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Abstract With the adoption of Vehicle-to-everything (V2X) technology, security and privacy of vehicles are paramount. To avoid tracking while preserving vehicle/driver’s privacy, modern vehicular public key infrastructure provision vehicles with multiple short-term pseudonym certificates. However, provisioning a large number of pseudonym certificates can lead to an enormous growth of Certificate Revocation Lists (CRLs) during its revocation process. One possible approach to avoid such CRL growth is by relying on activation code (AC)-based solutions. In such solutions, the vehicles are provisioned with batches of encrypted certificates, which are decrypted periodically via the ACs (broadcasted by the back-end system). When the system detects a revoked vehicle, it simply does not broadcast the respective vehicle’s AC. As a result, revoked vehicles do not receive their respective AC and are prevented from decrypting their certificates.

Abstract Autonomous vehicles (AVs) rely heavily upon their perception subsystems to “see” the environment in which they operate. Unfortunately, the effect of variable weather conditions presents a significant challenge to object detection algorithms, and thus, it is imperative to test the vehicle extensively in all conditions which it may experience. However, the development of robust AV subsystems requires repeatable, controlled testing—while real weather is unpredictable and cannot be scheduled. Real-world testing in adverse conditions is an expensive and time-consuming task, often requiring access to specialist facilities. Simulation is commonly relied upon as a substitute, with increasingly visually realistic representations of the real world being developed.

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 The result is a host of outdated and unpatched technologies being used on the street.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 This article is motivated by observations of the wind tunnel measurement data acquired during benchmarking and program development for a variety of passenger vehicles over the years. In wind noise development, contribution analysis is a common practice to screen and identify the most significant sources and paths. In order to shed light on the whole picture of the contribution analysis, the work presented in this article falls into two categories. One is the analysis of underlying mechanisms for a better understanding of the phenomena observed in the contribution results. The other is the summarization of wind noise contributions obtained by wind tunnel testing for some representative subsystems, e.g., the contributions based on different reference states, the effect of grilles, underbody, acoustic glass, and auditory masking.

Abstract Energy management strategies for charge-sustaining hybrid electric vehicles reduce fuel consumption and maintain battery pack state of charge while meeting driver output power demand. The equivalent consumption minimization strategy is a real-time energy management strategy that makes use of an equivalence ratio to quantify electric power consumption in terms of fuel power consumption. The magnitude of the equivalence ratio determines the hybrid electric vehicle mode of operation and influences the ability of the energy management strategy to reduce fuel consumption as well as maintain the battery pack state of charge. The equivalent consumption minimization strategy in this article uses three Willans line models, which have an associated marginal efficiency and constant offset, to model the performance in the hybrid electric vehicle controller.

Abstract Water quality monitoring is needed for the effective management of water resources. Periodic sampling and regular inspection/analysis allow one to classify water and identify changes or trends in water quality over time. This article presents a novel concept of an Amphibious Hybrid Unmanned Aerial Vehicle (AHUAV) that can operate in air and water for rapid water sampling, real-time water quality analysis, and water body management. A methodology using the developed AHUAV system for water body management has also been proposed for an easier and effective way of monitoring water bodies using advanced drone technologies. Using drones for water body management can be a cost-effective and efficient way of carrying out regular inspections and continual monitoring.

Abstract The importance of in-vehicle network security has increased with an increase in automated and connected vehicles. Hence, many attacks and countermeasures have been proposed to secure the controller area network (CAN), which is an existent in-vehicle network protocol. At the same time, new protocols-such as FlexRay and Ethernet-which are faster and more reliable than CAN have also been proposed. European OEMs have adopted FlexRay as a control network that can perform the fundamental functions of a vehicle. However, there are few studies regarding FlexRay security. In particular, studies on attacks against FlexRay are limited to theoretical studies or simulation-based experiments. Hence, the vulnerability of FlexRay is unclear. Understanding this vulnerability is necessary for the application of countermeasures and improving the security of future vehicles. In this article, we highlight the vulnerability of FlexRay found in the experiments conducted on a real FlexRay network.

Abstract Automated driving as one of the most anticipated technologies is approaching its market release in the near future. Since several years, the research in the automotive industry is largely focused on its development and presents well-engineered prototypes. The many aspects of this development do not only concern the function and its components itself, but also the proof of safety and assessment for its market release. It is clear that previous methods used for the release of Advanced Driver Assistance Systems are not applicable. In contrast to already released systems, automated driving is not restricted to a certain field of application in terms of driving scenarios it has to take action in. This results in an infeasible amount of required testing and unforeseeable scenarios the function can face throughout its lifetime. In this article, we show a scenario-based approach that promises to overcome those challenges.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract A tandem axle suspension is an important system to the ride comfort and vehicle stability of and road damage experience from commercial vehicles. This article introduces an investigation into the use of a controlled active tandem axle suspension, which for the first time enables more effective control using two fuzzy logic controllers (FLC). The proposed controllers compute the actuator forces based on system outputs: displacements, velocities, and accelerations of movable parts of tandem axle suspension as inputs to the controllers, in order to achieve better ride comfort and vehicle stability and extend the lifetime of road surface than the conventional passive suspension. A mathematical model of a six-degree-of-freedom (6-DOF) tandem axle suspension system is derived and simulated using Matlab/Simulink software.

Abstract When the vehicle is under braking condition in the longitudinal motion, the vehicle body will tilt due to the inertial force in motion. A high amplitude will result in uncomfortable feelings of the occupant, such as nervousness or dizziness. To solve the problem, this article presents an adaptive damping system (ADS), which combines the vehicle anti-pitch compensation control with the mixed skyhook (SH) and acceleration-driven-damper (ADD) control algorithm. This ADS can not only improve the vibration effect of the vertical motion for the vehicle but also consider the longitudinal motion of the vehicle body. In addition, a new damper mechanical hardware-in-the-loop test bench is built to verify the effectiveness of the algorithm.

Abstract A critical component of vehicle dynamic control systems is the accurate and real-time knowledge of the vehicle’s key states and parameters when running on the road. Such knowledge is also essential for vehicle closed-loop feedback control. Vehicle state and parameter estimation has gradually become an important way to soft-sense some variables that are difficult to measure directly using general sensors. In this work, a seven degrees-of-freedom (7-DOF) nonlinear vehicle dynamics model is established, where consideration of the Magic formula tire model allows us to estimate several vehicle key states using a hybrid algorithm containing an unscented Kalman filter (UKF) and a genetic algorithm (GA). An estimator based on the hybrid algorithm is compared with an estimator based on just a UKF. The results show that the proposed estimator has higher accuracy and fewer computation requirements than the UKF estimator.

Abstract In this article, a hierarchical coordinated control algorithm for integrating active rear steering and driving/braking force distribution (ARS+D/BFD) was presented. The upper-level control was synthesized to generate the required rear steering angle and external yaw moment by using a sliding-mode controller. In the lower-level controller, a control allocation algorithm considering driving/braking actuators and tire forces constraints was designed to assign the desired yaw moment to the four wheels. To this end, an optimization problem including several equality and inequality constraints were defined and solved analytically. Finally, computer simulation results suggest that the proposed hierarchical control scheme was able to help to achieve substantial enhancements in handling performance and stability.

Abstract Advanced passenger vehicles are complex dynamic systems that are equipped with several actuators, possibly including differential braking, active steering, and semi-active or active suspensions. The simultaneous use of several actuators for integrated vehicle motion control has been a topic of great interest in literature. To facilitate this, a technique known as control allocation (CA) has been employed. CA is a technique that enables the coordination of various actuators of a system. One of the main challenges in the study of CA has been the representation of actuator dynamics in the optimal CA problem (OCAP). Using model predictive control allocation (MPCA), this problem has been addressed. Furthermore, the actual dynamics of actuators may vary over the lifespan of the system due to factors such as wear, lack of maintenance, etc. Therefore, it is further required to compensate for any mismatches between the actual actuator parameters and those used in the OCAP.

Abstract As automated driving technology is evolving quickly and becomes more widely deployed, it is essential to validate the Safety of the Intended Functionality (SOTIF) of Automated Vehicles (AVs) prior to mass production. In general, an exhaustive real-world scenario validation of AVs is considered infeasible due to excessive time consumption. Additionally, simulation tests alone are often regarded as inadequate since it is difficult to model the system and physical properties of vehicles with full fidelity. Therefore, a SOTIF validation method for AVs is proposed in this article, which consists of structure design and scenario determination. A mature, systematic, and complete set of testing and evaluation procedures is presented in structure design, and a scenario generation method is introduced in scenario determination. The SOTIF validation method takes advantage of both simulation tests and on-road tests.

Abstract The crush energy is a key parameter to determine the delta-V in accident reconstructions. Since an accurate car crush profile can be obtained from 3D scanners, this research aims at validating the methods currently used in calculating crush energy from a crush profile. For this validation, a finite element (FE) car model was analyzed using various types of impact conditions to investigate the theory of energy-based accident reconstruction. Two methods exist to calculate the crush energy: the work based on the barrier force and the work based on force calculated by the vehicle acceleration times the vehicle mass. We show that the crush energy calculated from the barrier force was substantially larger than the internal energy calculated from the FE model. Whereas the crush energy calculated from the vehicle acceleration was comparable to the internal energy of the FE model.

Abstract This work introduces the concept of a dual-layer specification structure for standards that separate interoperability functions, such as backward compatibility, localization, and deployment, from those essential to reliability, security, and functionality. The latter group of features, which constitute the actual standard, make up the baseline layer for instructions, while all the elements required for interoperability are specified in a second layer, known as a Protocols, Operations, Usage, and Formats (POUF) document. We applied this technique in the development of a standard for Uptane [1], a security framework for over-the-air (OTA) software updates used in many automobiles. This standard is a good candidate for a dual-layer specification because it requires communication between entities, but does not require a specific format for this communication.

Abstract Connected vehicle (CV) technology has the potential to greatly improve the safety, mobility, and environmental sustainability of traffic. Many CV applications require the vehicle position as input, which is primarily provided by global navigation satellite systems (GNSS). Although a large number of those applications (e.g., Intersection Movement Assist) require vehicle positioning to have lane-level accuracy, it has been shown that the type of positioning system typically used by CVs currently cannot provide consistent lane-level accuracy, even under open-sky conditions. In order to address this gap, we have evaluated an enhanced positioning system that adds little, if any, to the cost of the CV.

Abstract One of the key problems of battery electric vehicles is the risk of severe range reduction in winter conditions. Technologies such as heat pump systems can help to mitigate such effects, but finding adequate heat sources for the heat pump sometimes can be a problem, too. In cold ambient conditions below −10°C and for a cold-soaked vehicle this can become a limiting factor. Storing waste heat or excess cold when it is generated and releasing it to the vehicle thermal management system later can reduce peak thermal requirements to more manageable average levels. In related architectures it is not always necessary to replace existing electric heaters or conventional air-conditioning systems. Sometimes it is more efficient to keep them and support them, instead. Accordingly, we show, how latent heat storage can be used to increase the efficiency of existing, well-established heating and cooling technologies without replacing them.

Abstract This article presents surrogate mixtures that simulate the physical and chemical properties in the auto-ignition of hydrotreated vegetable oil (HVO). Experimental investigation was conducted in the Ignition Quality Tester (IQT) to validate the auto-ignition properties with respect to those of the target fuel. The surrogate development approach is assisted by artificial neural network (ANN) embedded in MATLAB optimization function. Aspen HYSYS is used to calculate the key physical and chemical properties of hundreds of mixtures of representative components, mainly alkanes—the dominant components of HVO, to train the learning algorithm. Binary and ternary mixtures are developed and validated in the IQT. The target properties include the derived cetane number (DCN), density, viscosity, surface tension, molecular weight, and volatility represented by the distillation curve. The developed surrogates match the target fuel in terms of ignition delay and DCN within 6% error range.