Application of Automated Guided Vehicles in Smart Automated Warehouse Systems:A Survey

Automated Guided Vehicles(AGVs)have been introduced into various applications,such as automated warehouse systems,flexible manufacturing systems,and container terminal systems.However,few publications have outlined problems in need of attention in AGV applications comprehensively.In this paper,several key issues and essential models are presented.First,the advantages and disadvantages of centralized and decentralized AGVs systems were compared;second,warehouse layout and operation optimization were introduced,including some omitted areas,such as AGVs fleet size and electrical energy management;third,AGVs scheduling algorithms in chessboardlike environments were analyzed;fourth,the classical route-planning algorithms for single AGV and multiple AGVs were presented,and some Artificial Intelligence(AI)-based decision-making algorithms were reviewed.Furthermore,a novel idea for accelerating route planning by combining Reinforcement Learning(RL)andDijkstra’s algorithm was presented,and a novel idea of the multi-AGV route-planning method of combining dynamic programming and Monte-Carlo tree search was proposed to reduce the energy cost of systems.

Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms

The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.

Road User Charging for Urban Freight Vehicles: A Systems Approach

Road user charging (RUC) has a long history as a mechanism to recover infrastructure maintenance and capital costs. The present RUC systems are facing issues such as transparency, cross-subsidization, environmental concerns and reducing revenue due to the likes of lessening fuel tax as vehicles become more efficient. Therefore, this paper reviews the strengths and weaknesses of the present RUC mechanisms implemented in the world with respect to stakeholder problems and demands of the freight industry and to describe the need for a more appropriate, practical and sustainable approach that can be used in the future. Finally, a model is proposed that is transparent and considers usage-based charging addressing most of the weaknesses highlighted in the models reviewed. Further, it considers externalities produced by heavy vehicles into account. The model has the potential to provide answers to key stakeholder issues and will lead to a sustainable freight transport system in the future. Encouraging fuel-efficient modes, optimization of loading, routing and logistics systems, and long term land use planning are a few of them.

μ-Syntheses of Suspension Systems for EMS and EDS Maglev Vehicles

Under model uncertainty and complex disturbance, the robust control strategy should be used in suspension control systems for various Maglev vehicles to obtain ride comfort of passengers. In this paper, the robust controllers are synthesized using μ approach for levitation system of electromagnetic Maglev vehicle and active suspension system of super conducting Maglev vehicle. The numerical simulations for different parameter perturbations and different disturbances are accomplished, and a comparison of μ control and H ∞ control is performed. The simulation results show that, both H ∞ control and μ control for two kinds of Maglev vehicles exhibit good stability robustness to plant model uncertainty, but μ control exhibits better performance robustness than H ∞ control, therefore better ride quality could be obtained by μ control.

Fuzzy Logic Control for Suspension Systems of Tracked Vehicles

A scheme of fuzzy logic control for the suspension system of a tracked vehicle is presented. A mechanical model for the whole body of a tracked vehicle, which is totally a fifteen-degree-of-freedom system, is established. The model includes the vertical motion, the pitch motion as well as the roll motion of the tracked vehicle. In contrast to most previous studies, the coupling effect among the vertical, the pitch and the roll motions of the suspension system of a tracked vehicle is considered simultaneously. The simulation of fuzzy logic control under road surface with random excitation shows that the acceleration, pitch angle and roll angle of suspension system can be efficiently controlled.

Analysis of Hybrid Rechargeable Energy Storage Systems in Series Plug-In Hybrid Electric Vehicles Based on Simulations

In this paper, an extended analysis of the performance of different hybrid Rechargeable Energy Storage Systems (RESS) for use in Plug-in Hybrid Electric Vehicle (PHEV) with a series drivetrain topology is analyzed, based on simulations with three different driving cycles. The investigated hybrid energy storage topologies are an energy optimized lithium-ion battery (HE) in combination with an Electrical Double-Layer Capacitor (EDLC) system, in combination with a power optimized lithium-ion battery (HP) system or in combination with a Lithium-ion Capacitor (LiCap) system, that act as a Peak Power System. From the simulation results it was observed that hybridization of the HE lithium-ion based energy storage system resulted from the three topologies in an increased overall energy efficiency of the RESS, in an extended all electric range of the PHEV and in a reduced average current through the HE battery. The lowest consumption during the three driving cycles was obtained for the HE-LiCap topology, where fuel savings of respectively 6.0%, 10.3% and 6.8% compared with the battery stand-alone system were achieved. The largest extension of the range was achieved for the HE-HP configuration (17% based on FTP-75 driving cycle). HP batteries however have a large internal resistance in comparison to EDLC and LiCap systems, which resulted in a reduced overall energy efficiency of the hybrid RESS. Additionally, it was observed that the HP and LiCap systems both offer significant benefits for the integration of a peak power system in the drivetrain of a Plug-in Hybrid Electric Vehicle due to their low volume and weight in comparison to that of the EDLC system.

Video Based Vehicle Detection and its Application in Intelligent Transportation Systems

Video based vehicle detection technology is an integral part of Intelligent Transportation System (ITS), due to its non-intrusiveness and comprehensive vehicle behavior data collection capabilities. This paper proposes an efficient video based vehicle detection system based on Harris-Stephen corner detector algorithm. The algorithm was used to develop a stand alone vehicle detection and tracking system that determines vehicle counts and speeds at arterial roadways and freeways. The proposed video based vehicle detection system was developed to eliminate the need of complex calibration, robustness to contrasts variations, and better performance with low resolutions videos. The algorithm performance for accuracy in vehicle counts and speed was evaluated. The performance of the proposed system is equivalent or better compared to a commercial vehicle detection system. Using the developed vehicle detection and tracking system an advance warning intelligent transportation system was designed and implemented to alert commuters in advance of speed reductions and congestions at work zones and special events. The effectiveness of the advance warning system was evaluated and the impact discussed.

Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians.Consequently,traffic signs have been of great importance for every civilized country,which makes researchers give more focus on the automatic detection of traffic signs.Detecting these traffic signs is challenging due to being in the dark,far away,partially occluded,and affected by the lighting or the presence of similar objects.An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues.This technique aimed to devise an efficient,robust and accurate approach.To attain this,initially,the approach presented a new formula,inspired by existing work,to enhance the image using red and green channels instead of blue,which segmented using a threshold calculated from the correlational property of the image.Next,a new set of features is proposed,motivated by existing features.Texture and color features are fused after getting extracted on the channel of Red,Green,and Blue(RGB),Hue,Saturation,and Value(HSV),and YCbCr color models of images.Later,the set of features is employed on different classification frameworks,from which quadratic support vector machine(SVM)outnumbered the others with an accuracy of 98.5%.The proposed method is tested on German Traffic Sign Detection Benchmark(GTSDB)images.The results are satisfactory when compared to the preceding work.

Reentry Attitude Tracking Control for Hypersonic Vehicle with Reaction Control Systems via Improved Model Predictive Control Approach

This paper studies the reentry attitude tracking control problem for hypersonic vehicles(HSV)equipped with reaction control systems(RCS)and aerodynamic surfaces.The attitude dynamical model of the hypersonic vehicles is established,and the simplified longitudinal and lateral dynamic models are obtained,respectively.Then,the compound control allocation strategy is provided and the model predictive controller is designed for the pitch channel.Furthermore,considering the complicated jet interaction effect of HSV during RCS is working,an improved model predictive control approach is presented by introducing the online parameter estimation of the jet interaction coefficient for dealing with the uncertainty and disturbance.Moreover,considering the strong coupling effect between the yaw channel and roll channel,a coupled model predictive controller is designed by introducing the feedback of sideslip angle into the roll control channel to eliminate the coupling effect.Finally,the comparison simulations using the classical control method,MPC and IMPC approach are given to demonstrate the effectiveness and efficiency of the presented IMPC scheme.

Shadow Extraction and Elimination of Moving Vehicles for Tracking Vehicles

Shadow extraction and elimination is essential for intelligent transportation systems(ITS)in vehicle tracking application.The shadow is the source of error for vehicle detection,which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting,vehicle detection,vehicle tracking,and classification.Most of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets,but the process of extracting shadows from moving vehicles in low light of real scenes is difficult.The real scenes of vehicles dataset are generated by self on the Vadodara–Mumbai highway during periods of poor illumination for shadow extraction of moving vehicles to address the above problem.This paper offers a robust shadow extraction of moving vehicles and its elimination for vehicle tracking.The method is distributed into two phases:In the first phase,we extract foreground regions using a mixture of Gaussian model,and then in the second phase,with the help of the Gamma correction,intensity ratio,negative transformation,and a combination of Gaussian filters,we locate and remove the shadow region from the foreground areas.Compared to the outcomes proposed method with outcomes of an existing method,the suggested method achieves an average true negative rate of above 90%,a shadow detection rate SDR(η%),and a shadow discrimination rate SDR(ξ%)of 80%.Hence,the suggested method is more appropriate for moving shadow detection in real scenes.

Dynamic Cell Modeling for Accurate SOC Estimation in Autonomous Electric Vehicles

This paper presents findings on dynamic cell modeling for state-of-charge (SOC) estimation in an autonomous electric vehicle (AEV). The studied cells are Lithium-Ion Polymer-based with a nominal capacity of around 8 Ah, optimized for power-needy applications. The AEV operates in a harsh environment with rate requirements up to ±25C and highly dynamic rate profiles, unlike portable-electronic applications with constant power output and fractional C rates. SOC estimation methods effective in portable electronics may not suffice for the AEV. Accurate SOC estimation necessitates a precise cell model. The proposed SOC estimation method utilizes a detailed Kalman-filtering approach. The cell model must include SOC as a state in the model state vector. Multiple cell models are presented, starting with a simple one employing “Coulomb counting” as the state equation and Shepherd’s rule as the output equation, lacking prediction of cell relaxation dynamics. An improved model incorporates filter states to account for relaxation and other dynamics in closed-circuit cell voltage, yielding better performance. The best overall results are achieved with a method combining nonlinear autoregressive filtering and dynamic radial basis function networks. The paper includes lab test results comparing physical cells with model predictions. The most accurate models obtained have an RMS estimation error lower than the quantization noise floor expected in the battery-management-system design. Importantly, these models enable precise SOC estimation, allowing the vehicle controller to utilize the battery pack’s full operating range without overcharging or undercharging concerns.

Modeling and Simulation of aCounter-Rotating Turbine System for Underwater Vehicles

一台相反旋转的汽轮机的结构一在水下车辆被在常规单个阶段的汽轮机以后增加相反旋转的秒阶段汽轮机磁盘设计。可得到的动能和辅助系统的吸收力量以不同工作条件被计算，并且结果证明在相反旋转的汽轮机系统的主要引擎和辅助系统的力量与对方一起匹配很好。恰好在相反旋转的汽轮机系统的技术计划被建议以前，润滑的油环，燃料环，和海水循环的试验性的模拟被完成。模拟结果显示水力的传播系统能满足要求为一在水下车辆在一次稳定的航行或可变工作条件运行。

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 slip angle are fast.

Impact of Electric Vehicles on a Carbon Constrained Power System—A Post 2020 Case Study

Electric vehicles (EVs) offer great potential to move from fossil fuel dependency in transport once some of the technical barriers related to battery reliability and grid integration are resolved. The European Union has set a target to achieve a 10% reduction in greenhouse gas emissions by 2020 relative to 2005 levels. This target is binding in all the European Union member states. If electric vehicle issues are overcome then the challenge is to use as much renewable energy as possible to achieve this target. In this paper, the impacts of electric vehicle charged in the all-Ireland single wholesale electricity market after the 2020 deadline passes is investigated using a power system dispatch model. For the purpose of this work it is assumed that a 10% electric vehicle target in the Republic of Ireland is not achieved, but instead 8% is reached by 2025 considering the slow market uptake of electric vehicles. Our experimental study shows that the increasing penetration of EVs could contribute to approach the target of the EU and Ireland government on emissions reduction, regardless of different charging scenarios. Furthermore, among various charging scenarios, the off-peak charging is the best approach, contributing 2.07% to the target of 10% reduction of Greenhouse gas emissions by 2025.

Full Power Hydraulic Brake System Based on Double Pipelines for Heavy Vehicles

The hydraulic caliper disc brake system with air-over-oil is widely adopted at present for heavy vehicles,which makes use of air pressure system propelling the hydraulic pressure system acting on friction plates divided and combined for braking.There are some disadvantages such as pneumatic components failure,dust polluted and produce lots of heat in hydraulic caliper disc brake system.Moreover,considering the demands of the high speed,heavy weight,heavy load and fast brake of heavy vehicles,the full power hydraulic brake system based on double pipelines for heavy vehicles is designed and analyzed in this paper.The scheme of the full power hydraulic brake system,in which the triloculare cylinder is controlled by dual brake valve,is adopted in the brake system.The full power hydraulic brake system can accomplish steering brake,parking brake and emergent brake for heavy vehicles.Furthermore,electronic control system that is responsible for coordinating the work of hydraulic decelerator and hydraulic brake system is developed for different speed brakes.Based on the analysis of the influence of composed unit and connecting pipeline on braking performance,the nonlinear mathematic model is established for the full power hydraulic brake system.The braking completion time and braking pressure in braking performance of the double-pipeline steering brake and parking brake are discussed by means of simulation experiments based on Matlab/Simulink,and the simulation results prove that the braking performance of steering brake and parking brake meets the designing requirement of the full power hydraulic brake system.Moreover,the test-bed experiments of the brake system for heavy vehicles are carried out.The experimental data prove that the braking performance achieves the goal of the design,and that the full power hydraulic brake system based on double pipelines can effectively enhance braking performance,ensure braking reliability and security for heavy vehicles.

ROBUST STABILITY ANALYSIS FOR RAILWAY VEHICLE SYSTEMS

The lateral stability for railway vehicle dynamic system with uncertainparameters and nonlinear uncertain force vector is studied by using the Lyapunov stability theory. Arobust stability condition for the considered system is derived, and the obtained stability boundsare not necessarily symmetric with respect to the origin in the parameter space. The lateralstability analysis for a railway bogie model is analyzed by using the proposed approach. Thesymmetric and asymmetric results are both given and the influence of the adjustable parameter betaon the stability bounds is also discussed. With the help of the proposed method, the robuststability analysis can provide a reference for the design of the railway vehicle systems.

A New Coordinated Fuzzy-PID Controller for Power System Considering Electric Vehicles

With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.

Development of City Transport System and Two-wheel Vehicles

Based on the study on the city transport systems of some typical cities worldwide,this paper put forward that each city transport system has its own development mode,which is influenced by the city development plan,economic development level,traveling vehicle composition etc..When some problems occur,such as the congestions caused by contradiction between the road capacity and vehicle composition,the city transport system may come into temporary maturity period.If the improvement for road system is limited meanwhile,optimized structure of vehicle composition should be an effective solution in this case.With the development of economy-internationalization,the development speed of city transport modernization is rapid.When traveling easiness is conflicting with efficiency,the advantages of public transport system become more obvious.Correspondingly,the superiority of two-wheel vehicles will reappear.Though the important function of two-wheel vehicles for alleviating city traffic problems is obvious,however,their development strategy must be reasonably proposed,and operation regulations must be performed accordingly.

Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management

Recently,autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare,agriculture,industrial automation,etc.Among the interesting applications of autonomous systems,their applicability in agricultural sector becomes significant.Autonomous unmanned aerial vehicles(UAVs)can be used for suitable site-specific weed management(SSWM)to improve crop productivity.In spite of substantial advancements in UAV based data collection systems,automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops.The recently developed deep learning(DL)models have exhibited effective performance in several data classification problems.In this aspect,this paper focuses on the design of autonomous UAVs with decision support system for weed management(AUAV-DSSWM)technique.The proposed AUAV-DSSWM technique intends to identify the weeds by the use of UAV images acquired from the target area.Besides,the AUAV-DSSWM technique primarily performs image acquisition and image pre-processing stages.Moreover,the Adam optimizer with You Only Look Once Object Detector-(YOLOv3)model is applied for the detection of weeds.For the effective classification of weeds and crops,the poor and rich optimization(PRO)algorithm with softmax layer is applied.The design of Adam optimizer and PRO algorithm for the parameter tuning process results in enhanced weed detection performance.A wide range of simulations take place on UAV images and the experimental results exhibit the promising performance of the AUAV-DSSWM technique over the other recent techniques with the accy of 99.23%.