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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 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 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 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 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 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 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 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 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 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 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 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 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.