A Measurement Based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations

The vehicle-to-vehicle (V2V) propagation channel has significant implications on the design and performance of novel communication protocols for vehicular ad hoc networks (VANETs). Extensive research efforts have been made to develop V2V channel models to be implemented in advanced VANET system simulators for performance evaluation. The impact of shadowing caused by other vehicles has, however, largely been neglected in most of the models, as well as in the system simulations. In this paper we present a shadow fading model targeting system simulations based on real measurements performed in urban and highway scenarios. The measurement data is separated into three categories, line-of-sight (LOS), obstructed line-of-sight (OLOS) by vehicles, and non line-of-sight due to buildings, with the help of video information recorded during the measurements. It is observed that vehicles obstructing the LOS induce an additional average attenuation of about 10 dB in the received signal power. An approach to incorporate the LOS/OLOS model into existing VANET simulators is also provided. Finally, system level VANET simulation results are presented, showing the difference between the LOS/OLOS model and a channel model based on Nakagami-m fading.Comment: 10 pages, 12 figures, submitted to Hindawi International Journal of Antennas and Propagatio

Low-cost communication system for explorer-class underwater remotely operated vehicle

Disaster recovery from underwater earthquake, plane crashes into the sea, and monitoring underwater cables or piping for energy purpose are underwater missions for Remotely Operated Underwater Vehicle (ROV) in ASEAN MATE 2018 Competition. Two essentials factor to perform successfully in this ROV competition are design of an efficient communication protocol system and a low-cost communication hardware. In this research, an optimal communication system between RS-232 serial communication transmission and RS-485 serial communication transmission is developed to obtain the optimal solution. Both communication system is tested in Tech_SAS ROV-Telkom University Indonesia, a microcontroller underwater ROV based which used single microcontroller to control actuator, sensor and communication, and measured the Quality of Services (QoS) for end-to-end delay and packets loss. From the the experiment and evaluation for the two schemes, shows 12.57 ms end-to-end delay, 0% data packet error and $6 RS-485 communication system are the optimal solution for Tech_SAS ROV

LiFi Technology for Vehicle to Vehicle Communication in Poor Weather Conditions

Vehicle-to-vehicle (V2V) communication using LIFI (Light Fidelity) technology under fog conditions is presented. Fog is known as one of the most detrimental atmospheric conditions that causes outdoor optical wireless communications to be unreliable.Vehicle-to-vehicle (V2V) communication using LIFI (Light Fidelity) technology under fog conditions is presented. Fog is known as one of the most detrimental atmospheric conditions that causes outdoor optical wireless communications to be unreliable. The effect of the fog conditions is experimentally analyzed in the LIFI- based V2V system. Recognizing distance between two vehicles, a tail-light color of a vehicle, a high density light-emitting diode (LED) was employed in the experiment. The experimental results demonstrate that the proposed LIFI-based V2V system offers a reliable V2V data transmission over the fog-impaired optical channel with an ultrasonic sensor, even under a heavy fog condition. It is believed that vehicle-to-vehicle (V2V) communications and accurate positioning with submeter error could bring vehicle safety to a different level. However, to this date it is still unclear whether the envisioned V2V standard, dedicated short-range communications, can become available in commercially available vehicle products, while widely available consumer grade GPS receivers do not provide the required accuracy for many safety applications. The combining visible light communications and visible light positioning, we propose the use of smart automotive lighting in vehicle safety systems. These lights would be able to provide the functions of illumination and signaling, reliable communications, and accurate positioning in a single solution. The proposed solution has low complexity and is shown to be scalable in high vehicle density and fast topology changing scenarios. We also present several design guidelines for such a system, based on the results of our analytic and empirical studies. Finally, evaluation of our prototype provides evidence that the system can indeed detect potential risks in advance and provide early warnings to the driver in real-world scenarios, lowering the probability of traffic accidents. Index Terms: Light Fidelity (LIFI), vehicle-to-vehicle (V2V) communication

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

Plug-in Hybrid Vehicles -- A Vision for the Future

One of the unique advantages of plug-in hybrid vehicles is their capability to integrate the transportation and electric power generation sectors in order to improve the efficiency, fuel economy, and reliability of both systems. This goal is performed via integration of the onboard energy storage units of plug-in vehicles with the power grid by power electronic converters and communication systems. Employing energy storage systems improves the efficiency and reliability of the electric power generation, transmission, and distribution. Similarly, combining an energy storage system with the power train of a conventional vehicle results in a hybrid vehicle with higher fuel efficiency. In both cases, the energy storage system is used to provide load leveling. In this paper, viability of utilizing the same energy storage unit for both transportation and power system applications is discussed. Furthermore, future trends in analysis, design, and evaluation of distributed energy storage system for the power grid using power-electronic-intensive interface are identified

Assessing the Competing Characteristics of Privacy and Safety within Vehicular Ad Hoc Networks

The introduction of Vehicle-to-Vehicle (V2V) communication has the promise of decreasing vehicle collisions, congestion, and emissions. However, this technology places safety and privacy at odds; an increase of safety applications will likely result in the decrease of consumer privacy. The National Highway Traffic Safety Administration (NHTSA) has proposed the Security Credential Management System (SCMS) as the back end infrastructure for maintaining, distributing, and revoking vehicle certificates attached to every Basic Safety Message (BSM). This Public Key Infrastructure (PKI) scheme is designed around the philosophy of maintaining user privacy through the separation of functions to prevent any one subcomponent from identifying users. However, because of the high precision of the data elements within each message this design cannot prevent large scale third-party BSM collection and pseudonym linking resulting in privacy loss. In addition, this philosophy creates an extraordinarily complex and heavily distributed system. In response to this difficulty, this thesis proposes a data ambiguity method to bridge privacy and safety within the context of interconnected vehicles. The objective in doing so is to preserve both Vehicle-to-Vehicle (V2V) safety applications and consumer privacy. A Vehicular Ad-Hoc Network (VANET) metric classification is introduced that explores five fundamental pillars of VANETs. These pillars (Safety, Privacy, Cost, Efficiency, Stability) are applied to four different systems: Non-V2V environment, the aforementioned SCMS, the group-pseudonym based Vehicle Based Security System (VBSS), and VBSS with Dithering (VBSS-D) which includes the data ambiguity method of dithering. By using these evaluation criteria, the advantages and disadvantages of bringing each system to fruition is showcased

Voice-controlled in-vehicle infotainment system

Abstract. Speech is a form of a human to human communication that can convey information in a context-rich way that is natural to humans. The naturalness enables us to speak while doing other things, such as driving a vehicle. With the advancement of computing technologies, more and more personal services are introduced for the in-vehicle environment. A limiting factor for these advancements is the impact they cause towards driver distraction with the increased cognitive stress load. This has led to developing in-vehicle devices and applications with a heightened focus on lessening distraction. Amazon Alexa is a natural language processing system that enables its users to receive information and operate smart devices with their voices. This Master’s thesis aims to demonstrate how Alexa could be utilized when operating the in-vehicle infotainment (IVI) systems. This research was conducted by utilizing the design science research methodology. The feasibility of voice-based interaction was assessed by implementing the system as a demonstrable use-case in collaboration with the APPSTACLE project. Prior research was gathered by conducting a literature review on voice-based interaction and its integration to the vehicular domain. The system was designed by applying existing theories together with the requirements of the application domain. The designed system utilized the Amazon Alexa ecosystem and AWS services to provide the vehicular environment with new functionalities. Access to cloud-based speech processing and decision-making makes it possible to design an extendable speech interface where the driver can carry out secondary tasks by using their voice, such as requesting navigation information. The evaluation was done by comparing the system’s performance against the derived requirements. With the results of the evaluation process, the feasibility of the system could be assessed against the objectives of the study: The resulting artefact enables the user to operate the in-vehicle infotainment system while focusing on a separate task. The research proved that speech interfaces with modern technology can improve the handling of secondary tasks while driving, and the resulting system was operable without introducing additional distractions to the driver. The resulting artefact can be integrated into similar systems and used as a base tool for future research on voice-controlled interfaces