Reference Vehicle Research Articles

Enhancement of Yaw Moment Control for Drivers with Excessive Steering in Emergency Lane Changes

When a ground vehicle runs at high speeds, even a slight excess in the wheel steering angle can immediately cause the vehicle to slide sideways and lose control. In this study, we propose an active safety control system designed to address emergency situations where the driver applies excessive steering input and the vehicle speed varies significantly during control. The system combines the direct yaw moment (DYM) method with a steering saturation scheme that prevents excessive driver steering input from adversely influencing the front-wheel steering. Consequently, the control system allows the DYM to focus more on other stabilization tasks and maintain tire/road friction within its workable linear range. The implementation relies on a reference steering angle and a reference vehicle state, derived from a linear vehicle model considering tire/road friction limitations. When the driver’s steering angle and the system state deviate from these reference values, the control system intervenes by applying both the steering saturation scheme and DYM method. This ensures the front-wheel steering angle and system state remain close to the reference values. The control strategy is developed using the polytopic Linear Parameter Varying (LPV) technique and Linear Matrix Inequality (LMI) to account for the changes in vehicle speed. It is further enhanced with an input saturation technique based on a high-gain approach, which improves control utilization and system response during emergency situations. The advantages of the proposed control strategy are demonstrated through simulation results.

Trajectory Optimization and Multiple-Sliding-Surface Terminal Guidance in the Lifting Atmospheric Reentry

AbstractIn this paper, the problem of guiding a vehicle from the entry interface to the ground is addressed. The Space Shuttle Orbiter is assumed as the reference vehicle and its aerodynamics data are interpolated to properly simulate its dynamics. The transatmospheric guidance is based on an open-loop optimal strategy which minimizes the total heat input absorbed by the vehicle while satisfying all the constraints. Instead, the terminal phase guidance is achieved through a multiple-sliding-surface technique, which is able to drive the vehicle toward a specified landing point with desired heading angle and vertical velocity at touchdown, even in the presence of nonnominal initial conditions. The terminal guidance strategy is successfully tested through a Monte Carlo campaign, in the presence of stochastic winds and wide dispersions on the initial conditions at the terminal area energy management, in more critical scenarios with respect to the orbiter safety criteria.

Model-free autonomous control of four-wheel steering using artificial flow guidance

Four-wheel steering (4WS) is an effective technique to improve handling performance and lateral stability of road vehicles. Conventionally, controllers utilise the driver's actions and vehicle dynamics to coordinate front and rear-axle steering. This paper proposes a novel approach for 4WS controller design, based on the concept of Artificial Flow Guidance (AFG), which relies on a spatially distributed motion reference through a two-dimensional vector field. This field provides high-level guidance while lower-level steering controllers to control axle centres motions relative to the flow. These flow vectors, computed in real-time via simple geometric construction, can be pre-computed globally to evaluate the guidance algorithm's efficacy. When controlling only the front axle, this same approach can function as an autonomous driving system. Relying solely on a spatial reference field and control targets' velocities enables the controller to work in a simple and robust fashion, without using a reference vehicle dynamics model or lengthy parameter tuning. The proposed approach's effectiveness is validated through co-simulation with MATLAB/Simulink and the CarMaker simulation platform. AFG control performance is found to be at least comparable to that of more complex 4WS controllers using methods such as MPC; in the cases considered, AFG provides superior path-tracking performance.

Radar sensor based machine learning approach for precise vehicle position estimation

Estimating vehicles’ position precisely is essential in Vehicular Adhoc Networks (VANETs) for their safe, autonomous, and reliable operation. The conventional approaches used for vehicles’ position estimation, like Global Positioning System (GPS) and Global Navigation Satellite System (GNSS), pose significant data delays and data transmission errors, which render them ineffective in achieving precision in vehicles’ position estimation, especially under dynamic environments. Moreover, the existing radar-based approaches proposed for position estimation utilize the static values of range and azimuth, which make them inefficient in highly dynamic environments. In this paper, we propose a radar-based relative vehicle positioning estimation method. In the proposed method, the dynamic range and azimuth of a Frequency Modulated Continuous Wave radar is utilized to precisely estimate a vehicle’s position. In the position estimation process, the speed of the vehicle equipped with the radar sensor, called the reference vehicle, is considered such that a change in the vehicle’s speed changes the range and azimuth of the radar sensor. For relative position estimation, the distance and relative speed between the reference vehicle and a nearby vehicle are used. To this end, only those vehicles are considered that have a higher possibility of coming in contact with the reference vehicle. The data recorded by the radar sensor is subsequently utilized to calculate the precision and intersection Over Union (IOU) values. You Only Look Once (YOLO) version 4 is utilized to calculate precision and IOU values from the data captured using the radar sensor. The performance is evaluated under various real-time traffic scenarios in a MATLAB-based simulator. Results show that our proposed method achieves 80.0% precision in position estimation and obtains an IOU value up to 87.14%, thereby outperforming the state-of-the-art.

An electrified boom actuation system with energy regeneration capability driven by a novel electro-hydraulic unit

This paper presents a novel electrified solution for linear actuation systems, which has undergone a successful in-vehicle demonstration, marking a significant advancement in this field. Aligned with the growing trend towards electrification, this solution holds promise for a wide range of off-road applications. The showcased electro-hydraulic actuation architecture enables efficient four-quadrant operation and incorporates energy recovery capabilities. At the core of the system lies a distinctive electro-hydraulic unit, integrating a fixed hydraulic pump and a variable-speed electric motor into a compact and powerful entity. A specialized hydraulic system is designed to efficiently transform electrical energy from the electro-hydraulic unit into boom cylinder actuation. The sizing of the system is determined by the boom operation of a commercial compact loader. The maximum power output of the electro-hydraulic system is approximately 15 kW. The components of the proposed system are integrated into the reference vehicle, and comprehensive performance tests are conducted. The results of the tests performed on the vehicle with the boom lifting and lowering cycle indicate an overall system efficiency of 60%. The electrified solution consumes only about one-third of the energy used by the conventional boom actuation system on the reference machine, while exhibiting energy savings exceeding 75% during specific work phases. The energy savings come mainly from energy regeneration and minimal loss from throttling through the specialized hydraulic circuit design. The successful demonstration on the reference vehicle underscores the practicality and effectiveness of the proposed electrified solution in current mobile hydraulic applications.

Ungulate responses and habituation to unmanned aerial vehicles in Africa's savanna.

This article tests the hypothesis that "the likelihood that the species will react and level at which they do to the unmanned aerial vehicle (UAV) is related to the altitude, number of passes, sound intensity, type of UAV, takeoff distance, and species." This paper examined the behavioral responses of a group of free ranging ungulate species (Oryx, Kudu, Springbok, Giraffe, Eland, Hartebeest, and Impala) found in an animal reserve in Namibia to the presence of different in-flight UAV models. The study included 397 passes (trials) over 99 flights at altitudes ranging from 15 to 55 meters in three categories of response level: No response, Alert, and Movement. The ungulates were unhabituated to the UAVs and the study was conducted in the presence of stress-inducing events that occur naturally in the environment. Certain species were found to be more reactive than others, in addition to several displaying different response levels in single or mixed herd environments. Zebras were found to be less responsive in mixed herd environments while Oryx were present, as compared to when the Oryx were not; suggesting that some species may respond based on other species perception of threat or their relative fitness levels. The UAVs also produced inconsistent response rates between movement and alert behavior. The reference vehicle, Phantom 3 was much more likely than the Mavic to induce an alert response, while both having similar probabilities of inducing a movement response. Furthermore, the Custom X8 showed significantly more alert and movement responses than the other UAVs. This shows there may be several aspects to the UAVs that affect the responses of the ungulates. For instance, the sound intensity may alert the species more often, but close proximity may induce a movement response. More generally, the data shows that when the UAV is flying above 50 meters and has a measured sound intensity below 50 dB, the likelihood of inducing a movement response on an ungulate species is below 6% regardless of the vehicle on the first pass over the animals. Additionally, with each subsequent pass the likelihood of response dropped by approximately 20 percent. The results suggest a stronger correlation between flight altitude and response across the different ungulates, and the evidence suggests rapid habituation to the UAVs.

Life Cycle Analysis of an On-the-Road Modular Vehicle Concept

In order to reduce the environmental impacts caused by the transport sector, autonomous and electrified on-the-road modular vehicles (otrm) could be a solution. By separating the drive unit from the transport unit, they enable use cases for various transport tasks and reduce individual and motorized transport and its generated emissions. Therefore, the goal of this study is to assess the environmental impacts from cradle to grave by applying the LCA methodology for a defined otrm—the U-Shift—vehicle fleet considering a specific use case relative to a reference vehicle fleet. The results indicate that the U-Shift fleet reduces the life cycle environmental impacts in a range of 3–28% for all of the seven impact categories, which are analyzed in detail. While emissions from the use phase are similar, U-Shift has an environmental benefit in the production phase due to a low amount of resource-intensive driveboards. Considering the early development stage of U-Shift, several measures are discussed, addressing the material and configuration aspects of the vehicles as well as optimized use case applications, which promise further impact-reduction potential.

Hierarchical control of differential steering for four-in-wheel-motor electric vehicle.

The purpose of this paper is to study the control of differential steering for four-in-wheel-motor electric vehicles. The so-called differential steering means that the front wheel steering is realized through the differential driving torque between the left and right front wheels. With the consideration of tire friction circle, a hierarchical control method is proposed to realize the differential steering and the constant longitudinal speed simultaneously. Firstly, the dynamic models of the front wheel differential steering vehicle, the front wheel differential steering system and the reference vehicle are established. Secondly, the hierarchical controller is designed. The upper controller is to obtain the resultant forces and resultant torque required by the front wheel differential steering vehicle tracking the reference model through the sliding mode controller. In the middle controller, the minimum tire load ratio is selected as the objective function. Combined with the constraints, the resultant forces and resultant torque are decomposed into the longitudinal and lateral forces of four wheels by the quadratic programming method. The lower controller provides the required longitudinal forces and tire sideslip angles for the front wheel differential steering vehicle model through the tire inverse model and the longitudinal force superposition scheme. Simulation results show that the hierarchical controller can guarantee the vehicle to track the reference model well on both of the high and low adhesion coefficient road with all of the tire load ratios smaller than 1. It can be drawn that the control strategy proposed in this paper is effective.

An Adaptive Controller Design for Nonlinear Active Air Suspension Systems with Uncertainties

Active air spring suspensions can improve the vehicle ride comfort and meanwhile realize the vehicle height regulation, and therefore, they have been widely used and studied. However, to achieve better ride comfort and a satisfactory vehicle body height adjustment, the active air suspension controller becomes an indispensable and significant part of the system. Since the nonlinear suspension system possesses uncertainties, it is difficult to take into account both ride comfort and height regulation. This study innovatively proposes an adaptive control algorithm to specifically address the problem of vehicle height regulation and ride comfort for nonlinear active air suspension systems with uncertainties. The accurate tracking to reference vehicle body height curves is realized, and the ride comfort is also improved. Through simulations with two scenarios, it is illustrated that the active air suspension controller owns better control effectiveness than the PID controller. Compared with the PID controller, the designed controller can track the reference vehicle body height curves faster and more accurately. The result also verifies the priority of the designed controller.

Mission design for point-to-point passenger transport with reusable launch vehicles

With the progress of SpaceX’s Starship system, a fully reusable launch system appears possible in the near future. With this technological advance, a new class of transport missions could become economically feasible: Rocket-propelled transport of passengers and cargo at near-orbital speeds from one point on the Earth to another. This mission type is investigated for two reference vehicles: Starship from SpaceX and the SpaceLiner concept, developed by DLR-SART. For both vehicles, the properties during reentry are assessed and the impact on the descent trajectory is investigated, including parametric studies with regard to the effect of launch heading and crossrange capability. While the SpaceLiner upper stage relies on its high hypersonic L/D to cover the majority of the distance in quasi-stationary flight within the atmosphere, the Starship relies mostly on a ballistic flight path at higher altitudes. The flight within the upper layers of the atmosphere allows the SpaceLiner to change its heading mid-flight through banking maneuvers and thus efficiently curve around populated areas. However, this prolonged flight at high velocities within the upper atmosphere does necessitate active cooling of the leading edges. An exemplary mission from Shanghai to California is optimized for both reference vehicles, with the optimization target being minimal peak heat loads. Due to the Starship’s reliance on the ballistic portion of its flight to cover range, the peak heat flux is substantially higher on westward missions, compared to the eastward return flight.

Benchmark Evaluation & Proposed Electrical Architecture for a 12V BSG Vehicle

This paper makes an effort to define an optimal electrical architecture for a 12V BSG system for a mid- sized diesel engine, with the help of functional validation tests and specific test cases developed by the authors. The first few sections of the paper explain various modes of a 12V BSG hybrid operations namely-ESS, torque assist and recuperation on a reference vehicle. Set of test cases have been developed to explain 12V BSG behavior as a DC motor during ESS and torque- assist mode of operation and as a 3-phase generator during regenerative coasting mode. In the final section, an optimized electrical architecture of 12V BSG system is proposed for mid-sized diesel engine with manual transmission, based on objective measurement of test cases and a Pugh Comparison matrix of various feasible architectures.

Chassis Coordinated Control for Full X-by-Wire Four-Wheel-Independent-Drive Electric Vehicles

In this paper, a full X-by-wire chassis coordination control scheme is proposed by synthetically utilizing the Direct Yaw-moment Control, Active Front Steering, Anti-Slip Regulation and Active Roll Control to improve the longitudinal, yaw and roll stability. First, a vehicle state prediction module is established to predict vehicle yaw and roll stability and to generate three reference vehicle states, i.e., the desired roll angle, yaw rate and longitudinal velocity. Then, a decentralized event-triggered discrete sliding mode control scheme is developed to track these reference states by coordinating the X-by-wire subsystems based on their respective effective working areas. For yaw rate control, dynamic torque regulation factors are introduced to prevent wheel slip and lock-up based on real-time slip ratio feedback. Under longitudinal driving conditions, a robust sliding mode control and a hybrid control-based method are used under emergency acceleration or braking conditions. The hardware-in-the-loop (HIL) tests under the slalom, double lane change and fish hook tests show that the proposed chassis coordinated control scheme can comprehensively improve vehicle ride comfort, handling performance, longitudinal and lateral stability, and rollover prevention ability.

Improving Mobile Robot Maneuver Performance Using Fractional-Order Controller.

In this paper, the low-level velocity controller of an autonomous vehicle is studied. The performance of the traditional controller used in this kind of system, a PID, is analyzed. This kind of controller cannot follow ramp references without error, so when the reference implies a change in the speed, the vehicle cannot follow the proposed reference, and there is a significant difference between the actual and desired vehicle behaviors. A fractional controller is proposed which changes the ordinary dynamics allowing faster responses for small times, at the cost of slower responses for large times. The idea is to take advantage of this fact to follow fast setpoint changes with a smaller error than that obtained with a classic non-fractional PI controller. Using this controller, the vehicle can follow variable speed references with zero stationary error, significantly reducing the difference between reference and actual vehicle behavior. The paper presents the fractional controller, studies its stability in function of the fractional parameters, designs the controller, and tests its stability. The designed controller is tested on a real prototype, and its behavior is compared to a standard PID controller. The designed fractional PID controller overcomes the results of the standard PID controller.

Estimating vertiport passenger throughput capacity for prominent eVTOL designs

Urban Air Mobility has the potential to substantially reduce travel times in some cases of urban-related transportation. Travel time savings strongly depend on fast processing at vertiports, which presents a key challenge considering demand levels’ vertiports would experience when becoming an established mode of transport. This article sheds light on the passenger throughput vertiport airfields can manage and how the operations are sensitive to changes. One main contribution of this article is the introduction of hourly passenger throughput per area as a performance indicator that allows to compare vertiports of different sizes. VoloCity is studied as a reference vehicle and the resulting space requirement of the carefully specified baseline scenario is 188 square-meters per passenger per hour. A total of 13 prominent eVTOL designs are included in the study from which the current design space between maximum vehicle dimension and number of seats is deducted. The study shows that vehicles with a small maximum dimension yield the highest passenger throughput capacity. CityAirbus performs best (46.3 m2/PAX/h) with a diameter of 7.92 m and Archer Maker performs worst (221 m2/PAX/h) with a diameter of 12.2 m. How the performance indicators can be used as rules-of-thumb in the first-order estimations of vertiport throughput capacity or space requirement is described by means of illustrative examples. The insights presented in this paper might be useful for researches, vehicle developers, and municipalities alike.

TRUCON: Blockchain-Based Trusted Data Sharing With Congestion Control in Internet of Vehicles

The Internet of vehicles (IoV) has a substantial impact on traffic efficiency improvement and accidents avoidance. Due to restricted resources, vehicles must share observed data with RSUs and other vehicles to execute some time-tolerant computing tasks. However, data provided by vehicles cannot always be trusted due to the presence of attackers. Fake messages could have catastrophic ramifications, such as vehicle collisions. Furthermore, extensive data sharing might cause channel congestion, resulting in the loss of vital messages during delivery. To overcome the aforementioned issues, we propose TRUCON, a blockchain-based trusted data sharing mechanism with congestion control in IoV. Firstly, we propose a Kademlia algorithm-based traffic data forwarding method to control channel congestion state. By adjusting the bucket size and distance threshold, source vehicles can limit the number of reference vehicles forwarded. Secondly, we present a cuckoo filter-based traffic data deduplication and discrimination approach. To avoid repetitive sharing, vehicles and RSUs can check their local filters to verify if the current data report has been shared. Based on the foregoing, we propose a blockchain-based trust management mechanism with congestion control. RSUs serve as full nodes while vehicles are light nodes in the blockchain. Finally, we develop a trust management prototype system with congestion control that incorporates both on-chain and off-chain parts. It signifies that our scheme is both feasible and effective.

Fatigue monitoring and maneuver identification for vehicle fleets using a virtual sensing approach

Extensive monitoring comes at a prohibitive cost, limiting Predictive Maintenance strategies for vehicle fleets. This paper presents a measurement-based virtual sensing technique where local strain gauges are only required for few reference vehicles, while the remaining fleet relies exclusively on accelerometers. The scattering transform is used to perform feature extraction, while principal component analysis provides a reduced, low dimensional data representation. This enables direct fatigue damage regression, parameterized from unlabeled usage data. Identification measurements allow for a physical interpretation of the reduced representation. The approach is demonstrated using experimental data from a sensor equipped eBike, which is made publicly available.

Adaptive Nonlinear Control of Salient-Pole PMSM for Hybrid Electric Vehicle Applications: Theory and Experiments

This research work deals with the problem of controlling a salient-pole permanent-magnet synchronous motor (SP-PMSM) used in hybrid electric vehicles. An adaptive nonlinear controller based on the backstepping technique is developed to meet the following requirements: control of the reference vehicle speed in the presence of load variation and changes in the internal motor parameters while keeping the reliability and stability of the vehicle. The complexity of the control problem lies on the system nonlinearity, instability and the problem of inaccessibility to measure all the internal parameters, such as inertia, friction and load variation. For this issue, an adaptive backstepping regulator is developed to estimate these parameters. On the basis of formal analysis and simulation, as well as test results, it is clearly shown that the designed controller achieves all the goals, namely robustness and reliability of the controller, stability of the system and speed control, considering the uncertainty parameters’ measurements.

Numerical Analysis of the Wheel Camber of the Front Axle of a Passenger Car During Cornering

The work attends to the numerical analysis of the wheel forces and the resultant wheel camber of the reference vehicle Alfa Romeo 156 for four distinct suspension variants of front steered wheels, namely, non-parallel arms of different lengths (these are actually used on these vehicles with a nominal wheel camber of -1.1°), parallel arms of different lengths, long parallel arms and short parallel arms. In addition to these models, reference vehicle models with nominal wheel camber of 0° and +1° were built by the authors. The mentioned six models were employed to evaluate the influence of kinematic parameters on the dynamic response of the vehicle. The outputs of the simulations will provide a valuable basis for comparison with real measured data. Experimental data acquisition will be the subject of further research by the authors. If an acceptable correlation of the values is demonstrated, it will be practicable to verify the predictive power of the presented simulations. Accordingly, it will enable to carry out future simulations of vehicle braking with the necessary deceleration values. Attainment of these values would be problematic in the case of a real vehicle experiment.

Explaining a Deep Reinforcement Learning (DRL)-Based Automated Driving Agent in Highway Simulations

As deep learning models have become increasingly complex, it is critical to understand their decision-making, particularly in safety-relevant applications. In order to support a quantitative interpretation of an autonomous agent trained through Deep Reinforcement Learning (DRL) in the highway-env simulation environment, we propose a framework featuring three types of views for analyzing data: (i) episode timeline, (ii) frame by frame, and (iii) aggregated statistical analysis, also including heatmaps for a better spatial understanding. Our methodology allowed a novel, consistent description of the behavior of the agent. The main motivator for the taken action is typically the longitudinal distance from the second-closest and, to a lower extent, third-closest vehicle. In the overtakes, also the agent’s position in lanes becomes relevant. The analysis identified interesting patterns and an issue in the last frames of an episode, when the agent is unable to overtake the last two vehicles, arguably because of the lack of reference vehicles ahead. We observed a clear differentiation between attention and SHAP values (estimating the importance of each feature for each decision), reflecting the architecture of the neural network, where the first layer implements the attention mechanism, while the deeper ones make the actual decision. Attention focuses on the proximity of the ego, while the decision is taken on a wider horizon, denoting a valuable anticipation capability. To support research, the proposed framework is released as open source.

Nonlinear hierarchical control for four-wheel-independent-drive electric vehicle

As under-constrained systems, four-wheel-independent-drive (4WID) electric vehicles have more driving degrees of freedom. In this context, reasonable control and distribution of driving or braking torque to each wheel is extremely important from the vehicle safety perspective. However, it is difficult to provide the optimal wheel torque because of the time-varying characteristics and typical over-actuated nature of the system. In light of these challenges, a novel hierarchical control scheme comprising a top- and bottom-level controller is proposed herein. First, for the top-level controller, a time-varying model-predictive-control (TV-MPC) controller is designed based on an extended 3-degree-of-freedom (3-DOF) reference vehicle model. The total driving force and additional yaw moment can be obtained using the TV-MPC. Second, for the bottom-level controller, the torque expression of each wheel is determined using the equal-adhesion-rate-rule -based algorithm. The co-simulation results obtained herein indicate that the proposed control scheme can effectively improve vehicle safety.