Energy-saving operation approaches for urban rail transit systems

In an urban rail transit system, issues regarding headway regulation have aroused wide attention. The assurance of headway regularity can decrease train delay times and average passenger waiting times. An integrated control method is proposed to optimize train headway by adjusting the train arrival time at stations. The adjustment of train arrival time is achieved by using an analytical method, and then the speed profile for each train is calculated by a suboptimal method, which has been applied in a practical system. Through simulation, the CPU time for calculating optimal train arrival time and speed profile is analyzed, respectively. The analysis demonstrates that the proposed method satisfies the real-time requirements for solving the headway regulation problem. By adopting the proposed method, the average passenger waiting time and the energy consumption can be decreased. In particular, the proposed method has better performance when the dispatch headway is large.

In reality, the risk in urban rail transit system usually happens. In this paper, we construct the risk chain network in urban rail transit system, where the different factors are considered in detail. Moreover, in order to describe the characteristic of the risk chain network, the propagation risk is proposed. Based on these, the controllability of risk chain network is calculated in four kinds of systems in urban rail transit system. In addition, we analyze the key node, which has a serious impact on the controllability. Our paper may be useful to control the risk in urban rail transit system and improve the safety of urban rail transit.

Traction power consumption is an important part of energy consumption in railways. Many parameters, such as the geometric structure of the line, vehicle characteristics, and passenger density, affect the traction power consumption. Besides these parameters, the most important factor affecting the traction power consumption of a train is the speed profile of the train. Development of the speed profile has significant potential in energy efficiency. The objective of this study is to set an optimization model to minimize energy consumption and the size of the on-board energy storage device as much as possible, based on the appropriate train speed profile and recuperation of braking energy along the route, determined on a tram line with a ground-level energy supply system, and solving the optimization model by using a genetic algorithm (GA). In the study, a speed profile optimization is presented using GA. The objective function is to find the optimal maximum operation speed limit and speed profile that will reduce energy consumption and the on-board energy storage device size requirement within the specified running time based on operation expectations for each inter-station zone. In the mentioned speed profile optimization, constraints such as maximum and minimum running time for each inter-station zone, maximum operation speed limit for each inter-station zone, maximum acceleration and deceleration are taken into account. The simulation results show that energy savings for traction of up to 60% can be achieved compared with the existing system structure, with the usage of the recommended hybrid energy storage unit and optimized speed profile.

One inherent nature of the passenger transportation industry is that passengers are directly involved in the entire production process--the transportation itself, and they are always in the center of everything we do in managing the operations of an Urban Rail Transit (URT) system. Hence, a full understanding of the role and the impact of URT passengers is fundamental to the success of the operation of any URT systems. With new technologies being introduced into URT systems, the role of URT passengers has been changing. Traditionally, the role of URT passengers is in general a passive one. However, modern URT systems are increasingly witnessing passengers taking a more and more active role. Thus, a review and rethink of the passenger's role in an URT system is extremely necessary.

Wireless Local Area Network (WLAN) is currently used in the train-ground communication for the urban rail transit systems. Due to the high speed and frequency band limitations, WLAN is unable to meet the demand of future city and intercity rail transit. Time Division-Long Term Evolution (TD-LTE) technology allows to construct a flexible service environment compared with current WLAN based system. In this paper, a TD-LTE based train-ground communication system for the urban rail transit system is given. It integrates all the applications in urban rail transit system. An outdoor testing environment is set up to test the performance of the integrated TD-LTE based train-ground communication system. The packet loss rate, response time, throughput of the TD-LTE system are analyzed. Extensive testing results show that the Quality of Service (QoS) of the integrated TD-LTE based train-ground communication system satisfies the requirements of urban rail transit system.

Risk evaluation of urban rail transit emergencies using a multilayer hypernetwork approach

Establishing simulation models is a widely used and effective approach for analysing passenger flow distribution in urban rail transit systems. Recently, multi-agent and discrete event-based simulation models have shown exceptional performance in studying passenger flow information within urban rail transit systems. While simulations of passengers and trains often yield satisfactory results, few models capture the overall operational status of urban rail transit systems. The complex interactions among stations, trains and passengers make it challenging to integrate these elements into a unified system framework. In this paper, we introduce a triple simulation framework that integrates stations, trains and passengers as foundational elements to comprehensively simulate the entire urban rail transit system and observe overall passenger flow distribution. Experimental results demonstrate that our system surpasses existing advanced simulation models, achieving an accuracy rate of 88.44% with a tolerance for a 30% deviation. To further illustrate the effectiveness of our framework in analysing passenger flows, we conducted experiments using the Nanjing Metro AFC dataset, analysing passenger flow distributions at stations and on trains.

Rail transit is a typical Cyber-physical Systems (CPS). The study of urban rail transit CPS was carried out with the introduction of CPS into the urban rail transit system. Based on the analysis of CPS, the fundamental architecture of urban rail transit CPS was designed and the functions of corresponding layers were explained. The system model of urban rail transit CPS was proposed. The functions of the model and the interaction between each model were explained. The issue of heterogeneous networks integration in rail transit system and train system was analyzed. Meanwhile, according to the actual demand of security monitoring and management of train running, network controller between WSN and control bus was designed and verified. The results show that the network controller can well achieve data exchange between WSN and train network.

An Approach to Calculate Overall Efficiency of Rolling Stock for an Urban Rail Transit System

Travel time reliability is of high importance for passengers and transit agencies in the urban rail transit system. The travel time reliability models of OD pairs, line and network were established, and a short discussion on influence factors of travel time reliability was provided. Based on the real urban rail AFC data, the distribution of travel time was analyzed and a methodology based on kernel density estimation was presented to evaluate travel time reliability. Beijing urban rail transit system was used as a case study. It concluded that the travel time reliability is related to journey distance, interchange times and travel time segment. Keywords-urban rail transit; travel time reliability; kernel density estimation

Vibration from urban rail transit system may cause vibration of buildings in subway system or vibration of bridges in elevated rail system, this vibration from building or bridges will generate so called vibration induced secondary noise with a strong low frequency character. Although the A-weighted level is below the limit of local regulations, frequent complains showed A-weighted level not a proper criteria for annoyance. Many research work have been done on low frequency noise, but diversify results were shown in the literature. In this paper, frequency and level depending property of annoyance from rail transit vibration induced low frequency noise was studied through subjective evaluation, and a LF-weighting curve was proposed on the basis of A-weighting curve with the correction below 500Hz, with mathematical description formulated and correction value tabled. Calculated levels according to the proposed LF-weighting curve showed high correlation with subjective annoyance. Results of subjective annoyance on sound level showed that annoyance growing exponentially with the increase of linear SPL. Thereafter, a comprehensive mathematical relation between annoyance and frequency and strength of noise was built, and proved to be effective in evaluating the annoyance caused by low frequency noise from rail transits.

The reduction of train energy consumption is becoming more important due to increasing worldwide environmental concerns. This paper presents a driving strategy optimization study and field test results on an urban rail transit system. A genetic algorithm based optimization method has been developed specifically for this purpose. In order to identify and evaluate the practicability and performance of the optimization results, a field test has been carried out on Guangzhou Metro Line No. 7. A driver training study has been developed to help drivers to implement the energy saving features of the optimization. The field test results show that by applying the optimal driver strategy the train traction energy consumption can be significantly reduced within the given journey time constant, proving the developed optimization method is practicable and effective.

Most of the existing urban rail CBTC train ground communication systems are based on Wireless Local Networks (WLAN) technologies. With frequency interference and the increase of train speed, WLAN is incapable of meeting the requirements of CBTC train ground communication systems. Time Division-Long Term Evolution (TD-LTE) technology begins to be considered in urban rail transit systems. In this paper, we first design a TD-LTE based urban rail CBTC train ground communication systems, the handover procedure and handover requirements according to CBTC system principle are analyzed next. For verifing whether the designed TD-LTE based system meet the handover performance demands when trains travel in high speed CBTC systems, a laboratory test environment and a real field test environment are set up. Massive test results show that the handover performance of TD-LTE based urban rail CBTC train ground communication systems meets the demands of urban rail transit systems.

Both passenger demand and service supply are among the most important factors that determine the performance of urban rail transit system. It is not easy to find out optimal solution for the match between the passenger demand and service supply with traditional methods, due to the complexity of the combinatorial intelligent supply - demand matching problem. In order to get the comprehensively optimal matching degree, this paper transforms the multi-criteria problem into the distributed artificial intelligence optimization by using multi-agent dynamic interaction technique. On the demand side, the dynamic passenger traffic demand with agents is modelled from perspective of boundedly rational travel decision. On the supply side, the dynamic service supply of train traffic with agent is modelled. The headway time is designated as the main decision variable, for the key link between the passenger demand and service supply is the headway time in different time-of-day intervals. To make the passenger demand more closely matched with service supply in urban rail transit network system at the reasonable travel cost and operational cost, the calculation formula for matching degree is proposed, along with the distributed system architecture for agent-based matching mechanism, and the negotiation-based iterative mechanisms for balancing. The proposed methods are validated on the simulation platform NetLogo. The simulation results emphasize the importance of representing the supply side and the demand side jointly/interactively. These findings are meaningful for policies on both development of efficient capacity usage strategies of urban rail transit network and provision of high level of service for passengers.

The problem of railway alignment optimization is studied, with particular attention given to computing lifecycle costs while considering train speed profile optimization and traffic demand. Recurring expenses, including energy, user, and maintenance costs, are considered in the lifecycle. A novel speed profile optimization method for the energy-efficient operation of trains is developed and incorporated in a simulation model, which considers regenerative braking energy. According to the train motion simulation results, the energy consumption and travel time per round trip are obtained, based on which the recurring costs are computed by taking traffic demand into account. The horizontal and vertical alignments are jointly optimized with the train speed profile based on the computed recurring and initial expenses, which include rolling stock, earthwork, bridge, tunnel, right-of-way, and length-dependent construction costs. A case study and sensitivity analyses are presented to discuss the impacts of traffic demand on the optimized railway alignment. The effectiveness of the speed profile optimization method is demonstrated by comparing its simulated results with those without speed control.