Automatic Driving Operation Strategy of Urban Rail Train Based on Improved DQN Algorithm

To realize a better automatic train driving operation control strategy for urban rail trains,an automatic train driving method with improved DQN algorithm(classical deep reinforcement learning algorithm)is proposed as a research object.Firstly,the train control model is established by considering the train operation requirements.Secondly,the dueling network and DDQN ideas are introduced to prevent the value function overestimation problem.Finally,the priority experience playback and“restricted speed arrival time”are used to reduce the useless experience utilization.The experiments are carried out to verify the train operation strategy method by simulating the actual line conditions.From the experimental results,the train operation meets the ATO requirements,the energy consumption is 15.75%more energy-efficient than the actual operation,and the algorithm convergence speed is improved by about 37%.The improved DQN method not only enhances the efficiency of the algorithm but also forms a more effective operation strategy than the actual operation,thereby contributing meaningfully to the advancement of automatic train operation intelligence.

Training on LSA lifeboat operation using Mixed Reality

Background This work aims to provide an overview of the Mixed Reality(MR)technology’s use in maritime industry for training purposes.Current training procedures cover a broad range of procedural operations for Life-Saving Appliances(LSA)lifeboats;however,several gaps and limitations have been identified related to the practical training that can be addressed through the use of MR.Augmented,Virtual and Mixed Reality applications are already used in various fields in maritime industry,but their full potential have not been yet exploited.SafePASS project aims to exploit MR advantages in the maritime training by introducing a relevant application focusing on use and maintenance of LSA lifeboats.Methods An MR Training application is proposed supporting the training of crew members in equipment usage and operation,as well as in maintenance activities and procedures.The application consists of the training tool that trains crew members on handling lifeboats,the training evaluation tool that allows trainers to assess the performance of trainees,and the maintenance tool that supports crew members to perform maintenance activities and procedures on lifeboats.For each tool,an indicative session and scenario workflow are implemented,along with the main supported interactions of the trainee with the equipment.Results The application has been tested and validated both in lab environment and using a real LSA lifeboat,resulting to improved experience for the users that provided feedback and recommendations for further development.The application has also been demonstrated onboard a cruise ship,showcasing the supported functionalities to relevant stakeholders that recognized the added value of the application and suggested potential future exploitation areas.Conclusions The MR Training application has been evaluated as very promising in providing a user-friendly training environment that can support crew members in LSA lifeboat operation and maintenance,while it is still subject to improvement and further expansion.

High-Speed Trains Automatic Operation with Protection Constraints: A Resilient Nonlinear Gain-based Feedback Control Approach

This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.

Braking distance prediction for vehicle consist in low-speed on-sight operation:a Monte Carlo approach

The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for lowspeed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.

Recording the direct surgeon’s view with an operating microscopic view improves microscopic ophthalmic surgery training

AIM:To establish a recording system with a direct view of the surgeon to supplement video recording under an operating microscope,which lacks information on the movement and position of the surgeon’s hands,and to facilitate the reproduction of a skilled surgeon’s technique by a surgeon in training.METHODS:A small camera was attached to the operating microscope with a custom adapter.Microscopic surgeon’s view and direct surgeon’s view through this new camera were recorded in the surgical recording system.Both movies were synchronized and analyzed how do surgeons handle the instruments.RESULTS:A small camera attached to the operating microscope allowed the surgeon’s hands motion to be recorded without interfering with the surgeon’s movements.Different surgeons used different methods to manipulate the ultrasound handpiece and the irrigation/aspiration device.Even in the simple paracentesis procedure,different surgeons used different methods.Surgeons-in-training were able to identify and improve their weaknesses by watching synchronized movies of their hand motions and microscopic view.CONCLUSION:Simultaneous recording the surgical field out of the operating microscopic view by a small camera set on the microscope is comprehensive and improves surgeons-in-training understanding and learning surgeries.

Operational Safety Assessment of a High-Speed Train Exposed to the Strong Gust Wind

The operational safety characteristics of trains exposed to a strong wind have caused great concern in recent years.In the present paper,the effect of the strong gust wind on a high-speed train is investigated.A typical gust wind model for any wind angle,named“Chinese hat gust wind model”,was first constructed,and an algorithm for computing the aerodynamic loads was elaborated accordingly.A vehicle system dynamic model was then set up in order to investigate the vehicle system dynamic characteristics.The assessment of the operational safety has been conducted by means of characteristic wind curves(CWC).As some of the parameters of the wind-train system were difficult to measure,we also investigated the impact of the uncertain system parameters on the CWC.Results indicate that,the descending order of the operational safety index of the vehicle for each wind angle is 90°-60°-120°-30°-150°,and the worst condition for the operational safety occurs when the wind angle reaches around 90°.According to our findings,the gust factor and aerodynamic side force coefficient have great impact on the critical wind speed.Thus,these two parameters require special attention when considering the operational safety of a railway vehicle subjected to strong gust wind.

The Research and Development of Integrated Operation-Maintenance Simulation Training System

With deep development of state grid’s system of "Three Sets of Five [1]", China is in urgent need of establishing an appropriate type of simulation system to rapidly improve operation efficiency and the level of maintainers, which aim at the integrated operation of substation operation and maintenance service. This article gives an introduction of a simulation training system which is designed for operation-skills training in electrical systems. By the composition of the multiple subjects and skills training for operations staff, this system can provide human guarantee and intellectual support for the "Big-Centralized Overhal".

Research on the cooperative train control method in the metro system for energy saving

Purpose–To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure,energy-saving performance of the whole metro system cannot be guaranteed.Design/methodology/approach–A cooperative train control framework is formulated to regulate a novel train operation mode.The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train.An improved brute force(BF)algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.Findings–Case studies on the actual metro line in Guangzhou,China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters.The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.Originality/value–Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process,which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation.This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea,where energy-efficient train operation can be realised once train running time is determined,thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Observation of early active training effects after the operation for lumber intervertebral disc herniation

Objective To explore the recent and distant effects of early active training after the operation for lumber intervertebral disc herniation.Method 79 patients after the operation for mono segmental lumber intervertebral disc herniation had been divided into early active training group and routine control group randomly, and accepted training, regular re-examination, and follow-up of 1～6 years respedtively.Results The early active training group had better recent and distant objective effect, and more patients (97.6%) were satisfied with the operational effects.Conclusions The early active training after the operation for lumber intervertebral disc herniation is positive significant for operational effects.

Approach of Training Working Staff of Power System Operation Mode Based on State Evaluation

An approach of training working staff of power system operation mode based on state evaluation is proposed. In terms of knowledge features of power system operation mode, we studied a training method based on evaluation of learning state. This training method makes individual learning for different individual condition to give them ability to grasp learning points quickly, evaluate real-time learning effect, update learning style in time and summarize problems after one learning stage, so that learners can master professional knowledge in constant summaries and feedbacks. Obvious effects can be obtained on discontinuous learning time that trainees can master basic theories associated with their working and operations adapted to practical work quickly.

Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm

A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme,and the initial population can be formed by the way.The fitness function can be designed by the design requirements of the train control stop error,time error and energy consumption.the effectiveness of new individual can be ensured by checking the validity of the original individual when its in the process of selection,crossover and mutation,and the optimal algorithm will be joined all the operators to make the new group not eliminate on the best individual of the last generation.The simulation result shows that the proposed genetic algorithm comparing with the optimized multi-particle simulation model can reduce more than 10%energy consumption,it can provide a large amount of sub-optimal solution and has obvious optimization effect.

Optimization method of urban rail train operational plan based on O-D time-varying demand

Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.

Optimal Energy-Efficient Operation of a Metro Train on a Long and Steep Downhill Segment

Because the standard four-stage operation and con-trol strategy cannot fully utilize the gravitational potential energy of a train operating on a long and steep downhill segment,this paper further improves the method for train operation and control strategy.The improved operation includes three stages of acceleration,coasting-speed limit cruising,and brak-ing.Taking the speed limit,time limit,and distance limit as the constraints,the coasting condition switching point,braking condition switching point,traction coefficient,and braking force coefficient are used as the decision variables.Then,an improved train traction energy consumption model is constructed,and an improved differential evolution algorithm is designed to solve this model.The improved method is used to simulate two long and steep downhill segments of the Nanning metro.The results show that the improved method can meet the requirements of speed limit,time limit,and distance limit.Compared with the standard four-stage operation,the improved train operation and control strategy can reduce train energy consumption by more than 40%on the two long and steep downhill segments;compared with other similar algorithms,the improved algorithm is more suitable for solving the model.

Interactive plant simulation modeling for developing an operator training system in a natural gas pressure-regulating station

This study proposes a method of interactive plant simulation modeling which delivers the online simulated results to the field operators and induces them to take proper actions in the case of pre-identified accident scenarios in a chemical plant. The developed model integrates the real-time process dynamic simulation with 3DCFD accident simulation in a designed interface using object linking and embedding technology so that it can convey to trainees the online information of the accident which is not available in existing operator training systems.The model encompasses the whole process of data transfer till the end of the training at which a trainee operates an emergency shutdown system in a programmed model. In this work, an overall scenario is simulated which is from an abnormal increase in the main valve discharge（second）pressure due to valve malfunction to accidental gas release through the crack of a pressure recorder, and the magnitude of the accident with respect to the lead time of each trainee＇s emergency response is analyzed. The model can improve the effectiveness of the operator training system through interactively linking the trainee actions with the simulation model resulting in different accident scenarios with respect to each trainee＇s competence when facing an accident.

System Restoration Tools: System Restoration Navigator Integrated into EPRI Operator Training Simulator (SRN/OTS)

System operators and planners develop and implement restoration plans based on off-line simulation studies, and accumulated experience and knowledge. One of the challenges in developing a restoration plan is to sift through numerous possible restoration scenarios and paths, in order to identify those that are technically feasible. When implementing a restoration plan in an on-line environment following a blackout, the operators need to adapt to the actual outage scenarios and available resources, and be constantly mindful of anticipated voltage and frequency excursions that must remain within system and equipment tolerances. In recognition of these challenges, EPRI has developed System Restoration Navigator (SRN), to provide decision support to system restoration planning and operations engineers in developing, evaluating and revising system restoration strategies, guidelines, plans and step-by-step procedures. During 2013-2014, EPRI developed SRN version 3.0, which is designed to facilitate its integration into a commercial operator training simulator (OTS) (AKA a dispatch training simulator, DTS). The integration of SRN 3.0 with an OTS allows operators to obtain experience in simulating, developing, experimenting with and revising system restoration plans, and to address related regulatory standards. The integration expands the usability of SRN 3.0 by providing the OTS platform for training purposes and for the purpose of interfacing SRN 3.0 with operational power system models to be able to explore near real time application of SRN 3.0. This 2013-2014 development work also included the integration of SRN 3.0 into EPRI OTS, and its application on the Florida Reliability Coordinating Council (FRCC) power system. A detailed account of development of SRN 3.0, its integration into EPRI OTS and its application to FRCC system is presented in this paper.

Best Practice Standards and Methodology for Crane Operator Training—A Global Perspective

Crane operators control mobile or stationary cranes to lift, move and place objects at locations such as building and construction sites, wharves and shipyards. This activity occurs all over the world and is a high risk task with many noted examples of serious incidents and accidents. There are identifiable key causes that have been noted through analysis of the well documented cases and many of these causes are preventable through effective training programs. Internationally, there are not currently consistent approaches to crane operator training program content or duration. Leading causes of crane accidents are firstly discussed and identified as areas for inclusion in training programs. A number of current training approaches from a range of countries are then considered and these are used to outline the basis of a generic competency standard for crane operation, as it was found that there are not common standards in place. The proposed competency standard can be adapted by training regulators, training providers, government agencies, industry bodies and enterprises as a benchmark for the development of effective training programs.

Dynamic train dwell time forecasting:a hybrid approach to address the influence of passenger flow fluctuations

Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between trains.Accurate estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity estimation.In the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train dispatching.The averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data distributions.Then,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway line.The results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and variances.Further,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,respectively.Based on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell time.However,planned time has positive influences,whereas arrival delay has negative influences.

A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways

Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.