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Inter-vehicle communication (IVC) is the next step in developing a coordinated vehicular transportation system. With today's concerns of security in Internet communications, it is critical that the security in IVC be considered. With its many life-depending implications it is crucial that an IVC system be tolerant of both natural and man-made interference. The goal of our research was to explore solutions to address the issues of security of IVC in spite of its vulnerability to Denial-of- Service (DoS) attacks, in which an attacker systematically or selectively jams the signals exchanged by the vehicles. We present proposed solutions to DoS attacks on IVC, as well as introduce additional concepts and ideas that help address this important problem.

Robert Bosch GmBH proposed in 2012 a new version of communication protocol named as Controller area network with Flexible Data-Rate (CANFD), that supports data frames up to 64 bytes compared to 8 bytes of CAN. With limited data frame size of CAN message, and it is impossible to be encrypted and secured. With this new feature of CAN FD, we propose a hardware design - CAN crypto FPGA chip to secure data transmitted through CAN FD bus by using AES-128 and SHA-1 algorithms with a symmetric key. AES-128 algorithm will provide confidentiality of CAN message and SHA-1 algorithm with a symmetric key (HMAC) will provide integrity and authentication of CAN message. The design has been modeled and verified by using Verilog HDL – a hardware description language, and implemented successfully into Xilinx FPGA chip by using simulation tool ISE (Xilinx).

Lane line detection is a very critical element for Advanced Driver Assistance Systems (ADAS). Although, there has been significant amount of research dedicated to the detection and localization of lane lines in the past decade, there is still a gap in the robustness of the implemented systems. A major challenge to the existing lane line detection algorithms stems from coping with bad weather conditions (e.g. rain, snow, fog, haze, etc.). Snow offers an especially challenging environment, where lane marks and road boundaries are completely covered by snow. In these scenarios, on-board sensors such as cameras, LiDAR, and radars are of very limited benefit. In this research, the focus is on solving the problem of improving robustness of lane line detection in adverse weather conditions, especially snow. A framework is proposed that relies on using Vehicle-to-Infrastructure (V2I) communication to access reference images stored in the cloud.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

The assembling accuracy of two contactors during the relay switch production is an important factor affecting the quality of relay. An embedded machine vision quality Inspection system has been developed for electric relay production line inspection. The proposed system can provide online feedback on the quality of the relays by measuring the distance of the gap between the contacts of them. Two CMOS imaging sensors are operated for image acquisition and the parallel working mode is realized under dual-channel mode. A red light illumination system has been adopted to eliminate the imaging noise from the reflection of the surfaces of copper sheet. Before the test, the features areas in the image of same type relay is selected as template and saved in the computer. During the inspection procedure, a rotation invariance detection scheme based on circular projection matching algorithm has been used for fast recognizing and locating detected object with the help of these feature areas.

Traditional Heat Ventilation and Air Conditioning (HVAC) control systems are reactive by design and largely dependent on the on-board sensory data available on a Controller Area Network (CAN) bus. The increasingly common Internet connectivity offered in today's vehicles, through infotainment and telematic systems, makes data available that may be used to improve current HVAC systems. This includes real-time outside relative humidity, ambient temperature, precipitation (i.e., rain, snow, etc.), and weather forecasts. This data, combined with position and route information of the vehicle, may be used to provide a more comfortable experience to vehicle occupants in addition to improving driver visibility through more intelligent humidity, and defrost control. While the possibility of improving HVAC control utilizing internet connectivity seems obvious, it is still currently unclear as to what extent.

A low profile wideband Planar Inverted-F antenna (PIFA) is presented in this paper for automotive application in the sub-6 GHz 5G system and Dedicated Short Range Communication (DSRC) bands that operates in the frequency range from 617 MHz to 6 GHz while having an acceptable rejection in the GNSS bands. The proposed antenna is suitable for low profile applications in the automotive industry due to its physical dimensions and performance. Simulation results are presented along with measured data on a ground plane (GND) and on a vehicle from properly cut metal sheet prototype. The results are discussed in terms of return loss, radiation patterns, and efficiency.