algorithm for Maintaining Connected Network Topology in Mobile Ad-Hoc Networks Considering Freeway Mobility Model

Mobile Ad-Hoc Networks (MANETs) present real-time embedded system that is being used in a wide variety of applications where traditional networking infrastructure is practically infeasible. The highly dynamic character of a Mobile Ad-Hoc Network (MANET) poses significant challenges on network communications. Previous work on MANET has resulted in numerous routing protocols aiming to maintain network connectivity among the active nodes. This paper presents a fuzzy-based distributed algorithm to maintain connected MANET considering freeway mobility model. According to the algorithm, each node will control itself in a way that it can maintain its connectivity with other nodes. In this approach each node is enabled with a Global Positioning System (GPS) receiver. Through GPS each and every node is getting its position and velocity. After getting the information all the nodes in a network transmit their position and velocity information periodically. Obtaining information from all other nodes, each node will decide its own velocity to maintain connectivity. Moreover, faults to a particular node have also been considered in this algorithm. Results obtained through simulation studies show the effectiveness of the proposed algorithm

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

AN ADAPTIVE INFORMATION DISSEMINATION MODEL FOR VANET COMMUNICATION

Vehicular ad hoc networks (VANETs) have been envisioned to be useful in road safety and many commercial applications. The growing trend to provide communication among the vehicles on the road has provided the opportunities for developing a variety of applications for VANET. The unique characteristics of VANET bring about new research challenges

A REAL-TIME TRAFFIC CONDITION ASSESSMENT AND PREDICTION FRAMEWORK USING VEHICLE-INFRASTRUCTURE INTEGRATION (VII) WITH COMPUTATIONAL INTELLIGENCE

This research developed a real-time traffic condition assessment and prediction framework using Vehicle-Infrastructure Integration (VII) with computational intelligence to improve the existing traffic surveillance system. Due to the prohibited expenses and complexity involved for the field experiment of such a system, this study adopted state-of-the-art simulation tools as an efficient alternative. This work developed an integrated traffic and communication simulation platform to facilitate the design and evaluation of a wide range of online traffic surveillance and management system in both traffic and communication domain. Using the integrated simulator, the author evaluated the performance of different combination of communication medium and architecture. This evaluation led to the development of a hybrid VII framework exemplified by hierarchical architecture, which is expected to eliminate single point failures, enhance scalability and easy integration of control functions for traffic condition assessment and prediction. In the proposed VII framework, the vehicle on-board equipments and roadside units (RSUs) work collaboratively, based on an intelligent paradigm known as \u27Support Vector Machine (SVM),\u27 to determine the occurrence and characteristics of an incident with the kinetics data generated by vehicles. In addition to incident detection, this research also integrated the computational intelligence paradigm called \u27Support Vector Regression (SVR)\u27 within the hybrid VII framework for improving the travel time prediction capabilities, and supporting on-line leaning functions to improve its performance over time. Two simulation models that fully implemented the functionalities of real-time traffic surveillance were developed on calibrated and validated simulation network for study sites in Greenville and Spartanburg, South Carolina. The simulation models\u27 encouraging performance on traffic condition assessment and prediction justifies further research on field experiment of such a system to address various research issues in the areas covered by this work, such as availability and accuracy of vehicle kinetic and maneuver data, reliability of wireless communication, maintenance of RSUs and wireless repeaters. The impact of this research will provide a reliable alternative to traditional traffic sensors to assess and predict the condition of the transportation system. The integrated simulation methodology and open source software will provide a tool for design and evaluation of any real-time traffic surveillance and management systems. Additionally, the developed VII simulation models will be made available for use by future researchers and designers of other similar VII systems. Future implementation of the research in the private and public sector will result in new VII related equipment in vehicles, greater control of traffic loading, faster incident detection, improved safety, mitigated congestion, and reduced emissions and fuel consumption

A pervasive prediction model for vehicular ad-hoc network (VANET)

The growth of city traffic has contributed to severe traffic congestion and traffic accidents in the most of the cities in the world. Since people’s travel demand rise at a rate usually greater than the addition of road capacity to lead many other issues, such as environmental problems and the quality of life. Intelligent Transportation System (ITS) is committed to solving the worsening traffic problems. Wide deployment of such ITS can eventually provide more dynamic, real-time and efficient solutions to transportation problems. ITS uses a variety of high technologies, especially electronic information technology and data communications technology to improve road traffic efficiency, road traffic safety and environmental protection. A number of researchers have depended on the wireless mobile communication to improve data collection and utilisation. The data could be used for early warning and forecasting traffic conditions in real-time. The benefit of wireless mobile communication research, especially Car to Car (C2C) communication is to abandon the expensive wireline-deployed and central processing units. Through the interconnection of many personal mobile devices, a low- cost freely extended, high-performance and parallel system can be formed. Car to Car communication can make possible efficient and reliable data transmission by wireless links in a traffic area. It is based on principles of mobile ad-hoc network (MANET) and applies to the domain of vehicles, being Vehicular ad-hoc network (VANET) which is a key component of ITS. The C2C communication system has become essential for driving safety and comfort and also for improving road condition. Also, the traffic prediction system is also an important part of ITS, traffic condition prediction can be regarded as an extension application of VANET. It provides traffic condition in advance via a variety of prediction models and helps the people make better driving safety, travel decisions and route selections regarding departure or driving time. The challenge of wireless traffic prediction technology is the uncertainty of traffic and real-time traffic data collection. It is widely known that urban transport system is a participatory, time-varying and complex nonlinear system. This uncertainty comes not only from the natural causes, such as seasonal and weather factors, but also from human factors, such as traffic accidents, emergencies and driver’s behaviour. In particular, the short-term traffic prediction is more affected by random interference factors. Current wireless traffic prediction research is usually based on a combination of wireless technology and traditional prediction model. The predictable traffic conditions include travel speed, travel time, traffic density, traffic accident, congestion level. However, in a large network environment, as the number of nodes increases, the transmission performance degrades and the prediction accuracy decreases because the prediction model does not obtain enough data. In this thesis, a novel traffic prediction framework (PPM-C2C) is proposed – Pervasive Prediction Model (PPM) based on the C2C communication. The framework utilises ad-hoc data via C2C communications for a short time traffic prediction in each car. This project builds and investigates the behaviour of a pervasive traffic simulation model in Ad-hoc network, with a particular part of it embedded into each vehicle’s equipment. It includes the data collection, aggregation and application aim to be running in all individual cars so that cars have up to date information on the traffic at all times. Moreover, those cars could predict the traffic conditions of a road section in a short time through the proposed prediction framework, especially travel speed prediction. When the car receives the current traffic information about other vehicles, the prediction system will incorporate the information, analyse the data and predict the traffic conditions of this road section for a future time. The design does not depend on any roadside communications infrastructure. It is a simple and flexible car communication and processing technology to collect real-time traffic information. This process will be aided by car to car wireless communication technology available nowadays. To achieve this goal, a mobility model adapted to VANET needs to be generated that a realistic city scenario based on the actual traffic traces is carried out through simulation. Based on this, we investigate the necessary influencing factors for predicted results. The simulation results illustrate that the prediction model can be applied to wireless network environment for a short time prediction, and our results demonstrate the viability and effectiveness of the proposed prediction framework over Car to Car communications. Furthermore, the wireless environment and derived factors can result in decreased application performance

Cooperative control of autonomous connected vehicles from a Networked Control perspective: Theory and experimental validation

Formation control of autonomous connected vehicles is one of the typical problems addressed in the general context of networked control systems. By leveraging this paradigm, a platoon composed by multiple connected and automated vehicles is represented as one-dimensional network of dynamical agents, in which each agent only uses its neighboring information to locally control its motion, while it aims to achieve certain global coordination with all other agents. Within this theoretical framework, control algorithms are traditionally designed based on an implicit assumption of unlimited bandwidth and perfect communication environments. However, in practice, wireless communication networks, enabling the cooperative driving applications, introduce unavoidable communication impairments such as transmission delay and packet losses that strongly affect the performances of cooperative driving. Moreover, in addition to this problem, wireless communication networks can suffer different security threats. The challenge in the control field is hence to design cooperative control algorithms that are robust to communication impairments and resilient to cyber attacks. The work aim is to tackle and solve these challenges by proposing different properly designed control strategies. They are validated both in analytical, numerical and experimental ways. Obtained results confirm the effectiveness of the strategies in coping with communication impairments and security vulnerabilities

A Framework for Incident Detection and notification in Vehicular Ad-Hoc Networks

The US Department of Transportation (US-DOT) estimates that over half of all congestion events are caused by highway incidents rather than by rush-hour traffic in big cities. The US-DOT also notes that in a single year, congested highways due to traffic incidents cost over $75 billion in lost worker productivity and over 8.4 billion gallons of fuel. Further, the National Highway Traffic Safety Administration (NHTSA) indicates that congested roads are one of the leading causes of traffic accidents, and in 2005 an average of 119 persons died each day in motor vehicle accidents. Recently, Vehicular Ad-hoc Networks (VANET) employing a combination of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) wireless communication have been proposed to alert drivers to traffic events including accidents, lane closures, slowdowns, and other traffic-safety issues. In this thesis, we propose a novel framework for incident detection and notification dissemination in VANETs. This framework consists of three main components: a system architecture, a traffic incident detection engine and a notification dissemination mechanism. The basic idea of our framework is to collect and aggregate traffic-related data from passing cars and to use the aggregated information to detect traffic anomalies. Finally, the suitably filtered aggregated information is disseminated to alert drivers about traffic delays and incidents. The first contribution of this thesis is an architecture for the notification of traffic incidents, NOTICE for short. In NOTICE, sensor belts are embedded in the road at regular intervals, every mile or so. Each belt consists of a collection of pressure sensors, a simple aggregation and fusion engine, and a few small transceivers. The pressure sensors in each belt allow every message to be associated with a physical vehicle passing over that belt. Thus, no one vehicle can pretend to be multiple vehicles and then, is no need for an ID to be assigned to vehicles. Vehicles in NOTICE are fitted with a tamper-resistant Event Data Recorder (EDR), very much like the well-known black-boxes onboard commercial aircraft. EDRs are responsible for storing vehicles behavior between belts such as acceleration, deceleration and lane changes. Importantly, drivers can provide input to the EDR, using a simple menu, either through a dashboard console or through verbal input. The second contribution of this thesis is to develop incident detection techniques that use the information provided by cars in detecting possible incidents and traffic anomalies using intelligent inference techniques. For this purpose, we developed deterministic and probabilistic techniques to detect both blocking incidents, accidents for examples, as well as non-blocking ones such as potholes. To the best of our knowledge, our probabilistic technique is the first VANET based automatic incident detection technique that is capable of detecting both blocking and non blocking incidents. Our third contribution is to provide an analysis for vehicular traffic proving that VANETs tend to be disconnected in many highway scenarios, consisting of a collection of disjoint clusters. We also provide an analytical way to compute the expected cluster size and we show that clusters are quite stable over time. To the best of our knowledge, we are the first in the VANET community to prove analytically that disconnection is the norm rather than the exceptions in VANETs. Our fourth contribution is to develop data dissemination techniques specifically adapted to VANETs. With VANETs disconnection in mind, we developed data dissemination approaches that efficiently propagate messages between cars and belts on the road. We proposed two data dissemination techniques, one for divided roads and another one for undivided roads. We also proposed a probabilistic technique used by belts to determine how far should an incident notification be sent to alert approaching drivers. Our fifth contribution is to propose a security technique to avoid possible attacks from malicious drivers as well as preserving driver\u27s privacy in data dissemination and notification delivery in NOTICE. We also proposed a belt clustering scheme to reduce the probability of having a black-hole in the message dissemination while reducing also the operational burden if a belt is compromised