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The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

A new inter-disciplinary degree program has been developed at Lawrence Technological University: the Master of Science in Mechatronic Systems Engineering Degree (MS/MSE). It is one of a few MS-programs in mechatronics in the U.S.A. today. This inter-disciplinary program reflects the main areas of ground vehicle mechatronic systems and robotics. This paper presents areas of scientific and technological principles which the Mechanical Engineering, Electrical and Computer Engineering, and Math and Computer Science Departments bring to Mechatronic Systems Engineering and the new degree program. New foundations that make the basis for the program are discussed. One of the biggest challenges was developing foundations for mechanical engineering in mechatronic systems design and teaching them to engineers who have different professional backgrounds. The authors first developed new approaches and principles to designing mechanical subsystems as components of mechatronic systems.

In this paper, we proposed a distributed Engineering Computer Aided Learning System. Instead of attending engineering teaching sessions, engineering students are able to interact with the software to gain the same amount of teaching materials. Besides, they will interact with other engineering students from other Engineering schools. The proposed software has the ability to examine the student step by step to reach certain goals. The training and the examination will be different based on the student level and his learning process. Using this system the role of excellent professor can be achieved. The software will have two sessions, i.e. test session and learning session. The software provides the capability of knowledge sharing between multi schools and different educational systems that can provide the students with a large set of training materials. The system was built using JAVA programming language.

The demand for drive-by-wire, pre-crash warning and many other new features will require high bandwidth from the future in-vehicle networks. One way to satisfy the high bandwidth requirement of future vehicles is to use a higher bandwidth bus or multiple busses. However, the use of a higher bandwidth bus will increase the cost of the network. Similarly, the use of multiple buses will increase cost as well as the complexity of wiring. Thus, neither option is a viable solution. Another option could be the development of a higher layer protocol to reduce the amount of data to be transferred. The higher layer protocol could be acceptable provided it does not increase the message latencies. The cost of implementing the protocol will be marginal because it can be done by making changes in software. Various data reduction protocols are available in the literature. We have made changes in the existing data reduction protocols to improve the performance of the protocol.

In future, updating various software modules in vehicles on a regular basis will be required for various reasons such as update functionalities in the existing system, add new functionalities, remove software bugs, update navigation map etc. For updating software to a large number of vehicles, remote updating using mobile multicasting would be the most efficient and economic than unicast updating in service station. However, the security requirement of multicast communication, i.e., confidentiality and integrity of the information transmitted and authenticity of the group members, is challenging. In this paper, we investigate issues in designing key management architectures for secure multicast network, particularly for remote software update in future vehicles. Vehicular software distribution network is considered as wireless network where vehicles are connected to the software distributors through base stations.

The purpose of the Institute for Manufacturing Research (IMR) is to enhance Wayne State University's existing technological strength in the areas of manufacturing research which have demonstrated potential benefits for the State's economy. IMR's faculty conduct basic and applied research in selected areas of manufacturing science. The research programs within the Institute are broadly interdisciplinary and industrially interactive, and are organized around the following areas: materials development, modification, and nondestructive evaluation; software technology for manufacturing and engineering; and product reliability and machine tool research. Faculty from eight departments within the Colleges of Science and Engineering participate in IMR.

Microprocessors and microcontrollers are now widely used in automobiles. Microprocessor systems contain sources of interrupt and interrupt service routines, which are software components executed in response to the assertion of an interrupt in hardware. A major problem in designing the software of microprocessor systems is the analytical treatment of interrupt latency. Because multiple interrupt service routines are executed on the same CPU, they compete for the CPU and interfere with each other's latency requirements. Here, interrupt latency is defined as the delay between the assertion of the interrupt in hardware and the start of execution of the associated interrupt service routine. It is estimated that 80% of intermittent bugs in small microprocessor software loads are due to improper treatment of interrupts. Until this work, there is no analytic method for analyzing a particular system to determine if it may violate interrupt latency requirements.

Artificial Intelligence (A.I.) and Big Data are increasing become more applicable in the development of technology from machine design and mobility to bio-printing and drug discovery. The ability to quantify large amounts of data these systems generate will be paramount to establishing a robust infrastructure for interdisciplinary autonomous applications. This paper purposes an integrated approach to the environment, pre/post data processing, integration, and system security for robust systems in intelligent transportation systems. The systems integration is based on a FPGA embedded system design and computing (EDGE) platform utilizing image processing CNN algorithms from High Energy Physics (HEP) experiments in data centers with associative memory to ROS- FPGA technology in vehicles for hyper-scale infrastructure scalability. The ability to process data in the future is equivalent to collision particle detection that the Large Hadron Collider (LHC) produces at CERN.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.