Direct adaptive control for lane keeping in intelligent vehicle systems

In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.

Automotive Lighting Systems Based on Luminance/Intensity Grids: A Proposal Based on Real-Time Monitoring and Control for Safer Driving

The requirements for automotive lighting systems,especially the light patterns ensuring driver perception,are based on criteria related to the headlamps,rather than the light perceived by drivers and road users.Consequently,important factors such as pavement reflectance,driver age,or time of night,are largely ignored.Other factors such as presence of other vehicles,vehicle speed and weather conditions are considered by the Adaptive Driving Beam(ADB)and Adaptive Front-lighting System(AFS)respectively,though with no information regarding the visual perception of drivers and other road users.Evidently,it is simpler to simulate and measure the light emitted by the lamps than the light reflected by the pavement or emitted by other vehicles.However the current technology in cameras and light sensors,communication protocols,and control of Light Emitting Diodes(LED),combined with decision-making techniques applied to large amounts of data,can open a new era in the operation of headlamps and thus ensure the visual needs of drivers in real time and under actual road conditions.The solution lies in an interaction road-sensor-headlamp,which is not based on the light emitted by headlamps,but rather on the light perceived by the drivers.This study thus proposes a dual grid based on luminance and luminous intensity,which would manage the headlamps by optimizing driver perception and the safety of all road users.

Finite Frequency Fuzzy H∞Control for Uncertain Active Suspension Systems With Sensor Failure

This paper investigates the problem of finite frequency fuzzy H_∞ control for uncertain active vehicle suspension systems, in which sensor failure is taken into account. TakagiSugeno(T-S) fuzzy model is established for considered suspension systems. In order to describe the sensor fault effectively, a corresponding model is introduced. A vital performance index,H_∞ performance, is utilized to measure the drive comfort. In the framework of Kalman-Yakubovich-Popov theory, the H_∞ norm from external perturbation to controlled output is optimized effectively in the frequency domain of 4 Hz-8 Hz to enhance ride comfort level. Meanwhile, three suspension constrained requirements, i.e., ride comfort level, manipulation stability,suspension deflection are also guaranteed. Furthermore, sufficient conditions are developed to design a fuzzy controller to guarantee the desired performance of active suspension systems. Finally, the proposed control scheme is applied to a quarter-vehicle active suspension, and simulation results are given to illustrate the effectiveness of the proposed approach.

Adaptive Attitude Control for Multi-MUAV Systems With Output Dead-Zone and Actuator Fault

Many mechanical parts of multi-rotor unmanned aerial vehicle(MUAV)can easily produce non-smooth phenomenon and the external disturbance that affects the stability of MUAV.For multi-MUAV attitude systems that experience output dead-zone,external disturbance and actuator fault,a leader-following consensus anti-disturbance and fault-tolerant control(FTC)scheme is proposed in this paper.In the design process,the effect of unknown nonlinearity in multi-MUAV systems is addressed using neural networks(NNs).In order to balance out the effects of external disturbance and actuator fault,a disturbance observer is designed to compensate for the aforementioned negative impacts.The Nussbaum function is used to address the problem of output dead-zone.The designed fault-tolerant controller guarantees that the output signals of all followers and leader are synchronized by the backstepping technique.Finally,the effectiveness of the control scheme is verified by simulation experiments.

Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

Zimbabwe has witnessed the evolution of Information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management Information Systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by Information Systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

A Fuzzy Logic-Based Framework for Route Choice in Vehicle Navigation Systems

Vehicle Navigation Systems (VNS) is an important component of Intelligent Transportation Systems (ITS). These Systems are designed to assist drivers in making pre trip and enroute travel choice decisions, and typically, they must provide route choice, route guidance and other related services. Although there have been a lot of existed systems in the market, and most of them used lots of contemporary technologies, they are believed short of ″true intelligence″, because they paid little attention to the subjective issues in driver′s route choice behavior, such as travel objectives and personal preferences, etc. \;However, the VNS is designed for its users, and the successful implementation of VNS is largely dependent on the driver′s acceptance. If the driver feels that the VNS can′t give him (her) a satisfactory choice, he (she) will not use it, then, the marketing value of VNS will decline. And on the whole, the transport benefit that is mainly gained by the wide use of ITS will lost. \;Supported by the research project of ″Beijing Intelligent Urban Transportation Systems″, this paper presents a conceptual model to deal with this problem. We first defined the driver′s objective as a linguistic statement that has a set of attributes. These attributes are then treated as the fuzzy sets on the universal of all the existed routes. By determining each attribute′s membership function and assign driver dependent perception to these attributes, we can change the multi criteria route choice problem into a fuzzy logic based decision making problem. Then, to meet the demands of dynamic real time route selection, we use a limited routes set for choice and can swiftly get a satisfactory solution that we think is the driver′s actually needs.

Relativistic transformation between τ and TCG for Mars missions under IAU Resolutions

Considering the fact that the general theory of relativity has become an in- extricable part of deep space missions, we investigate the relativistic transformation between the proper time of an onboard clock τ and the Geocentric Coordinate Time （TCG） for Mars missions. By connecting τ with this local timescale associated with the Earth, we extend previous works which focus on the transformation between τ and the Barycentric Coordinate Time （TCB）. （TCB is the global coordinate time for the whole solar system.） For practical convenience, the relation between τ and TCG is recast to directly depend on quantities which can be read from ephemerides. We find that the difference between τ and TCG can reach the level of about 0.2 seconds in a year. To distinguish various sources in the transformation, we numerically calculate the contributions caused by the Sun, eight planets, three large asteroids and the space- craft. It is found that if the threshold of 1 microsecond is adopted, this transformation must include effects due to the Sun, Venus, the Moon, Mars, Jupiter, Saturn and the velocities of the spacecraft and Earth.

Relativistic transformation between τ and TCB for Mars missions: Fourier analysis on its accessibility with clock offset

In the context of the fact that Einstein＇s general relativity has become an inevitable part of deep space missions, we will extend previous works on relativistic transformation between the proper time ^- of a clock onboard a spacecraft orbiting Mars and the Barycentric Coordinate Time （TCB） by taking the clock offset into ac- count and investigate its accessibility by Fourier analysis on the residuals after fitting the ^--TCB curve in terms of n-th order polynomials. We find that if the accuracy of a clock can achieve better than ~ 10-5 s or ~ 10-6 s （depending on the type of clock offset） in one year after calibration, the relativistic effects on the difference between 7- and TCB will need to be carefully considered.

Relativistic algorithm for time transfer in Mars missions under IAU Resolutions: an analytic approach

With tremendous advances in modem techniques, Einstein＇s general rela- tivity has become an inevitable part of deep space missions. We investigate the rela- tivistic algorithm for time transfer between the proper time - of the onboard clock and the Geocentric Coordinate Time, which extends some previous works by including the effects of propagation of electromagnetic signals. In order to evaluate the implicit algebraic equations and integrals in the model, we take an analytic approach to work out their approximate values. This analytic model might be used in an onboard com- puter because of its limited capability to perform calculations. Taking an orbiter like Yinghuo-1 as an example, we find that the contributions of the Sun, the ground station and the spacecraft dominate the outcomes of the relativistic corrections to the model.

MUTS-Based Cooperative Target Stalking for A Multi-USV System

This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)system.Based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is proposed.Firstly,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG algorithm.The advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for training.Secondly,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is introduced.Finally,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking scenarios.In order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this paper.The proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission execution.Moreover,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.

Relativistic time transfer for a Mars lander： from Areocentric CoordinateTime to Barycentric Coordinate Time

As the second step of relativistic time transfer for a Mars lander,we investigate the transformation between Areocentric Coordinate Time（TCA）and Barycentric Coordinate Time（TCB）in the framework of IAU Resolutions.TCA is a local time scale for Mars,which is analogous to the Geocentric Coordinate Time（TCG）for Earth.This transformation has two parts:contributions associated with gravitational bodies and those depending on the position of the lander.After setting the instability of an onboard clock to 10;and considering that the uncertainty in time is about 3.2 microseconds after one Earth year,we find that the contributions of the Sun,Mars,Jupiter and Saturn in the leading term associated with these bodies can reach a level exceeding the threshold and must be taken into account.Other terms can be safely ignored in this transformation for a Mars lander.

Relativistic time transfer for a Mars lander:from proper time to Areocentric Coordinate Time

As the first step in relativistic time transfer for a Mars lander from its proper time to the time scale at the ground station, we investigate the transformation between proper time and Areocentric Coordinate Time （TCA） in the framework of IAU Resolutions. TCA is a local time scale for Mars, which is analogous to the Geocentric Coordinate Time （TCG） for Earth. This transformation contains two contributions： inter- hal and external. The internal contribution comes from the gravitational potential and the rotation of Mars. The external contribution is due to the gravitational fields of other bodies （except Mars） in the Solar System. When the （in）stability of an onboard clock is assumed to be at the level of 10-13, we find that the internal contribution is dominated by the gravitational potential of spherical Mars with necessary corrections asso- ciated with the height of the lander on the areoid, the dynamic form factor of Mars, the flattening of the areoid and the spin rate of Mars. For the external contribution, we find the gravitational effects from other bodies in the Solar System can be safely neglected in this case after calculating their maximum values.

Fuzzy Unknown Input Observer for Estimating Sensor and Actuator Cyber‑Attacks in Intelligent Connected Vehicles

The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected vehicles.This paper presents a solution to estimate sensor and actuator cyber-attacks in CVSs.A novel method is proposed that utilizes an augmented system representation technique and a nonlinear unknown input observer(UIO)to achieve asymptotic estimation of both CVS dynamics and cyber-attacks.The nonlinear CVS dynamics is represented in a Takagi–Sugeno(TS)fuzzy form with nonlinear consequents,which allows for the effective use of the differential mean value theorem to handle unmeasured premise variables.Furthermore,via Lyapunov stability theory sufficient conditions are proposed,expressed in terms of linear matrix inequalities,to design TS fuzzy UIO.Several test scenarios are performed with high-fidelity Simulink-CarSim co-simulations to show the effectiveness of the proposed cyber-attack estimation method.

Investigating safety and liability of autonomous vehicles:Bayesian random parameter ordered probit model analysis

Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.

A novel intelligent vehicle risk assessment method combined with multi-sensor fusion in dense traffic environment

Purpose–The purpose of this paper is to accurately capture the risks which are caused by each road user in time.Design/methodology/approach–The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment.Firstly,they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory.This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception.The information of object type,position and velocity was accurately obtained.Then,they conducted several experiments in real dense traffic environment on highways and urban roads,which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios.By analyzing the generation process of traffic risks between vehicles and the road environment,the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.Findings–The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking,and the road traffic risk was described as afield of equivalent force.The results extend the understanding of the traffic risk,which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.Originality/value–This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception.The information of object type,position and velocity was used to reduce erroneous data association between tracks and detections.Then,the authors conducted several experiments in real dense traffic environment on highways and urban roads,which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios.By analyzing the generation process of traffic risks between vehicles and the road environment,the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

LoS sensing-based superimposed CSI feedback for UAV-assisted mmWave systems

In Unmanned Aerial Vehicle(UAV)-assisted millimeter Wave(mmWave)systems,Channel State Information(CSI)feedback is critical for the selection of modulation schemes,resource management,beamforming,etc.However,traditional CSI feedback methods lead to significant feedback overhead and energy consumption of the UAV transmitter,therefore shortening the system operation time.To tackle these issues,inspired by superimposed feedback and Integrated Sensing and Communications(ISAC),a Line of Sight(LoS)sensing-based superimposed CSI feedback scheme is proposed.Specifically,on the UAV transmitter side,the Ground-to-UAV(G2U)CSI is superimposed on the UAV-to-Ground(U2G)data to feed back to the ground Base Station(gBS).At the gBS,the dedicated LoS Sensing Network(LoS-SenNet)is designed to sense the U2G CSI in LoS and NLoS scenarios.With the sensed result of LoS-SenNet,the determined G2U CSI from the initial feature extraction will work as the priori information to guide the subsequent operation.Specifically,for the G2U CSI in NLoS,a CSI Recovery Network(CSI-RecNet)and superimposed interference cancellation are developed to recover the G2U CSI and U2G data.As for the LoS scenario,a dedicated LoS Aid Network(LoS-Aid Net)is embedded before the CSI-RecNet and the block of superimposed interference cancellation to highlight the feature of the G2U CSI.Compared with other methods of superimposed CSI feedback,simulation results demonstrate that the proposed feedback scheme effectively improves the recovery accuracy of the G2U CSI and U2G data.Besides,against parameter variations,the proposed feedback scheme presents its robustness.

Distributed Robust UAVs Formation Control Based on Semidefinite Programming

The formation control of unmanned aerial vehicle(UAV)swarms is of significant importance in various fields such as transportation,emergency management,and environmental monitoring.However,the complex dynamics,nonlinearity,uncertainty,and interaction among agents make it a challenging problem.In this paper,we propose a distributed robust control strategy that uses only local information of UAVs to improve the stability and robustness of the formation system in uncertain environments.We establish a nominal control strategy based on position relations and a semi-definite programming model to obtain control gains.Additionally,we propose a robust control strategy under the rotation setΩto address the noise and disturbance in the system,ensuring that even when the rotation angles of the UAVs change,they still form a stable formation.Finally,we extend the proposed strategy to a quadrotor UAV system with high-order kinematic models and conduct simulation experiments to validate its effectiveness in resisting uncertain disturbances and achieving formation control.