Probabilistic network coding techniques for vehicular ad-hoc networks

vehicular ad hoc network (vanet) is an emerging technology that enables moving vehicles on the road to connect and communicate as network devices. vanets enhance roads safety measures and improve traffic efficiency. however, due to the lack of centralization and the large number of highly mobile nodes, vanets are considered as highly congested networks with significant packet collisions and retransmissions. on the other hand, network coding is an emerging technique known to effectively utilize network resources by significantly reducing the number of transmissions. in network coding, intermediate nodes minimize the number of transmission by combining different packets before transmitting. however, a fundamental problem for network coding relay when it receives a packet is whether to wait for a coding opportunity to reduce network congestion; or to send the packet immediately without coding to reduce packet delay. this thesis proposes network coding techniques to reduce the number of transmissions and the bandwidth consumption in vanet multi-hop scenario. it also presents an analytical study on the trade-off between the average packet delay and the network throughput in network coding. it proposes a probabilistic approach for the intermediate nodes and therefore develops an analytical framework to present the effect of using such technique on the network performance. the system stability conditions have also been investigated. moreover, flows with different and same priorities are considered and different mechanisms that consider the nature of the different applications are proposed. for fair delay, this thesis provides the optimum transmission probability which achieves the minimum fair delay and results in an optimum throughput. while for different priority flows, a queue state based probabilistic scheduling schemes are proposed to avoid unbounded packet delays. to highlight the result, for symmetric rate flows, fairness scheme shows that the optimum fair delay can be achieved with probability of transmission of 0.5. it also shows that despite the flow data rate, using this probability will result in 33% improvement in the bandwidth consumption, and in an equal hop delay for both flows that is 0.5/?, where ? is the average flow data rate. moreover, for asymmetric rate flows the work provides the optimum transmission probability and its corresponding fair delay and throughput improvement. simulation is carried out to verify the analytical results where it is closely matched the theoretical results

Real time collision warning system in the context of vehicle-to-vehicle data exchange based on drivings behaviours analysis

Worldwide injuries in vehicle accidents have been on the rise in recent years, mainly due to driver error regardless of technological innovations and advancements for vehicle safety. Consequently, there is a need for a reliable-real time warning system that can alert drivers of a potential collision. Vehicle-to-Vehicle (V2V) is an extensive area of ongoing research and development which has started to revolutionize the driving experience. Driving behaviour is a subject of extensive research which gains special attention due to the relationship between speeding behaviour and crashes as drivers who engage in frequent and extreme speeding behaviour are overinvolved in crashes. National Highway Traffic Safety Administration (NHTSA) set guidelines on how different vehicle automation levels may reduce vehicle crashes and how the use of on-board short-range sensors coupled with V2V technologies can help facilitate communication among vehicles. Based on the previous works, it can be seen that the assessment of drivers’ behaviours using their trajectory data is a fresh and open research field. Most studies related to driving behaviours in terms of acceleration�deceleration are evaluated at the laboratory scale using experimental results from actual vehicles. Towards this end, a five-stage methodology for a new collision warning system in the context of V2V based on driving behaviours has been designed. Real-time V2V hardware for data collection purposes was developed. Driving behaviour was analyzed in different timeframes prior obtained from actual driving behaviour in an urban environment collected from OBD-II adapter and GPS data logger of an instrumented vehicle. By measuring the in-vehicle accelerations, it is possible to categorize the driving behaviour into four main classes based on real-time experiments: safe drivers, normal, aggressive, and dangerous drivers. When the vehicle is in a risk situation, the system based on NRF24L01+PA/LNA, GPS, and OBD-II will pass a signal to the driver using a dedicated LCD and LED light signal. The driver can instantly decide to make the vehicle in a safe mood, effectively avoid the happening of vehicle accidents. The proposed solution provides two main functions: (1) the detection of the dangerous vehicles involved in the road, and (2) the display of a message informing the driver if it is safe or unsafe to pass. System performance was evaluated to ensure that it achieved the primary objective of improving road safety in the extreme behaviour of the driver in question either the safest (or the least aggressive) and the most unsafe (or the most aggressive). The proposed methodology has retained some advantages for other literature studies because of the simultaneous use of speed, acceleration, and vehicle location. The V2V based on driving behaviour experiments shows the effectiveness of the selected approach predicts behaviour with an accuracy of over 87% in sixty-four real-time scenarios presented its capability to detect behaviour and provide a warning to nearby drivers. The system failed detection only in few times when the receiving vehicle missed data due to high speed during the test as well as the distances between the moving vehicles, the data was not received correctly since the power transmitted, the frequency range of the signals, the antenna relative positions, and the number of in-range vehicles are of interest for the V2V test scenarios. The latter result supports the conclusion that warnings that efficiently and quickly transmit their information may be better when driver are under stress or time pressure

Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encour-aging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility‐as‐a‐service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope