VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

Public safety application for approaching emergency vehicle alert and accident reporting in VANETs using WAVE

Today\u27s transport system has evolved from horse driven carriages and paved roads to a more complex road transport system made up of a variety of vehicles and other infrastructure, all put in place in order to support safe and efficient mobility of vehicles. The next step to further improve the transportation system of today is to make the vehicles and roadside infrastructure more intelligent by making them communicate with each other. This new ability will help find new solutions to current problems like traffic congestion, vehicular collisions, monitoring of adherence to traffic rules and alerting the drivers of hazardous conditions. Vehicular Ad-Hoc Networks (VANETs) are vehicle to vehicle and vehicle to road side infrastructure networks which make this possible by providing support to numerous applications aimed towards improving safety and driving experience on the road. A Public Safety VANET application adhering to the IEEE Wireless Access in Vehicular Environments (WAVE) standard and requirements laid down by National Highway Traffic Safety Administration (NHTSA) was designed, implemented, simulated and tested over a scalable open-sourced test bed aimed towards simulating a complete Intelligent Transportation System consisting of various applications operating together. The application supports two features: Approaching Emergency Vehicle Alert: An Approaching Public Safety Vehicle (Police/Fire/EMS) in a state of emergency will alert the vehicles in its path using the VANET, causing them to give way. Post-Crash Warning: A vehicle involved in a crash will immediately alert approaching vehicles about its current state using the VANET, helping them come to a halt at a safe distance, hence avoiding pileups. The performance and adherence to the requirements was analyzed, and a demonstration of the system was prepared to showcase the application in action

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

A content dissemination framework for vehicular networking

Vehicular Networks are a peculiar class of wireless mobile networks in which vehicles are equipped with radio interfaces and are, therefore, able to communicate with fixed infrastructure (if available) or other vehicles. Content dissemination has a potential number of applications in vehicular networking, including advertising, traffic warnings, parking notifications and emergency announcements. This thesis addresses two possible dissemination strategies: i) Push-based that is aiming to proactively deliver information to a group of vehicles based on their interests and the level of matching content, and ii) Pull-based that is allowing vehicles to explicitly request custom information. Our dissemination framework is taking into consideration very specific information only available in vehicular networks: the geographical data produced by the navigation system. With its aid, a vehicle's mobility patterns become predictable. This information is exploited to efficiently deliver the content where it is needed. Furthermore, we use the navigation system to automatically filter information which might be relevant to the vehicles. Our framework has been designed and implemented in .NET C# and Microsoft MapPoint. It was tested using a small number of vehicles in the area of Cambridge, UK. Moreover, to prove the correctness of our protocols, we further evaluated it in a large-scale network simulation over a number of realistic vehicular trace-based scenarios. Finally, we built a test-case application aiming to prove that vehicles can gain from such a framework. In this application every vehicle collects and disseminates road traffic information. Vehicles that receive this information can individually evaluate the traffic conditions and take an alternative route, if needed. To evaluate this approach, we collaborated with UCLA's Network Research Lab (NRL), to build a simulator that combines network and dynamic mobility emulation simultaneously. When our dissemination framework is used, the drivers can considerably reduce their trip-times

Network Routing Using the Network Tasking Order, a Chron Approach

This thesis promotes the use of the network tasking order (NTO), in collaboration with the air tasking order (ATO), to optimize routing in Mobile Ad hoc Networks (MANET). The network topology created by airborne platforms is determined ahead of time and network transitions are calculated offline prior to mission execution. This information is used to run maximum multi-commodity flow algorithms offline to optimize network flow and schedule route changes for each network node. These calculations and timely route modifications increases network efficiency. This increased performance is critical to command and control decision making in the battlefield. One test scenario demonstrates near a 100% success rate when route scheduling and splitting network traffic over an emulated MANET compared to Open Shortest Path First (OSPF) which only achieved around a 71% success rate, and Mesh Made Easy (MME) which achieved about 50% success. Another test scenario demonstrates that the NTO can experience degradation due to schedule delay. Overall, if executed and planned properly, the NTO can significantly improve network Quality of Service (QoS)

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information