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• A QRA model is proposed to evaluate the hazmat transportation accident risk. • Possible accident scenarios are identified by an event tree comprising six intermediate events. • A mathematical model is presented to evaluate the number of fatalities for each accident scenario. • One case study is created to testify the capability of the proposed QRA model. This study develops a quantitative risk assessment (QRA) model to evaluate the hazmat transportation accident risk that combines the frequency and consequence of all possible accident scenarios. The possible accident scenarios are identified by an event tree comprising six intermediate events including accident time, wind speed, number of vehicles involved in the accident, leak hole size, incapacitating injury/death of the hazmat truck driver and time of exposure to toxic gas. A mathematical model is presented to evaluate the quantitative consequence in terms of the number of fatalities for each accident scenario. With the hazmat transportation relevant data in Shanghai, one case study is finally created to testify the capability of the proposed QRA model in evaluating the hazmat transportation accident risk. [ABSTRACT FROM AUTHOR]

The underreporting issue on shipping accident data has plagued the researchers focused on maritime safety analysis for many years. For improving the quality of shipping accident records, this study proposes a novel methodology comprising three steps to complement the underreported maritime accident records. The first step is to investigate the underreporting rates under various conditions through questionnaire survey. Based on the survey results, the second step is to build a Cluster-Specific Random Effects (CSRE) model to estimate the underreporting rates under various scenarios. Then, the third step is to replicate the underreported accident records using the Monte Carlo simulation technique. Model results show that the occurrence probability of missing accident records involving liquid cargo ships is lower than other ship categories while fishing ships are more likely to have a higher underreporting rate. Non-serious accidents are more likely to be underreported than serious accidents. The case study confirms the effectiveness of the proposed three-step method for complementing the maritime accident databases suffering underreporting problems. [ABSTRACT FROM AUTHOR]

• We conducted a quantitative analysis of intelligent SCA technology over the past 20 years using bibliometric methods and data portrait techniques and traced earlier literature for a systematic review. • We identified the hotspots and research frontiers of intelligent ship collision avoidance in maritime transportation. • We discussed the contributions, innovations, and trends of future research in intelligent ship collision avoidance. With the increasing promotion of digital technology, safety issues faced by rush ships in the maritime industry have once again received attention. Ship collision avoidance (SCA) is not only a hot topic in the shipping industry but also an eye-catching issue in the development of intelligent ships. This paper provides a bibliometric and systematic overview of the literature on SCA to assist researchers in understanding the frontiers and recent trends of SCA. Based on the bibliographic portrait, a classification and grading study was conducted on the literature to provide a systematic review of it. A screening process was conducted on 851 relevant articles related to SCA and published in 2004–2023 in the Web of Science (WoS) database, and 526 highly relevant and high-quality papers were selected. Then, CiteSpace, VOSviewer software, and data visualization techniques were used to conduct a bibliographic portrait analysis on the selected papers. The evidence from these systematic literature reviews revealed the close collaboration relationships among researchers, research institutions, and countries or regions in the field of SCA studying shortly. Furthermore, the frontiers of the research on SCA were focused on three aspects, i.e. research subjects, technological methods, and novel algorithms in intelligent SCA. COLREG is a problem that must be considered in intelligent SCA. The future trends in intelligent SCA were explored and SCA technology was introduced from artificial intelligence (AI) so as to meet the safety requirement of maritime autonomous surface ships. AI algorithms such as machine learning and deep learning are key technologies for SCA. This research provides a theoretical basis and implementation directions of the research on SCA. The hybrid encounters between traditional ships and intelligent ships, as well as multi-ship encounters in narrow waterways, will be the focal points of attention in the future. [ABSTRACT FROM AUTHOR]

A comprehensive analysis of ship emissions is a key step towards taking effective strategies to mitigate air pollution. Based on the AIS data, the objective of this study is to estimate ship emissions with high-resolution (0.001° × 0.001°) in the Yangtze River estuary using the STEAM model. Effects of ship types, operating modes, discharge equipment, time and location on ship emissions are also examined in this study. Results reveal that the annual ship emissions for CO 2 , CO, HC, NO x and SO 2 in 2014 are 1.818 × 106 tons, 2.593 × 103 tons, 1.949 × 103 tons, 3.394 × 104 tons and 1.584 × 104 tons, respectively. Findings highlight that the majority of ship emissions are generated under the slow-steaming and normal cruising states. There exist strong temporal and spatial effects on ship emissions. Ship emissions are mainly distributed at the port areas, intersection areas and the north channel of the Yangtze River estuary. This study concludes with some future efforts and directions to mitigate ship emissions in this water area effectively (e.g., encouraging cargo ships to use the lower carbon fuels for propulsion, optimizing ship routes in the north channel and interactions of the Yangtze River estuary). [ABSTRACT FROM AUTHOR]

Unsafe acts of ship officers have been a direct cause of many maritime accidents. In the maritime industry, much effort has been made to prevent unsafe acts and to improve safe behaviours of ship officers. The positive effect of organizational safety climate on human behaviour has been well documented in the literature. Within this context, this paper aims to pioneer the development of the measurement constructs of safety climate in shipping operations and analyze its impact on safety consciousness and behaviour of ship officers. Using primary data collected from 284 deck officers and captains, an exploratory and confirmatory factor analysis and a structural equation model are used to reveal the relationship among the constructs of safety climate, safety consciousness and safety behaviour. The research results show that (1) safety climate generates a direct positive effect on safety consciousness and behaviour; (2) safety consciousness has a positive effect on safety behaviour; and (3) safety consciousness acts as a mediator between safety climate and safety behaviour. Its managerial implications and practical contributions lie in the provision of useful insights on how ship managers can effectively gain the improved safety behaviours of ship officers by appropriate introduction of safety climate and consciousness. [ABSTRACT FROM AUTHOR]

The trend towards global warming and the rapid decline in the extent of summer Arctic sea ice over recent years has increased the feasibility of international Arctic shipping. In this study we propose a seasonal NSR (North Sea Route)/SCR (Suez Canal Route)-combined shipping service linking Shanghai and Rotterdam, using the Northern Sea Route during the economical navigable window but using the traditional Suez Canal Route at other times. Different from the previous literatures, this paper dynamically considers the sea ice extent in the model, which is more reasonable for the assessment of Arctic container shipping, because fuel consumption is highly related to ship speed, while ship speed is determined by the relative distances of ice-covered and ice-free route stages. A new approach is developed to predict the time points at which the ship enters and exits the ice-covered stage, given that both the ship position and the extent of sea ice are constantly changing. The results show that the NSR/SCR-combined Arctic container service can be more economical than the SCR, given lower NSR tariffs. [ABSTRACT FROM AUTHOR]

There is usually a high red-light running (RLR) collision rate at signalized intersections because of the unpredictability of dangerous RLR vehicles traversing intersections illegally. The RLR collision warning systems can help drivers be aware of the red-light running (RLR) vehicles and take collision avoidance actions timely. The objective of this paper is to evaluate the effects of auditory warning information on brake response time (RT) to red-light running vehicles during the collision avoidance process based on a driving simulator experiment. Warning status (e.g., warning vs. no warning), warning lead time (3 s vs. 5 s) and warning content (directional information vs. undirectional information) were considered to examine the effectiveness of the RLR collision warning system under different conditions. The experiment results showed that the auditory warning information can effectively reduce brake RT and collision occurrence rate and RT is the most influential variable on the collision occurrence. Although early warning is more effective than late warning in reducing brake RT and collision rate, the late warning can still lower the collision rate by 37%. However, the directional warning information did not have apparent advantages over the undirectional warning information. The findings of this study are helpful for the designers of RLR collision warning systems to enhance the effectiveness of the systems’ application on traffic safety. [ABSTRACT FROM AUTHOR]

With the merit on representing traffic conflict through examining the crash mechanism and causality proactively, crash surrogate measures have long been proposed and applied to evaluate the traffic safety. However, the driver’s Perception-Reaction Time (PRT), an important variable in crash mechanism, has not been considered widely into surrogate measures. In this regard, it is important to know how the PRT affects the performances of surrogate indicators. To this end, three widely used surrogate measures are firstly modified by involving the PRT into their crash mechanisms. Then, in order to examine the difference caused by the PRT, a comparative study is carried out on a freeway section of the Pacific Motorway, Australia. This result suggests that the surrogate indicators’ performances in representing rear-end crash risks are improved with the incorporating of the PRT for the investigated section. [ABSTRACT FROM AUTHOR]

Water transportation plays an important role in the comprehensive transportation system and regional logistics. The number of vessel accidents is an important indicator for evaluating vessel traffic safety and the efficiency of the maritime management strategy. The aim of this work is to provide an efficient way to predict the number of vessel accidents in China. Firstly, to weaken the randomness of the vessel accident number time series, the gray processing operation is adopted to generate a new sequence with exponential and approximate exponential rules. In addition, an extended least-squares support vector machine (LSSVM) model is applied in the forecasting of the new sequence, in which the parameters of the LSSVM are optimized by an improved quantum-behaved particle swarm (IQPSO). The proposed method is applied in the forecasting of the number of vessel accidents in China, and the efficiency is shown by comparing the prediction results with GM (1, 1), PSO-LSSVM, and QPSO-LSSVM. [ABSTRACT FROM AUTHOR]

Water transportation plays an important role in the comprehensive transportation system and regional logistics. The number of vessel accidents is an important indicator for evaluating vessel traffic safety and the efficiency of the maritime management strategy. The aim of this work is to provide an efficient way to predict the number of vessel accidents in China. Firstly, to weaken the randomness of the vessel accident number time series, the gray processing operation is adopted to generate a new sequence with exponential and approximate exponential rules. In addition, an extended least-squares support vector machine (LSSVM) model is applied in the forecasting of the new sequence, in which the parameters of the LSSVM are optimized by an improved quantum-behaved particle swarm (IQPSO). The proposed method is applied in the forecasting of the number of vessel accidents in China, and the efficiency is shown by comparing the prediction results with GM (1, 1), PSO-LSSVM, and QPSO-LSSVM. [ABSTRACT FROM AUTHOR]

This paper presents a novel framework for system-theoretic risk management of maritime transportation systems (MTS) based on the principles of formal safety assessment. The proposed framework comprises four essential steps: (1) risk identification: identifying accident scenarios and associated risk-influencing factors in the MTS through text mining of maritime accident investigation reports; (2) risk analysis: determining the probabilities and consequences of accident scenarios in the MTS using Bayesian network modeling; (3) risk evaluation: assessing the risks of various accident scenarios and the comprehensive risk of the MTS, and comparing the results with risk acceptance criteria to make informed decisions; and (4) risk treatment: proposing effective risk control options (RCOs) for accident scenarios and the comprehensive risk of the MTS by incorporating expert judgment, fuzzy sets, and Bayesian network modeling. To demonstrate the applicability of the proposed framework, the risk management of the Yangtze River Estuary is presented as a case study. By adopting a comprehensive approach to risk management, stakeholders gain a more holistic view of risk and achieve more effective decision-making processes for RCOs. The framework may help improve the safety and security of maritime operations, enhance the efficiency and competitiveness of the industry. • A novel framework for system-theoretic risk management of MTS based on the principles of FSA. • The framework can be used for proposing effective RCOs for reducing the comprehensive risk of the MTS. • The risk management of the Yangtze River Estuary is presented as a case study for reducing the navigational risks. [ABSTRACT FROM AUTHOR]

This paper presents a novel framework for system-theoretic risk management of maritime transportation systems (MTS) based on the principles of formal safety assessment. The proposed framework comprises four essential steps: (1) risk identification: identifying accident scenarios and associated risk-influencing factors in the MTS through text mining of maritime accident investigation reports; (2) risk analysis: determining the probabilities and consequences of accident scenarios in the MTS using Bayesian network modeling; (3) risk evaluation: assessing the risks of various accident scenarios and the comprehensive risk of the MTS, and comparing the results with risk acceptance criteria to make informed decisions; and (4) risk treatment: proposing effective risk control options (RCOs) for accident scenarios and the comprehensive risk of the MTS by incorporating expert judgment, fuzzy sets, and Bayesian network modeling. To demonstrate the applicability of the proposed framework, the risk management of the Yangtze River Estuary is presented as a case study. By adopting a comprehensive approach to risk management, stakeholders gain a more holistic view of risk and achieve more effective decision-making processes for RCOs. The framework may help improve the safety and security of maritime operations, enhance the efficiency and competitiveness of the industry. • A novel framework for system-theoretic risk management of MTS based on the principles of FSA. • The framework can be used for proposing effective RCOs for reducing the comprehensive risk of the MTS. • The risk management of the Yangtze River Estuary is presented as a case study for reducing the navigational risks. [ABSTRACT FROM AUTHOR]

Highlights • We optimize shipping schedule for steel plants cluster alongside inland river. • The model considers timely demands of steel plants over multiple periods. • A MIP formulation and dynamic programming algorithm are developed. • We explore the iron ore trade volume under various scenarios. Abstract This paper aims to provide an optimal shipping schedule for steel-manufacturing plants cluster alongside the Yangtze River by developing a mixed integer programming formulation. The model takes into account the multi-layer shipping network on the Yangtze River, the dynamic iron ore price and transportation costs, and the timely demands of steel plants over multiple periods. By applying the proposed model to a real-world case, several interesting findings are observed, leading to further useful managerial insights. We also propose an exact solution approach based on a dynamic programming algorithm to a special case of this problem motivated by real-world practice. [ABSTRACT FROM AUTHOR]

Proper intersection sight distance can effectively lower the possibility of intersection accidents. American Association of State Highway and Transportation Officials (2011) provide a series of recommended dimensions of intersection sight triangles for uncontrolled and stop/yield-controlled intersections. However, in reality, although the actual intersection design for unsignalized intersections satisfies the requirements of sight distance and clear sight triangle in American Association of State Highway and Transportation Officials' guideline, there are still a large number of crashes occurring at unsignalized intersections for drivers running stop/yield signs or failing to slow down. This paper presents a driving simulator study on pre-crash at intersections under three intersection field of view (IFOV) conditions. The aim was to explore whether better IFOVs at unsignalized intersections improve their emergent collision avoidance performance under an assumption of valid intersection sight distance design. The experimental results show drivers' ability to identify potential hazards to be significantly affected by their IFOVs. As drivers' IFOV improved, drivers were more likely to choose braking actions to avoid collisions. Better IFOVs were also associated with significant increases in brake time to intersection and significant reductions in deceleration rate and crash rate, thus leading to a lower risk of traffic crash involvement. The results indicate that providing a better IFOV for drivers at intersections should be encouraged in practical applications in order to improve drivers' crash avoidance capabilities. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Debates on the ordering patterns of crash injury severity are ongoing in the literature. Models without proper econometrical structures for accommodating the complex ordering patterns of injury severity could result in biased estimations and misinterpretations of factors. This study proposes a hybrid finite mixture (HFM) model aiming to capture heterogeneous ordering patterns of driver injury severity while enhancing modeling flexibility. It attempts to probabilistically partition samples into two groups in which one group represents an unordered/nominal data-generating process while the other represents an ordered data-generating process. Conceptually, the newly developed model offers flexible coefficient settings for mining additional information from crash data, and more importantly it allows the coexistence of multiple ordering patterns for the dependent variable. A thorough modeling performance comparison is conducted between the HFM model, and the multinomial logit (MNL), ordered logit (OL), finite mixture multinomial logit (FMMNL) and finite mixture ordered logit (FMOL) models. According to the empirical results, the HFM model presents a strong ability to extract information from the data, and more importantly to uncover heterogeneous ordering relationships between factors and driver injury severity. In addition, the estimated weight parameter associated with the MNL component in the HFM model is greater than the one associated with the OL component, which indicates a larger likelihood of the unordered pattern than the ordered pattern for driver injury severity. [ABSTRACT FROM AUTHOR]

Holidays are special periods and give rise to many kinds of non-mandatory trips, such as shopping trips and tourist trips. This study investigates the relationship between Integrated Multimodal Travel Information (IMTI) service and holiday travel behavior characteristics in a trip chain. The Exploratory Factor Analysis (EFA) method is first used to extract the common factors based on the RP–SP fusion data under the pre-trip IMTI and en-route IMTI services, respectively. The Structural Equation Modeling (SEM) method is then applied to examine causal effects and quantitative relationships between the influencing factors and trip chain characteristics based on the EFA results. The results show that pre-trip IMTI has a significant negative effect on the holiday travel behavior. The more pre-trip IMTI is obtained by the traveler, the simpler the trip chain spatiotemporal and structural complexity will be. In addition, although the effect of en-route IMTI is less than pre-trip IMTI, it still plays an important role compared to other factors. Therefore, providing IMTI is a new and good alternative to alleviate holiday traffic congestions. [ABSTRACT FROM AUTHOR]

Objective This paper aims to assess the potential crash risks across different traffic lanes (shoulder lane, median lane, and middle lane) near to ramps (before on-ramps, between ramps, and after off-ramps). Methods Field data are collected at seven locations (90 min for each location) during peak hours. Two risk indices based on time to collision, individual risk and societal risk are proposed to represent the distinct interpretations of risks to transport agencies and individual motorists. One-way ANOVA is applied to analyze the risk impact of ramps in various types of locations across distinct traffic lanes. Results Median lanes and sections after off-ramps have relatively lower risks compared to other lanes and sections. The individual and societal risks might not always be consistent since the two risk indices are proposed based on distinct perspectives: transport agencies focus on the crash/conflict frequencies in a road section and individual motorists concern more about the probability of being involved in a crash/conflict during their journey. Conclusions The differences in risks mainly result from the frequent lane-changing and merging activities. This model could be used to evaluate the performance of expressway ramp design. [ABSTRACT FROM AUTHOR]

The travel time reliability of buses has become increasingly important for public transit companies. In this study, a novel approach is proposed to evaluate and analyse the travel time reliability of bus services provided by TransLink in Queensland, Australia. In view of their stochastic features, the two components of travel time - dwell time and driving time - are represented by discrete distributed and normally distributed random variables respectively. Accordingly, the travel time could be described by Gaussian mixture models. Based on the proposed model, impact analysis shows that bus line reliability would increase by around 15% if onboard top-up for 'go cards' (electronic tickets) was not offered by TransLink. It was found that not providing this top-up method would not significantly harm the benefit of go card users, but it would substantially increase the total social benefit thanks to improved bus line reliability. [ABSTRACT FROM AUTHOR]