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

Adaptive routing for intermittently connected mobile ad hoe networks

The vast majority of mobile ad hoc networking research makes a very large assumption: that communication can only take place between nodes that are simultaneously accessible within in the same connected cloud (i.e., that communication is synchronous). In reality, this assumption is likely to be a poor one, particularly for sparsely or irregularly populated environments.In this paper we present the Context-Aware Routing (CAR) algorithm. CAR is a novel approach to the provision of asynchronous communication in partially-connected mobile ad hoc networks, based on the intelligent placement of messages. We discuss the details of the algorithm, and then present simulation results demonstrating that it is possible for nodes to exploit context information in making local decisions that lead to good delivery ratios and latencies with small overheads.</p

How is Big Data Transforming Operations Models in the Automotive Industry: A Preliminary Investigation

Over the years, traditional car makers have evolved into efficient systems integrators dominating the industry through their size and power. However, with the rise of big data technology the operational landscape is rapidly changing with the emergence of the “connected” car. The automotive incumbents will have to harness the opportunities of big data, if they are to remain competitive and deal with the threats posed by the rise of new connected entrants (i.e. Tesla). These new entrants unlike the incumbents have configured their operational capabilities to fully exploit big data and service delivery rather than production efficiency. They are creating experience, infotainment and customized dimensions of strategic advantage. Therefore the purpose of this paper is to explore how “Big Data” will inform the shape and configuration of future operations models and connected car services in the automotive sector. It uses a secondary case study research design. The cases are used to explore the characteristics of the resources and processes used in three big data operations models based on a connected car framework

Assistant Suite

This project was conducted to demonstrate a voice-to-mechanical application from one source to multiple platforms with the use of hardware-to-software technology. The main platforms that are used for implementation is an Amazon Echo Dot, which serves as the voice interceptor to transcribe speech through integrated software hosted within the Amazon Web Services (AWS) cloud network, and a Raspberry Pi microcontroller, which serves as the device which controlled mechanical movements based on what is transcribed from the Echo. The user can speak a command into the Echo to control the movement of one of two RC cars without any physical engagement. The Echo utilizes Wi-Fi to connect to the AWS cloud network to transcribe the speech, which then goes through a series of channels to communicate with a microcontroller that is connected to its own RC car to cause that selected RC car to move in a specified direction. For example, the user can speak a command that says “Alexa, move car A forward for two seconds,” and this will translate to the selected car to motion forward for a total of two seconds. The project also displays the usefulness of being able to speak to multiple microcontrollers connected to separate devices under a single application; this caters to the convenience of not having to close and open separate applications every time a different connection is needed.https://scholarscompass.vcu.edu/capstone/1193/thumbnail.jp

A Structured Approach to Securing the Connected Car

<p>Vehicles of today have become increasingly dependent on software to handle their functionalities. Updating and maintaining the software in vehicles has therefore become a costly process for the automotive industry. By introducing wireless communications to vehicles, vehicular maintenance can greatly be improved and many other new applications can also be brought to the vehicles. However, the vehicle was not designed with security in mind. Since the vehicle is safety-critical, it is vital that such new remote services do not violate the safety and security requirements of the vehicle. Thus, this thesis presents a general approach to securing the connected car and the usefulness of the approach is demonstrated in a vehicular diagnostics scenario.</p> <p>The thesis comes in two main parts. In the first part, we address security mechanisms for the connected car. First, a survey of current mechanisms to secure the in-vehicle networks is made. Then, a description of possible communication methods with vehicles is given and a taxonomy of current entities involved in such communication is presented. The taxonomy is organised in actors, vehicle-to-X communications, network paths, and dependability and security attributes. The usefulness of the taxonomy is demonstrated by two examples.</p> <p>In the second part, we address security with respect to vehicular diagnostics. First, an overall security analysis of the interaction between the connected car and the repair shop is conducted. We find that the most imminent risk in the repair shop is the loss of authentication keys. The loss of such keys allows masquerading attacks against vehicles. To address this problem, we propose a Kerberos-inspired protocol for authentication and authorisation of the diagnostics equipment and a trusted third party is introduced.</p> <p>To conclude, this thesis shows the value of adopting a structured approach to securing the connected car. The approach has been shown to be useful for identifying threats and countermeasures and thus help improving security.</p

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun