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The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).

Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.

The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.

Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

The purpose of this paper is to develop a nonlinear control system for flight trajectory control of flapping Micro Aerial Vehicles (MAVs), subjected to wind.

In the dynamic study and fabrication of the MAV, biomimetic principles are considered as the best inspiration for the MAV's flight as well as design constraints. The blade element theory, which is a two‐dimensional quasi‐steady state method, is modified to consider the effect of MAV's translational and rotational velocity. A quaternion‐based dynamic wrench method is then developed for the dynamic system.

The flapping flight dynamics is highly nonlinear and the system is under‐actuated, so any linear control strategy fails to meet any desired maneuver for trajectory tracking. In this study, a controller with quaternion‐based feedback linearization method is designed for the dynamical averaged system. It is shown that the original system is bonded to a stable limit cycle with desired amplitude and the controller inputs are bounded.

The effectiveness of a synthesized controller is proved for the cruse and the Cuban‐8 maneuver.

The authors' major contribution is developing feedback linearization quaternion‐based controller and deriving some essential mathematics for implementing quaternion model in the synthesis of controller. A piezoelectric‐actuated wing model is developed for the control system. Results of cursing and turning modes of the flight indicate the stability of the flight. Finally, an appropriate controller is designed for the Cuban‐8 maneuver so that the MAV would follow the trajectory with a bounded fluctuation.

This study aims to propose a novel subjective assessment (SA) method for level 2 or level 2+ advanced driver assistance system (ADAS) with a customized case study in China.

The proposed SA method contains six dimensions, including perception, driveability and stability, riding comfort, human–machine interaction, driver workload and trustworthiness and exceptional operating case, respectively. And each dimension subordinates several subsections, which describe the corresponding details under this dimension.

Based on the proposed SA, a case study in China is conducted. Six drivers with different driving experiences are invited to give their subjective ratings for each subsection according to a predefined rating standard. The rating results show that the ADAS from Tesla outperforms the upcoming electric vehicle in most cases.

The proposed SA method is beneficial for the original equipment manufacturers developing related technologies in the future.

The paper aims to identify a suitable generic brake force distribution ratio (β) corresponding to optimal brake design attributes in a diminutive driving range, where road conditions do not exhibit excessive variations. This will intend for an appropriate allocation of brake force distribution (BFD) to provide dynamic stability to the vehicle during braking.

Two techniques are presented (with and without wheel slip) to satisfy both brake stability and performance while accommodating variations in load sharing and road friction coefficient. Based on parametric optimization of the design variables of hydraulic brake using evolutionary algorithm, taking into account both the laden and unladen circumstances simultaneously, this research develops an improved model for computing and simulating the BFD applied to commercial and passenger vehicles.

The optimal parameter values defining the braking system have been identified, resulting in effective β = 0.695 which enhances the brake forces at respective axles. Nominal slip of 3.42% is achieved with maximum deceleration of 5.72 m/s² maintaining directional stability during braking. The results obtained from both the methodologies are juxtaposed and assessed governing the vehicle stability in straight line motion to prevent wheel lock.

Optimization results establish the practicality, efficacy and applicability of the proposed approaches. The findings provide valuable insights for the design and optimization of hydraulic drum brake systems in modern automobiles, which can lead to safer and more efficient braking systems.

This paper aims to deal with the development of a software tool to simulate and study vehicle – road interaction (VRI) to quantify the forces induced and energy released from vehicles to the road pavement, in different vehicle motion scenarios, and the energy absorbed by the road surface, speed reducers or a specific energy harvester surface or device. The software tool also enables users to quantify the energetic efficiency of the process.

Existing software tools were analysed and its limitations were identified in terms of performing energetic analysis on the interaction between the vehicle and the road pavement elements, such as speed reducers or energy harvest devices. The software tool presented in this paper intends to overcome those limitations and precisely quantify the energy transfer.

Different vehicle models and VRI models were evaluated, allowing to conclude about each model precision: bicycle car model has a 60 per cent higher precision when compared with quarter-car model, and contact patch analysis model has a 67 per cent higher precision than single force analysis model. Also, a technical study was performed for different equipment surface shapes and displacements, concluding that these variables have a great influence on the energy released by the vehicle and on the energy harvested by the equipment surface.

The developed software tool allows to study VRI with a higher precision than existing tools, especially when energetic analyses are performed and when speed reduction or energy harvesting devices are applied on the pavement.

For autonomous vehicles, trajectory prediction of surrounding vehicles is beneficial to improving the situational awareness of dynamic and stochastic traffic environments, which is a crucial and indispensable element to realize highly automated driving.

In this paper, the overall framework consists of two parts: first, a novel driver characteristic and intention estimation (DCIE) model is built to indicate the higher-level information of the vehicle using its low-level motion variables; then, according to the estimation results of the DCIE model, a classified Gaussian process model is established for probabilistic vehicle trajectory prediction under different motion patterns.

The whole method is later applied and analyzed in the highway lane-change scenarios with the parameters of models learned from the public naturalistic driving data set. Compared with other traditional methods, the performance of this proposed approach is proved superior, demonstrated by the higher accuracy in the long prediction horizon and a more reasonable description of uncertainty.

This hierarchical approach is proposed to make trajectory prediction accurately both in the short term and long term, which can also deal with the uncertainties caused by the perception system or indeterminate vehicle behaviors.

This study aims to investigate the safety effects of work zone advisory systems. The traditional system includes a dynamic message sign (DMS), whereas the advanced system includes an in-vehicle work zone warning application under the connected vehicle (CV) environment.

A comparative analysis was conducted based on the microsimulation experiments.

The results indicate that the CV-based warning system outperforms the DMS. From this study, the optimal distances of placing a DMS varies according to different traffic conditions. Nevertheless, negative influence of excessive distance DMS placed from the work zone would be more obvious when there is heavier traffic volume. Thus, it is recommended that the optimal distance DMS placed from the work zone should be shortened if there is a traffic congestion. It was also revealed that higher market penetration rate of CVs will lead to safer network under good traffic conditions.

Because this study used only microsimulation, the results do not reflect the real-world drivers’ reactions to DMS and CV warning messages. A series of driving simulator experiments need to be conducted to capture the real driving behaviors so as to investigate the unresolved-related issues. Human machine interface needs be used to simulate the process of in-vehicle warning information delivery. The validation of the simulation model was not conducted because of the data limitation.

It suggests for the optimal DMS placement for improving the overall efficiency and safety under the CV environment.

A traffic network evaluation method considering both efficiency and safety is proposed by applying traffic simulation.

This paper aims to present the control laws to be used in the control of pendular motion on tethered satellite systems in space during orbiting by using a nonlinear design technique.

This work presents both physical and mathematical models represented in a circular orbit. Euler equation of the rigid body is applied under reasonable assumption so as to form the equations of pendular motion. These equations are then used to develop the control laws using a nonlinear design technique. The control laws are required to drive the in-plane angles and out-of-plane angles of the pendular motion to the required trajectories. Simulations are then conducted to study the control results.

Simulation results show that the control laws in both plane angles of motions considered are able to move the pendular motion to the required trajectory. It was also eminent that a lot of effort is required in the case of the reference trajectory that corresponds to the constant inside-plane. To control the pendular motion of the plane, one requires an extended period of time and it should be controlled within a reasonable range. In the outside-of-plane pendular motion, minimal or no effort is required for the control. The reason is that the trajectory is natural planar.

This research is expected to provide a dynamic control strategy for all tethered satellite space systems.

The research proposes a combined dynamic method for the purpose of improving the control of all types of tether satellites.