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Abstract After a severe lane change, a wind gust, or another disturbance, the driver might be unable to recover the intended motion. Even though this fact is known by any driver, the scientific investigation and testing on this phenomenon is just at its very beginning, as a literature review, focusing on SAE Mobilus® database, reveals. We have used different mathematical models of car and driver for the basic description of car motion after a disturbance. Theoretical topics such as nonlinear dynamics, bifurcations, and global stability analysis had to be tackled. Since accurate mathematical models of drivers are still unavailable, a couple of driving simulators have been used to assess human driving action. Classic unstable motions such as Hopf bifurcations were found. Such bifurcations seem almost disregarded by automotive engineers, but they are very well-known by mathematicians. Other classic unstable motions that have been found are “unstable limit cycles.”

Abstract The exponentially growing electrification market is driving demand for lithium-ion batteries (LIBs) with high performance. However, LIB thermal runaway events are one of the unresolved safety concerns. Thermal runaway of an individual LIB can cause a chain reaction of runaway events in nearby cells, or thermal propagation, potentially causing significant battery fires and explosions. Such a safety issue of LIBs raises a huge concern for a variety of applications including electric vehicles (EVs). With increasingly higher energy-density battery technologies being implemented in EVs to enable a longer driving mileage per charge, LIB safety enhancement is becoming critical for customers. This comprehensive review offers an encompassing overview of prevalent abuse conditions, the thermal event processes and mechanisms associated with LIBs, and various strategies for suppression, prevention, and mitigation.

Abstract The cooperative platoon of multiple trucks with definite proximity has the potential to enhance traffic safety, improve roadway capacity, and reduce fuel consumption of the platoon. To investigate the truck platooning performance in a real-world environment, two Peterbilt class-8 trucks equipped with cooperative truck platooning systems (CTPS) were deployed to conduct the first-of-its-kind on-road commercial trial in Canada. A total of 41 CTPS trips were carried out on Alberta Highway 2 between Calgary and Edmonton during the winter season in 2022, 25 of which were platooning trips with 3 to 5 sec time gaps. The platooning trips were performed at ambient temperatures from −24 to 8°C, and the total truck weights ranged from 16 to 39 tons. The experimental results show that the average time gap error was 0.8 sec for all the platooning trips, and the trips with the commanded time gap of 5 sec generally had the highest variations.

Abstract The electrically interconnected suspension (EIS) is a novel suspension system that has gained attention due to its potential to improve vehicle vibration control. This article provides a comprehensive review of EIS and related technologies. It starts with an overview of the research on hydraulic interconnected suspension (HIS) and its limitations. Then, it discusses the development of the electromagnetic suspension (EMS) and its advantages in adjusting mechanical characteristics. The article focuses on the electrical network and decoupling control characteristics of EIS, demonstrating the principle of synchronous decoupling control of multiple vibration modes. A comparison of the structure and control characteristics of EIS and HIS highlights the advantages of EIS in vehicle vibration control.

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract This article explores the value of simulation for autonomous-vehicle research and development. There is ample research that details the effectiveness of simulation for training humans to fly and drive. Unfortunately, the same is not true for simulations used to train and test artificial intelligence (AI) that enables autonomous vehicles to fly and drive without humans. Research has shown that simulation “fidelity” is the most influential factor affecting training yield, but psychological fidelity is a widely accepted definition that does not apply to AI because it describes how well simulations engage various cognitive functions of human operators. Therefore, this investigation reviewed the literature that was published between January 2010 and May 2022 on the topic of simulation fidelity to understand how researchers are defining and measuring simulation fidelity as applied to training AI.

Abstract ERRATUM

Abstract A comprehensive literature review of the optimization techniques used for the process parameter optimization of Abrasive Jet Machining (AJM), Ultrasonic Machining (USM), Laser Beam Machining (LBM), Electrochemical Machining (ECM), and Plasma Arc Machining (PAM) are presented in this review article. This review article is an extension of the review work carried out by previous researchers for the process parameter optimization of non-traditional machining processes using various advanced optimization algorithms. The review period considered for the same is from 2012 to 2022. The prime motive of this review article is to find out the sanguine effects of various optimization techniques used for the optimization of various considered objectives of selected non-traditional machining processes in addition to deemed materials and foremost process parameters.

Abstract The engineering of vehicular systems is becoming increasingly difficult, mainly due to the ongoing integration of cyber-physical systems (CPS) aiming to automate difficult tasks or provide additional features to drivers. This automation potential leads to increasing complexity when engineering the vehicle itself or its subcomponents. In particular the development of a future-oriented kind of mobility, namely, connected autonomous vehicles (CAVs), is accompanied by new challenges, leading back to the different domains to be considered. To cope with this complexity and enable the mutual engineering of vehicular embedded systems, the Software Platform Embedded Systems (SPES) framework provides viewpoints and hierarchy layers in the shape of a matrix. However, to address all domains considered during the development of CAVs, the SPES methodology lacks specifications of how to model such vehicles across multiple domains, which impede its utilization in actual industrial projects.

Abstract Vehicular communications face unique security issues in wireless communications. While new vehicles are equipped with a large set of communication technologies, product life cycles are long and software updates are not widespread. The result is a host of outdated and unpatched technologies being used on the street. This has especially severe security impacts because autonomous vehicles are pushing into the market, which will rely, at least partly, on the integrity of the provided information. We provide an overview of the currently deployed communication systems and their security weaknesses and features to collect and compare widely used security mechanisms. In this survey, we focus on technologies that work in an ad hoc manner. This includes Long-Term Evolution mode 4 (LTE-PC5), Wireless Access in Vehicular Environments (WAVE), Intelligent Transportation Systems at 5 Gigahertz (ITS-G5), and Bluetooth.

Abstract Vehicle to Everything (V2X) allows vehicles, pedestrians, and infrastructure to share information for the purpose of preventing accidents, enhancing road safety, and improving the efficiency and energy consumption of transportation. Although V2X messages are authenticated, their content is not validated. Sensor errors or adversarial attacks can cause messages to be perturbed and, therefore, increase the likelihood of traffic jams, compromise the decision process of other vehicles, or provoke fatal crashes. In this article, we introduce V2X Core Anomaly Detection System (VCADS), a system based on the theory presented in [1] and built for the fields provided in the periodic messages shared across vehicles (i.e., Basic Safety Messages, BSMs). VCADS uses physics-based models to constrain the values in each field and detect anomalies by finding the numerical difference between a field and independent derivations of the same field.

Abstract Renewable energy sources provide an excellent opportunity for state departments of transportation (DOTs) to benefit from a dual use of land while providing flexible, resilient, affordable, and environmentally responsible modes of generation. Solar photovoltaic (PV) systems are particularly useful in this regard. This study presents a literature review on the types of solar project partnerships, application of solar PV systems by DOTs in the United States (U.S.), solar energy potential, energy policies, and incentives in Virginia. In addition, a feasibility assessment of installing solar PV systems at six (6) Virginia DOT (VDOT)-owned sites is presented. The review of the literature indicated that twenty state DOTs have implemented or are developing solar projects using their facilities. The feasibility assessment showed the benefits of installing solar PV systems at VDOT facilities.

Abstract The innovations of vehicle connectivity have been increasing dramatically to enhance the safety and user experience of driving, while the rising numbers of interfaces to the external world also bring security threats to vehicles. Many security countermeasures have been proposed and discussed to protect the systems and services against attacks. To provide an overview of the current states in this research field, we conducted a systematic mapping study (SMS) on the topic area “security countermeasures of in-vehicle communication systems.” A total of 279 papers are identified based on the defined study identification strategy and criteria. We discussed four research questions (RQs) related to the security countermeasures, validation methods, publication patterns, and research trends and gaps based on the extracted and classified data. Finally, we evaluated the validity threats and the whole mapping process.

Abstract Aluminum boron carbide (Al-B4C) composites have been a popular choice among scientists and designers for high-performance strength-to-weight ratio engineering applications. Requirements for such applications are met due to enhanced microstructure, mechanical properties, and ease of processing conditions. The performance and application of these composites are mostly dependent on certain parameters, like composition ratios of reinforcing particles, their sizes and wettability, the presence of additional phases, etc. Prominently, efforts are also being made to synthesize Al-B4C as functionally graded materials (FGMs) that have the potential to cater to the needs of advanced engineering applications and can facilitate new dimensions in the field of aluminum matrix composites (AMCs).

Abstract The electric vehicle market is expected to put a large strain on the existing electricity grid. Additionally, the majority of grid electricity is produced from the combustion of fossil fuels, negating the environmental benefits of electric vehicles. As such, it is necessary to evaluate the “green” options that will allow electric vehicles to break away from the grid—solar power. Solar power uses photovoltaic cells to convert sunlight into electricity, which can then go into recharging a car’s battery. Its existing usage has been limited due to cost and efficiency concerns; however, recent improvements in technology have made them viable. In particular, new materials have driven the cost down to $0.30 per Watt. Meanwhile, different thin-cell silicon materials are achieving efficiencies in excess of 20%. This article evaluates these advances and analyzes the applicability of solar-power for vehicles.

Abstract Electrochemical impedance spectroscopy (EIS) is widely used to diagnose the state of health (SOH) of lithium-ion batteries. One of the essential steps for the diagnosis is to analyze EIS with an equivalent circuit model (ECM) to understand the changes of the internal physical and chemical processes. Due to numerous equivalent circuit elements in the ECM, existing parameter identification methods often fail to meet the requirements in terms of identification accuracy or convergence speed. Therefore, this article proposes a novel impedance model parameter identification method based on the random mutation differential evolution (RMDE) algorithm. Compared with methods such as nonlinear least squares, it does not depend on the initial values of the parameters. The method is compared with chaos particle swarm optimization (CPSO) algorithm and genetic algorithm (GA), showing advantages in many aspects.

Abstract The development of electrification, industrial intelligence, and interconnectivity has driven the transformation of the automobile from a mechanical to an intelligent product. Automobiles have gradually changed from a closed system to an open environment. Therefore, a variety of security threats and attack surfaces are emerging. Hackers or attackers can illegally access and control vehicles through external interfaces such as Bluetooth, Wi-Fi, and cellular. Automotive cybersecurity issues are becoming more prominent than ever. SAE J3061 and ISO/SAE 21434 being drafted also indicate that automotive cybersecurity has been elevated to a position equal to or more important than functional safety. Security threat analysis helps the development of the early concept phase of automotive cybersecurity. However, the threat analysis based on the traditional attack tree has the disadvantages of multiple subjective factors and low accuracy.

Abstract Expert perceptions have been increasingly used to perform risk assessments in airport predictive risk assessments in recent years. Although it is known that biases are less influential in groups of experts when compared to laypeople, they still can be residually present in such tasks with this specific group. Therefore, this article aims to propose (1) the pragmatic organization of knowledge about the biases that may affect airport risk assessments by groups of experts and (2) which of them most often arise in this type of analysis and at what intensity. For the development of the work, we carried out a dense bibliographic review of the theme. Later, we performed a predictive risk assessment and a survey, with the support of an experienced group of 30 experts from Brazilian regulatory agency and airport operators.

Abstract This article explores a wide variety of energy-saving transportation concepts that exploit the unique characteristics of electric vehicles. The confluence of three emerging concepts in transportation, namely electric vehicles, autonomous navigation, and networked vehicles, is shown to present unprecedented opportunities for the optimization of transportation efficiency, especially for passenger and commercial road vehicles. The article addresses both urban and highway driving situations and some of the associated optimization problems. After the introduction of a suitable powertrain model, several optimization problems of practical importance are formulated. It is shown that if the only term in the cost function is transportation energy, and all other conditions are formulated as constraints, substantial energy cost reductions are possible.

Abstract The Noise, Vibration, and Harshness (NVH) performance of automotive powertrain (PT) mounts involves the PT source vibration, PT mount stiffness, road input, and overall transfer path design. Like safety, performance, and durability driving dynamics, vehicle-level NVH also plays a major contributing factor for electric vehicle (EV) refinement. This article highlights the recent research on PT mounting-related NVH controls on electric cars. This work’s main contribution lies in the comparative study of the internal combustion engine (ICE)-based PT mounting and EV-based PT mounting system (PMS) with specific EV challenges. Various literature on PT mounts from the passive, semi-active, and active mounting systems are studied. The parameter optimization technique for mount stiffness and location by various research papers is summarized to understand the existing methodologies and research gap in EV application.