Xiaobo Qu

Ship collision risk assessment for the Singapore Strait

The Singapore Strait is considered as the bottleneck and chokepoint of the shipping routes connecting the Indian and the Pacific Ocean. Therefore, the ship collision risk assessment is of significant importance for ships passing through the narrow, shallow, and busy waterway. In this paper, three ship collision risk indices are initially proposed to quantitatively assess the ship collision risks in the Strait: index of speed dispersion, degree of acceleration and deceleration, and number of fuzzy ship domain overlaps. These three risk indices for the Singapore Strait are estimated by using the real-time ship locations and sailing speeds provide by Lloyds MIU automatic identification system (AIS). Based on estimation of these three risk indices, it can be concluded that Legs 4W, 5W, 11E, and 12E are the most risky legs in the Strait. Therefore, the ship collision risk reduction solutions should be prioritized being implemented in these four legs. This study also finds that around 25% of the vessels sail with a speed in excess of the speed limit, which results in higher potentials of ship collision. Analysis indicates that the safety level would be significantly improved if all the vessels follow the passage guidelines.

An Overview of Maritime Waterway Quantitative Risk Assessment Models

The safe navigation of ships, especially in narrow shipping waterways, is of the utmost concern to researchers as well as maritime authorities. Many researchers and practitioners have conducted studies on risk assessment for maritime transportation and have proposed risk reduction/control measures accordingly. This article provides a detailed review and assessment of various quantitative risk assessment models for maritime waterways. Eighty-seven academic papers and/or project reports are summarized and discussed. The review then proceeds to analyze the frequency and consequence estimation models separately. It should be pointed out that we further summarize the advantages and disadvantages of frequency estimation models and provide recommendations for their application. From the overview, we find that the quantification of the impact of human error is of great importance and should be considered in future studies. Possible solutions are also proposed in the discussions.

Estimation of rear-end vehicle crash frequencies in urban road tunnels

According to The Handbook of Tunnel Fire Safety, over 90% (55 out of 61 cases) of fires in road tunnels are caused by vehicle crashes (especially rear-end crashes). It is thus important to develop a proper methodology that is able to estimate the rear-end vehicle crash frequency in road tunnels. In this paper, we first analyze the time to collision (TTC) data collected from two road tunnels of Singapore and conclude that Inverse Gaussian distribution is the best-fitted distribution to the TTC data. An Inverse Gaussian regression model is hence used to establish the relationship between the TTC and its contributing factors. We then proceed to introduce a new concept of exposure to traffic conflicts as the mean sojourn time in a given time period that vehicles are exposed to dangerous scenarios, namely, the TTC is lower than a predetermined threshold value. We further establish the relationship between the proposed exposure to traffic conflicts and crash count by using negative binomial regression models. Based on the limited data samples used in this study, the negative binomial regression models perform well although a further study using more data is needed.

Vessel collision frequency estimation in the Singapore Strait

This paper aims to estimate Vessel Collision Frequency in the Singapore Strait. This frequency is obtained as the product of the number of Vessel Conflicts and the causation probability using the real-time vessel movement data from the Lloyd’s Marine Intelligence Unit (Lloyd’s MIU) database. The results show that the container carriers have the highest Vessel Collision Frequency while Roll-On Roll-Off (RORO) and passenger ships have the lowest frequency. Tankers cause the highest head-on collision frequency. In the Singapore Strait, the most risky overtaking area is between longitudes 103°48′E and 104°12′E. The most risky head-on area is between longitudes 103°50′E and 104°00′E while the majority of crossing collisions occur between longitudes 103°50′E and 104°12′E. The Vessel Collision Frequency is found to be 1·75 per year in the traffic lanes. Currently, westbound traffic in the Strait is more risky than eastbound traffic (the number of westbound collisions in July was 0·0991 while the number of eastbound collisions was 0·0470). Furthermore, the estimated Vessel Collision Frequency during the day is less than that at night. The results of this paper could be beneficial for the Maritime and Port Authority of Singapore to further enhance the navigational safety strategies implemented in the Singapore Strait. 1. INTRODUCTION. The Singapore Strait is a 105 kilometre long strait between the Strait of Malacca in the west and the South China Sea in the east. It links one of the largest ports to the rest of the world and has a high density of vessel traffic. More than 200 vessels pass through the Strait on a daily basis and this gives an annual throughput of approximately 70,000 vessels, carrying 80% of the oil transported to Northeast Asia, as well as one third of the world’s traded goods including Chinese manufactures, Indonesian coffee etc. Although the Singapore Strait is of great importance to the global economy (Wang and Meng, 2011; Qu and Meng, 2012), it is not deep enough for some of the largest vessels (mostly oil tankers). The Strait also has substantial sections of narrower and shallower shipping lanes. At Philips Channel, it narrows to 2·8 kilometres wide, with 2·1 kilometres in the shipping lanes, creating one of the world’s chokepoints. Therefore, the navigational safety of vessels through the

A probabilistic quantitative risk assessment model for the long-term work zone crashes.

Work zones especially long-term work zones increase traffic conflicts and cause safety problems. Proper casualty risk assessment for a work zone is of importance for both traffic safety engineers and travelers. This paper develops a novel probabilistic quantitative risk assessment (QRA) model to evaluate the casualty risk combining frequency and consequence of all accident scenarios triggered by long-term work zone crashes. The casualty risk is measured by the individual risk and societal risk. The individual risk can be interpreted as the frequency of a driver/passenger being killed or injured, and the societal risk describes the relation between frequency and the number of casualties. The proposed probabilistic QRA model consists of the estimation of work zone crash frequency, an event tree and consequence estimation models. There are seven intermediate events--age (A), crash unit (CU), vehicle type (VT), alcohol (AL), light condition (LC), crash type (CT) and severity (S)--in the event tree. Since the estimated value of probability for some intermediate event may have large uncertainty, the uncertainty can thus be characterized by a random variable. The consequence estimation model takes into account the combination effects of speed and emergency medical service response time (ERT) on the consequence of work zone crash. Finally, a numerical example based on the Southeast Michigan work zone crash data is carried out. The numerical results show that there will be a 62% decrease of individual fatality risk and 44% reduction of individual injury risk if the mean travel speed is slowed down by 20%. In addition, there will be a 5% reduction of individual fatality risk and 0.05% reduction of individual injury risk if ERT is reduced by 20%. In other words, slowing down speed is more effective than reducing ERT in the casualty risk mitigation.

A tree-structured crash surrogate measure for freeways.

In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicles action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The results show that the proposed indicator outperforms the three traditional crash surrogate measures (i.e., Time to Collision, Proportion of Stopping Distance, and Crash Potential Index) in representing rear-end crash risks. The applications of this measure are also discussed.

Safety evaluation for expressways: A comparative study for macroscopic and microscopic indicators

Objective: This article is to assess the performance of 3 macroscopic safety indicators (speed, speed dispersion, and volume) and two microscopic potential crash risks (time to collision and deceleration rate to avoid crash) on safety evaluation for expressways. Methods: Field data were collected at 3 locations for 4 different time periods on an expressway in Beijing, China. The speed of each vehicle, headway time, and vehicle length were recorded by a traffic management system. The 5 safety indicators were thus calibrated on the basis of the collected data. Further, consistency and comparative analyses were applied to assess the performance of indicators. Results: According to the analyses, speed dispersion was a better predictor of the two microscopic potential risks compared to the two macroscopic indicators. Conclusions: Speed dispersion is recommended to proactively assess road safety because (1) it provides consistent risk evaluation with microscopic potential risks and (2) it makes data collection easier.

Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels

Urban road tunnels provide an increasingly cost-effective engineering solution, especially in compact cities like Singapore. For some urban road tunnels, tunnel characteristics such as tunnel configurations, geometries, provisions of tunnel electrical and mechanical systems, traffic volumes, etc. may vary from one section to another. These urban road tunnels that have characterized nonuniform parameters are referred to as nonhomogeneous urban road tunnels. In this study, a novel quantitative risk assessment (QRA) model is proposed for nonhomogeneous urban road tunnels because the existing QRA models for road tunnels are inapplicable to assess the risks in these road tunnels. This model uses a tunnel segmentation principle whereby a nonhomogeneous urban road tunnel is divided into various homogenous sections. Individual risk for road tunnel sections as well as the integrated risk indices for the entire road tunnel is defined. The article then proceeds to develop a new QRA model for each of the homogeneous sections. Compared to the existing QRA models for road tunnels, this section-based model incorporates one additional top event-toxic gases due to traffic congestion-and employs the Poisson regression method to estimate the vehicle accident frequencies of tunnel sections. This article further illustrates an aggregated QRA model for nonhomogeneous urban tunnels by integrating the section-based QRA models. Finally, a case study in Singapore is carried out.

Development and applications of a simulation model for vessels in the Singapore Straits

The traffic volume in the Singapore Strait will be significantly increased according to the prediction by the United Nations Conference on Trade and Development. Therefore, it is important for the maritime authorities (e.g. Maritime and Port Authority of Singapore) to capture a picture of ship movements in the Straits in the near future. This paper proposed a novel simulation model for ship movements in the narrow and busy shipping channel. The simulation approach is on the basis of a modified Cellular Automata model and takes interactions between consecutive ships into consideration by expert judgment from experienced personnel. Discrete event models are applied to generate vessels with different categories and velocities from four portals of the Strait. Ten ship following rules and five ship crossing rules are used to simulate the mariners response to various navigational scenarios. The model is further verified by comparing the actual travel time through the Strait and the time derived from the model. At last, applications of the model are illustrated.

Uncertainty Propagation in Quantitative Risk Assessment Modeling for Fire in Road Tunnels

Road tunnels are critical transportation infrastructures that provide underground passageways for motorists and commuters. Fire in road tunnels in combination with tunnel safety provisions failure may lead to catastrophic consequences, and thus, necessitates a robust and reliable approach to assess tunnel risks. This article proposes a quantitative risk assessment model for fire in road tunnel by taking into consideration two types of uncertainties. A Monte Carlo-based estimation method is developed to propagate parameter uncertainty in quantitative risk assessment model consisting of event tree analysis as well as consequence estimation models. The percentile-based individual risks and α-cut-based societal risks are put up and the risk indices are proven to be very useful for tunnel operators with distinct risk attitudes to assess the safety level of a road tunnel. Finally, the proposed research methodology is applied to Singapore KPE road tunnels.