INCORPORATING MEASURES TO REDUCE GROUND VIBRATION PRODUCED BY BLASTING FOR QUARRY SAFETY MANAGEMENT: A CASE STUDY

The European Union policy strategies on the sustainability of the transport system pursue the goals of maximizing safety and environmental benefits and reducing the severity and frequency of crashes, congestion, and pollutant emission rates. A common issue is the planning of the most effective solution for operational and safety management at intersections. In this study, an egg turbo roundabout is proposed as the alternative solution to a conventional roundabout in Southern Italy which suffers from traffic congestion. A comparative analysis is carried out using microsimulation techniques to investigate the safety effects and operational improvements of converting a traditional priority intersection into standard roundabout or turbo roundabout layout. In particular, the VISSIM software is used to explore the most relevant operational performance measures: queue length, travel times and delays. The lowest values of these measurements are recorded for the simulated turbo roundabout, thus making this scheme more appropriate in terms of operational performances. With regard to safety analysis, the Surrogate Safety Assessment Model (SSAM) is used to collect information on the predicted number of conflicts, the probability, and severity of the potential collisions. The results suggest that, for the specific case study, the safety levels of the standard roundabout and the turbo roundabout are approximately comparable.

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The Implementation of a Health and Safety Management System and its Interaction with Organisational/Safety Culture: An Industrial Case Study

Policy and Practice in Health and Safety ◽

10.1080/14774003.2005.11667654 ◽

2005 ◽

Vol 3 (1) ◽

pp. 17-39 ◽

Cited By ~ 1

Author(s):

David Baird

Keyword(s):

Safety Culture ◽

Management System ◽

Safety Management ◽

Health And Safety ◽

Industrial Case Study ◽

Safety Management System

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Information Sharing in Complex Systems: A Case Study on Public Safety Management

Procedia - Social and Behavioral Sciences ◽

10.1016/j.sbspro.2015.11.493 ◽

2015 ◽

Vol 213 ◽

pp. 722-727 ◽

Cited By ~ 7

Author(s):

Barbara Kożuch ◽

Katarzyna Sienkiewicz-Małyjurek

Keyword(s):

Complex Systems ◽

Information Sharing ◽

Public Safety ◽

Safety Management

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Early Warning Mechanism for the Surge of Passengers in Metro Systems Based on Automated Fare Collection Data: Case Study of Guangzhou, China

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119838847 ◽

2019 ◽

Vol 2673 (4) ◽

pp. 917-929 ◽

Cited By ~ 1

Author(s):

Ning Huan ◽

Enjian Yao ◽

Binbin Li

Keyword(s):

Early Warning ◽

Traffic Control ◽

Safety Management ◽

Early Stage ◽

Point Of View ◽

Control Measures ◽

Passenger Flow ◽

Early Warning Mechanism ◽

Metro Systems

Recently, surges of passengers caused by large gatherings, temporary traffic control measures, or other abnormal events have frequently occurred in metro systems. From the standpoint of the operation managers, the available information about these outside events is incomplete or delayed. Unlike regular peaks of commuting, those unforeseen surges pose great challenges to emergency organization and safety management. This study aims to assist managers in monitoring passenger flow in an intelligent manner so as to react promptly. Compared with the high cost of deploying multisensors, the widely adopted automated fare collection (AFC) system provides an economical solution for inflow monitoring from the application point of view. In this paper, a comprehensive framework for the early warning mechanism is established, including four major phases: data acquisition, preprocessing, off-line modeling, and on-line detection. For each station, passengers’ tapping-on records are gathered in real time, to be further transformed into a dynamic time series of inflow volumes. Then, a sequence decomposition model is formulated to highlight the anomaly by removing its inherent disturbances. Furthermore, a novel hybrid anomaly detection method is developed to monitor the variation of passenger flow, in which the features of inflow patterns are fully considered. The proposed method is tested by a numerical experiment, along with a real-world case study of Guangzhou metro. The results show that, for most cases, the response time for detection is within 5 min, which makes the surge phenomenon observable at an early stage and reminds managers to make interventions appropriately.

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