Ability Of Vehicle Research Articles

Enhancing the Minimum Awareness Failure Distance in V2X Communications: A Deep Reinforcement Learning Approach.

Vehicle-to-everything (V2X) communication is pivotal in enhancing cooperative awareness in vehicular networks. Typically, awareness is viewed as a vehicle's ability to perceive and share real-time kinematic information. We present a novel definition of awareness in V2X communications, conceptualizing it as a multi-faceted concept involving vehicle detection, tracking, and maintaining their safety distances. To enhance this awareness, we propose a deep reinforcement learning framework for the joint control of beacon rate and transmit power (DRL-JCBRTP). Our DRL-JCBRTP framework integrates LSTM-based actor networks and MLP-based critic networks within the Soft Actor-Critic (SAC) algorithm to effectively learn optimal policies. Leveraging local state information, the DRL-JCBRTP scheme uses an innovative reward function to increase the minimum awareness failure distance. Our SLMLab-Gym-VEINS simulations show that the DRL-JCBRTP scheme outperforms existing beaconing schemes in minimizing awareness failure probability and maximizing awareness distance, ultimately improving driving safety.

Study on Integrated Evaluation and Development Strategy of Pedestrian Protection in 2024 Edition of C-NCAP

This paper discusses the comprehensive assessment of pedestrian protection in the 2024 edition of China-New Car Assessment Program (C-NCAP) and its development strategies. The assessment plan has been adjusted according to the actual conditions of Chinese road traffic and vehicle characteristics, emphasizing comprehensive testing of vehicle safety performance. Improvement in structural crash safety significantly enhances a vehicle's ability to protect occupants in collision accidents and reduces injury risks. This article particularly focuses on pedestrian protection assessment and proposes a series of development strategies by integrating AEB VRU system testing with head and leg testing. These strategies aim to further enhance the level of pedestrian protection provided by vehicles and contribute to overall traffic safety improvement.

Research on Optimization Design of Front and Side Structures under the 24th Edition of C-NACP Automotive Collision Standard

Structural crashworthiness plays a core role in vehicle safety design, mainly focusing on the maximum impact force that the body structure can withstand in collision accidents, and striving to maximize collision energy absorption to ensure that passengers have sufficient living space. The design of structural crashworthiness needs to consider the deformation mechanism and energy absorption characteristics of vehicles under different collision modes, and improve crashworthiness through material selection, structural optimization, and other means. In addition, the structural crashworthiness is closely connected to the passenger restraint system, which together constitute the key to the passive safety performance of the vehicle. In vehicle safety design, the improvement of structural crashworthiness can significantly enhance the vehicle's ability to protect passengers in collision accidents and reduce the risk of injury. Therefore, in-depth research on structural crashworthiness and the development of efficient crashworthiness structures are important directions for improving vehicle safety performance.

Path Planning of Self-driving Vehicles Combining Ant Colony and DWA Algorithms in Complex Dense Obstacles

INTRODUCTION: To solve the problems of low quality and weak global optimization of the DWA algorithm, especially the problems of unreasonable path planning and the inability to give consideration to speed and driving safety in the process of vehicles passing through dense obstacles, this paper proposed an improved DWA algorithm based on ant colony algorithm.
 OBJECTIVES: The traffic capacity and computing efficiency of Self-driving Vehicles in complex dense obstacles can be greatly improved.
 METHODS: Through the obstacle density and distance information obtained by high-precision sensors on the vehicle, the speed objective function is updating in real time by using ant colony algorithm. And the maneuverability and safety performance of vehicles passing through are considering by the way.
 RESULTS: The experimental results show that this method can obviously improve the vehicle's traveling ability and uneven path planning in the case of dense obstacles, and the number of iterations of the algorithm is reduced by more than 16%.
 CONCLUSION: The improved DWA algorithm integrated with the ant colony algorithm can effectively improve the operating efficiency of the algorithm, reduce the distance the car must go around outside the obstacles, and improve Car driving safety. The effectiveness and universality of the improved DWA algorithm were verified through experiments.

Physics‐based wave propagation model assisted vehicle localisation in tunnels

AbstractConnected and autonomous vehicles systems can provide a safe and convenient transportation solution through wireless communication between vehicles and roadside communication infrastructure. The vehicle's ability to establish its location plays an important role in such systems. This article presents an efficient localisation framework by combining physics‐based wireless propagation models and fingerprint localisation algorithms. To that end, a parabolic wave equation (PWE)‐based wireless channel simulator is utilised to obtain the direction of arrival (DOA) values that construct the fingerprint dataset. A detailed procedure on how to obtain the DOA information using PWE, as well as analysis and guidelines on the selection of the key parameters of the localisation framework are provided. Numerical results are compared with theoretical data in terms of accuracy, and the selection of parameters during the localisation process is investigated in actual road tunnel cases. Besides, various numbers of wireless access points and schemes of fingerprinting algorithms have been studied, showing the capability of the proposed approach to be employed for the pre‐design of wireless communication systems.

Torque coordinated control of the through-the-road (TTR) 4-wheel-drive (4WD) hybrid vehicle under extreme road conditions

Vehicular safety is of considerable significance to the intelligent development of hybrid vehicles. However, the real-time stability control or reasonable torque distribution under the extreme road conditions remain a huge challenge due to the multiple uncertain parameters and difficulties to reconcile the handling and stability performance. To address the above problems for a through-the-road (TTR) 4-wheel-drive (4WD) hybrid vehicle, this study provides a handling and stability management (HSM) approach by incorporating the offline optimization rules and on-line model predictive control (MPC). Firstly, the vehicle dynamic model with seven degrees of freedom (7-DOF) is used to offline extract torque distribution rules (Offline-ETDR), and the online MPC feedback (Online-MPCF) is utilized to compensate the extra torque requirements for the poor effect under the extreme conditions. Accordingly, the offline optimization results and online correction are fused to provide the total torque demand given the real-time road condition detection. Finally, the real vehicle test are implemented to validate the effectiveness of the proposed torque coordination strategy. In comparison to the vehicle with no torque control strategy, the proposed method significantly improves the vehicle's cornering ability while also ensuring the high stability performance.

Toward efficient vehicular-based virtual network infrastructure for smart cities

Future smart cities will undoubtedly generate and process an immense volume of data. Developing a smart network infrastructure is thus becoming a key component for the better development and efficient governance of smart cities. The main objective of this article is to examine the feasibility of utilizing moving vehicles to develop an efficient Vehicular-based Virtual Network Infrastructure (VVNI) for smart cities. The basic idea here is to divide the whole city into distinct cells, then predict and evaluate the vehicle eligibility to act efficiently as a centralized communication and information hub for each cell. Specifically, we present the basic framework of the proposed VVNI, and identify the corresponding efficiency requirements in terms of service availability, cost, and quality; then we introduce novel metrics to characterize the vehicle's ability to cope with these requirements. Several simulation scenarios were conducted to assess the efficiency of the proposed VVNI. The simulation results demonstrate how the proposed model outperforms existing models and improves system performance in three benchmark areas: throughput, packet delivery ratio, and latency, especially in medium- and high-density network scenarios with slower vehicle velocities. The simulation results are promising to further enhance the development of the proposed network infrastructure.

Fluorine-Functionalized Polyphosphazene Immunoadjuvant: Synthesis, Solution Behavior and In Vivo Potency.

The inclusion of fluorine motifs in drugs and drug delivery systems is an established tool for modulating their biological potency. Fluorination can improve drug specificity or boost the vehicle's ability to cross cellular membranes. However, the approach has yet to be applied to vaccine adjuvants. Herein, the synthesis of fluorinated bioisostere of a clinical stage immunoadjuvant-poly[di(carboxylatophenoxy)phosphazene], PCPP-is reported. The structure of water-soluble fluoropolymer-PCPP-F, which contains two fluorine atoms per repeat unit-was confirmed using 1H, 31P and 19F NMR, and its molecular mass and molecular dimensions were determined using size-exclusion chromatography and dynamic light scattering. Insertion of fluorine atoms in the polymer side group resulted in an improved solubility in acidic solutions and faster hydrolytic degradation rate, while the ability to self-assemble with an antigenic protein, lysozyme-an important feature of polyphosphazene vaccine adjuvants-was preserved. In vivo assessment of PCPP-F demonstrated its greater ability to induce antibody responses to Hepatitis C virus antigen when compared to its non-fluorinated counterpart. Taken together, the superior immunoadjuvant activity of PCPP-F, along with its improved formulation characteristics, demonstrate advantages of the fluorination approach for the development of this family of macromolecular vaccine adjuvants.

Adaptive Correction of Landmark for Visual Homing in Mobile Vehicles

This paper presents an optimized visual homing method based on Average Landmark Vector (ALV), termed Adaptive Correction of Landmark (ACoL), which exhibits good homing performance and robustness in both static and dynamic indoor environments. The salient features of this paper are: (1) Inherent constraints of visual homing are analyzed in detail to reveal the limitations of existing ALV-based methods. (2) Instead of removing mismatched landmarks or artificially assigning fixed weights to landmarks, a novel solution is proposed by adaptively evaluating a reasonable weight for each landmark to account for contribution to the output. (3) Computation time of the proposed method is particularly concerned to enable the vehicle to perform real-time homing tasks in actual scenarios. (4) Simulations and experiments demonstrate the superiority of the proposed method under both static and dynamic conditions. Our method focuses on improving a vehicle's homing ability in terms of landmark matching, landmark distribution and homing direction. Comparative studies with other ALV-based methods demonstrate that our method generalizes well to various complex and challenging indoor scenarios.

Nezha-F: Design and Analysis of a Foldable and Self-Deployable HAUV

This letter introduces a small hybrid aerial underwater vehicle (HAUV), which we named Nezha-F, that can fly in the air, perform vertical profiling underwater, and vertically take off and land from both the water surface and ground. A foldable and self-deployable arm mechanism linked to and driven by a piston variable buoyancy system (PVBS) is proposed to reduce the excessive underwater drag caused by aerial structures. By having a compact size and successfully balanced aerial and underwater performance without adding excessive actuators, this design provides a feasible idea for the miniaturization of amphibious floats. The dynamic characteristics of the small PVBS are linear fitted, and modeled. The originally nonlinear actuator performance is linearized by the post-fitting mapping. Asymmetric dead zones of the actuator are removed by adding compensation to the algorithm. During a 10-day field test, the vehicle showed good aerial performance and underwater control effect. Several full mission cycle tests proved the vehicle's ability in semi-autonomous operation and robust domain crossing and verified the vehicle's endurance during each mission stage.

Secondary yaw control to improve curving vs. stability trade-off for a railway vehicle

Active primary/secondary suspensions have been proposed to solve the trade-off between curving and stability in railway vehicles. One concept is known as secondary yaw control (SYC), which consists of applying a controllable yaw torque between the carbody and the two bogies. This has been studied in the past mainly to enhance the vehicle's curving ability, but this paper extends the idea by examining the implications of designing a bogie with soft yaw stiffness between the bogie frame and the wheelsets and using SYC to provide active stabilisation. To this aim, a state feedback control law is designed according to the LQR technique. The paper presents the general concept of the active suspension control to be investigated and the specific control strategies applied. Then the effectiveness of the proposed actuation concept is investigated by means of numerical simulations performed on mathematical models of the passive and actively controlled vehicles implemented in a fully nonlinear multi-body simulator.

Method for the influence design assessment of a wheeled agricultural vehicle on the soil

The impact of a wheeled agricultural vehicle on the deformable support surface determines the vehicle's ability to move, as well as soil compaction, which is not desirable in agriculture. The agricultural machine must not cause more pressure on the ground than is permissible. Therefore, in the tasks of design numerical modelling of the agricultural vehicle movement or trailer, it is required to calculate the specified parameter. It is impossible to calculate without knowledge of the geometric characteristics of the contact spot associated with the normal deformation of the tire under normal load. To calculate these characteristics, it is necessary to have universal dependencies for determining the normal stiffness of the tire. These are available for tires of various purposes. The elastic properties of ultra-low pressure tires are insufficiently studied. Experimental studies of the elastic properties of these tires have been carried out with the authors participation. However, there are currently no dependencies to describe them. This does not provide the possibility of a correct design calculation of the influence of such tires on the soil. The purpose of the work: to develop a universal method for calculating the influence on the soil of agricultural vehicle. A universal method for calculating the impact of a wheeled agricultural machine on the ground has been developed. Universal design-experimental dependence for determining the normal stiffness of ultra-low pressure tires is obtained. It takes into account tire pressure, normal load under specific conditions and geometric characteristics.

Self-supervised reinforcement learning-based energy management for a hybrid electric vehicle

Reinforcement learning is a new research hotspot in the energy management strategy. At present, some problems in the application of reinforcement learning to energy management control still exist, including sparse reward, convergence speed, generalization ability, etc. This paper proposes a self-supervised reinforcement learning method based on a Deep Q-learning approach for fuel-saving optimization of a plug-in hybrid electric vehicle (PHEV). First, a detailed vehicle powertrain model of the Prius is built. Second, we use the self-supervised learning model to enrich the reward function. The reward function consists of two parts: internal and external rewards. Finally, to prevent the self-supervised model from falling into the “self-good” situation, a reinforcement learning calibration method is proposed. The vehicle exploration method is more effective because of the enrichment of the reward function. Furthermore, following the characteristics of self-supervised learning, we have also constructed a new driving cycle to verify the generalization ability. Results show that our proposed deep reinforcement learning method based on self-supervised and learning calibration realizes faster training convergence and lower fuel consumption than the traditional policy, and its fuel economy can reach approximately the global optimum under our new driving cycle. • The method used in this can enhance the vehicle's ability to explore the environment. • Internal rewards were constructed using self-supervised learning methods. • The algorithm has generalization ability in energy management control strategy. • The reward function is corrected with the reinforcement learning calibration.

A hybrid underwater robot for multidisciplinary investigation of the ocean twilight zone.

Mesobot, an autonomous underwater vehicle, addresses specific unmet needs for observing and sampling a variety of phenomena in the ocean's midwaters. The midwater hosts a vast biomass, has a role in regulating climate, and may soon be exploited commercially, yet our scientific understanding of it is incomplete. Mesobot has the ability to survey and track slow-moving animals and to correlate the animals' movements with critical environmental measurements. Mesobot will complement existing oceanographic assets such as towed, remotely operated, and autonomous vehicles; shipboard acoustic sensors; and net tows. Its potential to perform behavioral studies unobtrusively over long periods with substantial autonomy provides a capability that is not presently available to midwater researchers. The 250-kilogram marine robot can be teleoperated through a lightweight fiber optic tether and can also operate untethered with full autonomy while minimizing environmental disturbance. We present recent results illustrating the vehicle's ability to automatically track free-swimming hydromedusae (Solmissus sp.) and larvaceans (Bathochordaeus stygius) at depths of 200 meters in Monterey Bay, USA. In addition to these tracking missions, the vehicle can execute preprogrammed missions collecting image and sensor data while also carrying substantial auxiliary payloads such as cameras, sonars, and samplers.

Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques

Advanced automotive active-safety systems, in general, and autonomous vehicles, in particular, rely heavily on visual data to classify and localize objects such as pedestrians, traffic signs and lights, and other nearby cars, to assist the corresponding vehicles maneuver safely in their environments. However, the performance of object detection methods could degrade rather significantly under challenging weather scenarios including rainy conditions. Despite major advancements in the development of deraining approaches, the impact of rain on object detection has largely been understudied, especially in the context of autonomous driving. The main objective of this paper is to present a tutorial on state-of-the-art and emerging techniques that represent leading candidates for mitigating the influence of rainy conditions on an autonomous vehicle's ability to detect objects. Our goal includes surveying and analyzing the performance of object detection methods trained and tested using visual data captured under clear and rainy conditions. Moreover, we survey and evaluate the efficacy and limitations of leading deraining approaches, deep-learning based domain adaptation, and image translation frameworks that are being considered for addressing the problem of object detection under rainy conditions. Experimental results of a variety of the surveyed techniques are presented as part of this tutorial.

Design and Analysis of Steering and Lifting Mechanisms for Forestry Vehicle Chassis

Due to its special topographical structure, the forest working environment requires a vehicle chassis that can adapt well to complex terrain conditions. This article describes the key components of a chassis that was designed to adapt to complex terrain. The working principle and structural design of the steering structure and the lifting structure are analyzed in detail, and function verification is carried out. The steering mechanism has three degrees of freedom, and the first degree of freedom reduces the body’s inclination by 30°. The second degree of freedom can increase the steering angle of the chassis to 47°, decreasing the turning radius of the chassis. The third degree of freedom reduces the body rollover inclination by 30°. The entire steering mechanism enhances the ride and stability of the chassis. With the lifting mechanism, the wheel-legs are lifted so that the chassis can pass a limit height of 187 mm, and the wheel-legs are lowered to raise the center of gravity of the vehicle chassis by 244 mm. The entire lifting mechanism greatly improves the vehicle's ability to cross forest terrain. The size is reduced by 10% compared to other structures, and the lifting height and obstacle resistance are improved by 12.7%.

Establishment Procedure of Child Restraint Systems Reference List for ASEAN NCAP


 
 
 Babies and children below the age of 12 are the most vulnerable road users compared to older children (i.e., 12 years and above) and adults. To reduce the risk of severe injuries in the case of crashes or emergency braking, it is important that these groups of children are transported properly using age- or size-appropriate Child Restraint Systems (CRS) for as long as possible. As part of the ASEAN NCAP protocol, a so-called "CRS Reference List" that contains a sample of widely available, well-performing child seats in the ASEAN market was established to assess the vehicle's ability to safely and correctly accommodate child seats. The reference list should be reviewed every two years following a systematic revision process and published in ASEAN NCAP's website. In this paper, some shortlisted CRS identified in previous work would be assessed following ASEAN NCAP Child Occupant Protection (COP) protocol where the CRS performance is evaluated. The technical assessment is explained in detail in this paper, where several measurements taken during vehicle impact tests using several shortlisted CRS are shown. The final "CRS Reference List" would then be established by ASEAN NCAP following the systematic assessment process based on the findings and recommendations from this work for the future ASEAN NCAP COP assessment.
 
 

Modeling the high cross-country motion ability of a wheeled vehicle on deformable soil

Introduction. The improvement of the wheeled vehicles (WV) design intended for operation in areas with a poorly developed road network is an important task. The increase of vehicle operation efficiency allows significant reducing both the cost of freight traffic to remote areas of our country and development of new territories. The variety of soil surfaces on the territory of the Russian Federation makes it difficult to choose vehicle parameters at the early stages of vehicle design. Thanks to the high level of computer technology development, it is advisable to use the methods of WV motion simulation. Purpose of the study . The use of new approaches to the interaction calculation parameters of a wheel propeller with the ground, when the main features of the WV design are taken, allows to more accurately model the process of vehicle movement on a soil surface and take into consideration the mutual influence of various systems on the vehicle's cross-country ability when driving on deformable supporting surfaces. Methodology and research methods. The article presents a method for imitating the motion of a high passability WV on the deformable soil. The method is based on the principle of creating a mathematical model of WV in the environment of rigid body dynamics, extended by new models. The interaction modeling peculiarities of an elastic tire with deformable soil are to create an additional dynamic sphere. The algorithm of this sphere uses a model of the elastic tire interaction with deformable soil, developed by Professor Ya.S. Ageikin and supplemented by his students. Scientific novelty and results . The article considers an example of rectilinear motion of a WV on loam, the results of the study are presented. The approach makes it possible to comprehensively investigate the passability of the WV when moving on deformable support surfaces. The mathematical model takes into account the main WV systems and their characteristics: engine, transmission, power flow distribution mechanisms (differentials) and their condition, wheel propeller, massive inertial properties of WV links. Practical significance. The developed method makes it possible to analyze the passability of, both existing and newly developed WVs. It also allows you to study the mutual influence of WV systems on the ability to move on various soil surfaces. At that the loads on the load-bearing elements of the WVs are determined, the loading history for resource assessment included.

Feedback Game-Based Shared Control Scheme Design for Emergency Collision Avoidance: A Fuzzy-Linear Quadratic Regulator Approach

Driver-machine shared control scheme opens up a new frontier for the design of driver assistance system, especially for improving active safety in emergency scenario. However, the driver's stress response to steering assistance and strong tire nonlinearity are main challenges suffered by controller designing for collision avoidance. These unfavorable factors are particularly pronounced during emergency steering maneuvers and sharply degrade shared control performance. This paper proposes a fuzzy-linear quadratic regulator (LQR) game-based control scheme to simultaneously enhance vehicle stability while compensating driver's inappropriate steering reaction in emergency avoidance. A piecewise linear-based Takagi–Sugeno (T–S) fuzzy structure is presented to mimic driver's knowledge about vehicle lateral nonlinearity, and the control authority is shared between driver and emergency steering assistance (ESA) system through steer-by-wire (SBW) assembly. An identical piecewise internal model is chosen for ESA and the shared lane-keeping problem is modeled as a fuzzy linear quadratic (LQ) problem, where the symmetrical fuzzy structure further enhances vehicle's ability to handle extreme driving conditions. In particular, the feedback Stackelberg equilibrium solutions of the fuzzy-LQ problem are derived to describe the interactive steering behavior of both agents, which enables the ESA to compensate driver's irrational steering reaction. Hardware-in-the-loop (HIL) experiment demonstrates the ESA's capability in compensating driver's aggressive steering behavior, as well as the copiloting system's excellent tracking and stabilizing performance in emergency collision avoidance.

Efficacy of seat-mounted thoracic side airbags in the German vehicle fleet

ABSTRACTObjective: Thoracic side airbags (tSABs) deploy within close proximity to the occupant. Their primary purpose is to provide a protective cushion between the occupant and the intruding door. To date, various field studies investigating their injury mitigation has been limited and contradicting. The research develops efficacy estimations associated for seat-mounted tSABs in their ability to mitigate injury risk from the German collision environment.Methods: A matched cohort study using German In-Depth Accident Study (GIDAS) data was implemented and aims to investigate the efficacy of seat-mounted tSAB units in preventing thoracic injury. Inclusion in the study required a nearside occupant involved in a lateral collision where the target vehicle exhibited a design year succeeding 1990. Collisions whereby a tSAB deployed were matched on a 1:n basis to collisions of similar severity where no airbag was available in the target vehicle. The outcome of interest was an incurred bodily or thoracic regional injury. Through conditional logistic regression, an estimated efficacy value for the deployed tSAB was determined.Results: A total of 255 collisions with the deployed tSAB matched with 414 collisions where no tSAB was present. For the given sample, results indicated that the deployed tSAB was not able to provide an unequivocal benefit to the occupant thoracic region, because individuals exposed to the deployed tSAB were at equal risk of injury (Thorax Maximum Abbreviated Injury Scale (Tho.MAIS)2+ odds ratio [OR] = 1.04, 95% confidence interval [CI], 0.41–2.62; Tho.MAIS3+ OR = 1.15, 95% CI, 0.41–3.18). When attempting to isolate an effect for skeletal injuries, a similar result was obtained. Yet, when the tSAB was coupled with a head curtain airbag, a protective effect became apparent, most noticeable for head/face/neck (HFN) injuries (OR = 0.59, 95% CI, 0.21–1.65).Conclusion: The reduction in occupant HFN injury risk associated with the coupled tSAB and curtain airbag may be attributable to its ability to provide coverage over previous mechanisms of injury. Yet, the sole presence of the tSAB showed no ability to provide additional benefit for the occupant's thoracic region. Future work should identify mechanisms of injury in tSAB cases and attempt to quantify improvements in the vehicle's ability to resist intrusion.