Search results

At the US passenger stations, train operations approaching terminating tracks rely on the engineer’s compliant behavior to safely stop before the end of the tracks. Noncompliance actions from the disengaged or inattentive engineers would result in hazards to train passengers, train crewmembers and bystanders at passenger stations. Over the past decade, a series of end-of-track collisions occurred at passenger stations with substantial property damage and casualties. This study’s developed systemic model and discussions present policymakers, railway practitioners and academic researchers with a flexible approach for qualitatively assessing railroad safety.

To achieve a system-based, micro-level analysis of end-of-track accidents and eventually promote the safety level of passenger stations, the systems-theoretic accident modeling and processes (STAMP), as a practical systematic accident model widely used in the complex systems, is developed in view of environmental factors, human errors, organizational factors and mechanical failures in this complex socio-technical system.

The developed STAMP accident model and analytical results qualitatively provide an explicit understanding of the system hazards, constraints and hierarchical control structure of train operations on terminating tracks in the US passenger stations. Furthermore, the safety recommendations and practical options related to obstructive sleep apnea screening, positive train control-based collision avoidance mechanisms, robust system safety program plans and bumping posts are proposed and evaluated using the STAMP approach.

The findings from STAMP-based analysis can serve as valid references for policymakers, government accident investigators, railway practitioners and academic researchers. Ultimately, they can contribute to establishing effective emergent measures for train operations at passenger stations and promote the level of safety necessary to protect the public. The STAMP approach could be adapted to analyze various other rail safety systems that aim to ultimately improve the safety level of railroad systems.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

The quantity of e-taxi in Bangladesh is increasing day by day, especially in the municipality area. With the increase of this e-taxi quantity, it becomes hard to provide parking space for these consequences the illegal parking on road. This parking consequences traffic congestion on the road and obstructs the free flow of traffic. So, this paper aims to investigate the present scenario of this e-taxi parking problem and provides a solution by finding out a suitable location for an e-taxi station by the analytic hierarchy process (AHP) approach.

For the study, both primary and secondary data were collected. Primary data on existing parking points on the road of e-taxi which consequences traffic congestion are collected from the Municipality area. Secondary data on the existing road network of the Pabna Municipality has collected from the MIDP data also from the literature review. For the suitability analysis process for establishing an e-taxi station, six variables were determined. These variables are determined from the previous studies and the expert opinion survey. The six variables are land use of the study area, road network of the study area, proximity to the office area, proximity to the educational facilities, proximity from the market and finally,proximity from the hospital. After the selection of the variables ranking value was determined from the expert opinion. Then using The AHP method final weight value is determined and, finally, with the assist of geographical information system.

From the resulting total 4,285 spots were found as optimally suitable spots are found which is almost 21% of the suitable spot. No mostly suitable spots are found from the GIS analysis. The moderately suitable spots were found in the prime number of 14,817 spots, almost 75% of the suitable spot. Likely the most suitable spots no partly suitable spots were found but the number of very few suitable spots was found in the number of 918, 4% of the suitable spot. A total of 20,020 spots was found as suitable for the construction of E-taxi station.

Finding out a suitable spot for e-taxi stand the traffic congestion can be solved, accident risk can be minimized during loading and unloading of passengers and the municipality authority can find a permanent solution for the traffic congestion problem.

Exploring the influencing factors on urban rail transit (URT) ridership is vital for travel demand estimation and urban resources planning. Among various existing ridership modeling methods, direct demand model with ordinary least square (OLS) multiple regression as a representative has considerable advantages over the traditional four-step model. Nevertheless, OLS multiple regression neglects spatial instability and spatial heterogeneity from the magnitude of the coefficients across the urban area. This paper aims to focus on modeling and analyzing the factors influencing metro ridership at the station level.

This paper constructs two novel direct demand models based on geographically weighted regression (GWR) for modeling influencing factors on metro ridership from a local perspective. One is GWR with globally implemented LASSO for feature selection, and the other one is geographically weighted LASSO (GWL) model, which is GWR with locally implemented LASSO for feature selection.

The results of real-world case study of Shenzhen Metro show that the two local models presented perform better than the traditional global model (OLS) in terms of estimation error of ridership and goodness-of-fit. Additionally, the GWL model results in a better fit than GWR with global LASSO model, indicating that the locally implemented LASSO is more effective for the accurate estimation of Shenzhen metro ridership than global LASSO does. Moreover, the information provided by both two local models regarding the spatial varied elasticities demonstrates the strong spatial interpretability of models and potentials in transport planning.

The main contributions are threefold: the approach is based on spatial models considering spatial autocorrelation of variables, which outperform the traditional global regression model – OLS – in terms of model fitting and spatial explanatory power. GWR with global feature selection using LASSO and GWL is compared through a real-world case study on Shenzhen Metro, that is, the difference between global feature selection and local feature selection is discussed. Network structures as a type of factors are quantified with the measurements in the field of complex network.

Railway-level crossings (RLCs) are the point of intersection between rail and road users and are therefore hotpots of road-rail user conflict and catastrophic collisions. The purpose of this study is to assess the risks associated with RLCs and suggest probable reduction measures. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of Addis Ababa light rail transit (AA-LRT) north-south (N-S) route. The identified risky events are then categorized based on As Low As Reasonably Practicable (ALARP) principle and generic risk ranking matrix. The authors then examine existing safety management measures at railway crossing and assess the need for additional safety management. Five major crossings on the 16.9 km (10.5 mi) N-S line, starting from Menelik II Square to Kality, were considered for the study. This study is carried out by data collection from about 145 stakeholders and the application of statistical data and risk analysis methods. The major findings of this study and the recommendations for improvement are suggested.

The research followed a case study approach. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of AA-LRT N-S route. The identified risky events are then categorized based on ALARP principle and generic risk ranking matrix. Collected data was then analyzed using SPSS to deduce relationships.

The study findings reveal human factors as the greatest cause of accidents, injury or death. About 22% of hazards identified by category are human factors, whereas 20% are because of technical problems. Intolerable risks stand at 42%, whereas the tolerable risks are at 36% according to risk classification results as per the ALARP model. Because the process of risk management is a long-term cycle, its importance should not be missed at any time.

Because of design considerations of RLCs and the difference in generalized human behaviors for people of a given region, the results are limited to AA-LRT RLCs. This study opens a discourse for detailed evaluations, qualitative and quantitative analysis into the categorized identified hazards. There is also room for additional research into the performance of RLCs aimed at formulating standard necessary features that should be included on RLCs for proper risk control especially in emerging economies.

The research paper is original and has not been submitted for consideration to other journals.

Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

This paper presents comparative studies of modern transportation systems in the Bengal Delta and British Borneo. To meet the demands of the new modes of resource extraction, the British colonial rulers introduced a new transportation system in both regions and built roads, railways, and navigational routes connecting major commercial and political centers. There has been little research into the historical connections between modern transportation and environmental changes in colonial South Asia and Malaysia. When modern transportation was introduced, environmental consequences were rarely considered. As a result, significant ecological changes and declines were unintentionally caused. The environmental changes brought about by these transportation systems in these two regions were not the same one from the other. For example, railroad construction harmed the plains and waterways in the Bengal Delta, whereas, in British Borneo, rubber plantations for the global market harmed the rainforests.

This paper aims to study the impact of human resource heterogeneity on firms’ cash-holding policies.

The authors construct a proxy for human resource heterogeneity using the dissimilarity in employees’ skill structure between the firm and its peers in the same industry.

The authors report evidence that firms with heterogeneous human resources hold more cash than other firms. This effect is more pronounced in labor-intensive firms and firms more susceptible to hold-up by employees, i.e. firms located in regions with more labor disputes and firms surrounded by more external employment opportunities. In addition, the authors demonstrate that high cash holdings triggered by human resource heterogeneity reduce the scale and efficiency of firms’ capital investment.

This study highlights the role of human resource heterogeneity in determining firms’ cash policies. This paper adds to the understanding of labor adjustment costs within the firm and provides insights into firms’ cash-holding decisions.

The causes of high-speed railway failures are complex, and it is difficult to quantitatively and accurately describe safety evaluation. The purpose of this paper is to construct a model to ensure the safety of high-speed railway operations.

The authors construct a high-speed railway operation safety evaluation index system from four aspects: personnel, equipment, environment and management and analyze the inter-coupling relationship of various safety factors. Based on the evaluation index system, the use of network analytic hierarchy process (ANP) and fuzzy comprehensive evaluation will be used to establish a high-speed railway operation safety evaluation model.

Through the literature investigation and field investigation, combined with high-speed railway safety key points and system composition, 4 first-level indicators and 17 second-level indicators were selected to construct a high-speed railway operation safety evaluation index system. It can be seen from the results that the personnel management system and the signal and control system have the largest weight.

On the basis of establishing an evaluation index system, comprehensively considering the internal coupling relationship between evaluation indexes and the fuzziness of high-speed railway operation safety evaluation, high-speed railway uses ANP fuzzy network analysis method to construct high-speed railway operation, and the safety evaluation model has certain advantages and practicability in the case of the relative lack of high-speed railway operation data and fault data.