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Considering the unobserved spatial heterogeneity, this study aims to build a Bayesian spatial multinomial logistic (BSMNL) model by utilizing the geographic information from historical maritime accidents. The proposed BSMNL model can be applied to investigate the determinants of human errors involved in maritime accidents. Compared to the traditional multinomial logistic (MNL) model, the proposed BSMNL model produces a more accurate estimate of the effects of environmental and accident factors on the occurrence likelihood of human errors in maritime accidents. Results show that accidents involving cargo and container ships; tankers carrying liquefied natural gas (LNG), liquefied petroleum gas (LPG), or oil; and fishing vessels are more likely to be associated with human errors. Further, one important finding is that the involvement of fishing vessels significantly increases the occurrence probability of both negligence errors and judgment or operational errors. In addition, the occurrence likelihood of human errors is generally higher in springtime, conditions of poor visibility, the absence of strong winds or waves, and the moored or docked status. [ABSTRACT FROM AUTHOR]

Considering the differences in traffic delays and accident costs at different stages of the shipping cycle, this study develops a system dynamics model to determine the impacts of the shipping cycle on traffic delays and accident costs at port collector-distributor roads. Taking the collector-distributor roads of Yangshan Deepwater Port in Shanghai as a case study, parameter estimation and a model validity test are conducted. The changes in traffic delays and accident costs before and during maintenance activities at different stages of the shipping cycle are analyzed by increasing the growth rates of gross domestic product (GDP), and secondary and tertiary industries in GDP. The model results show that, as the economic growth rate increases, the growth magnitudes of traffic delays and accident costs during a peak period are significantly larger than those during a trough period. The results of this study provide policies and suggestions for improving traffic efficiency and safety on port collector-distributor roads. It is suggested to increase the maintenance frequency and maintenance funds during a peak period. Additionally, it is necessary to develop an intelligent road maintenance system for port collector-distributor roads that takes the shipping cycle into account in order to enhance the road safety level. [ABSTRACT FROM AUTHOR]

The accurate detection of seafarers' unsafe behaviors is of great significance to improve the ship navigation safety. This study proposes an improved deep learning framework with a self-made dataset to detect the unsafe behavior of seafarers on duty. In order to increase the detection speed, the improved Cross Stage Partial connections (CSP) module is proposed to replace the original CSP module in the neck network of traditional algorithm. The efficient channel attention (ECA) module is also introduced to the backbone network of conventional algorithm as the attention mechanism network. In addition, the learning and representation capacities of the improved deep learning framework are promoted by redesigning the sizes of anchor boxes. The experiment results show that the proposed framework outperforms traditional object detection algorithms (e.g., YOLOv5s, R-CNN) in detecting seafarers' unsafe behaviors because of the much higher detection speed and detection accuracy. [ABSTRACT FROM AUTHOR]

Ship anomaly detection is a vital aspect for monitoring navigational safety in specific water areas. Considering the effect of water channel boundaries, we propose the detection of an abnormal ship trajectory based on the complex polygon (DATCP) method to detect ship anomalies in this study. With the automatic identification systems (AIS) data from the Yangtze River estuary, a case study is created to verify the effectiveness of the proposed DATCP method. The case study results reveal that the proposed DATCP method can provide higher detection accuracy than the conventional A* algorithm. The feature analysis results indicate that ship anomalies are significantly influenced by ship type, time period, weather conditions and ship traffic characteristics. [ABSTRACT FROM AUTHOR]

This study investigates the lane-changing behavior in work zone merging areas during the period from the time of starting a lane-changing maneuver to that of completing the lane-changing maneuver. With vehicle trajectory data from short-term work zone sites, we establish a spatial-temporal varying coefficient model considering possible spatial-varying and time-varying effects. Model results show that four factors including the longitudinal gap between the lane-changing vehicle and lead vehicle, lane-changing vehicle speed, through lane lag vehicle type and crash severity between the lane-changing vehicle and the through lane lag vehicle exhibit spatial-varying effects on the drivers' lane-changing behavior, while time-varying effects are found from the lead vehicle speed in the merge lane, crash severities of the lane-changing vehicle with regard to the lead vehicle and the through lane lead vehicle. Time-varying and spatial-varying effects from vehicle crash severities between the lane-changing vehicle and through lane vehicles suggest that lane-changing vehicles tend to take a risky merge as the elapsed time increases or when they are closer to the work zone. [ABSTRACT FROM AUTHOR]

By integrating AIS data with visual data, this study aims to propose a data fusion-based methodology for the robust assessment of vessel collision risk in inland waterways. With the data from the Huangpu River, one case study is created and comparison results show that visual data could greatly overestimate the vessel collision risk while the vessel conflict count could be underestimated from AIS data. The proposed methodology could contribute to a 35.70% reduction in the false detection rate compared to the pure visual data but an increase of 16.84% in the conflict detection accuracy compared to the AIS data. Moreover, results show that the proposed methodology is able to perform much better than the pure AIS data technique during the daytime period while it outperforms the pure visual data technique during the nighttime period. This suggests that the proposed data-fusion methodology could provide a more reliable and accurate estimate for the vessel collision risk in inland waterways. Results also show that higher collision risk is associated with the high tide period and turning area in the Huangpu River. Therefore, special attention should be placed to enhance the navigation safety during this time period for the inland waterway turning area. • Propose a data fusion-based methodology for the robust assessment of vessel collision risk in inland waterways. • The pure visual data technique could greatly overestimate the vessel collision risk. • The number of vessel conflicts could be underestimated using the pure AIS data technique. • The proposed methodology could provide a more reliable and accurate estimate. • The higher collision risk is associated with the high tide period and turning area. [ABSTRACT FROM AUTHOR]

Considering the varying effects of influencing factors, this study aims to model the relationship between crash frequency and influencing factors for the highways involving traffic hazards and involving no traffic hazards separately. Two spatial-temporal interaction effect models are built with highway crash data occurring on the highway network comprising 11 highways managed by the China Communication Construction Co (CCCC) Asset Management Company. The model results show that there exist no significant spatial-temporal interaction effects for the highway crashes. The highway crash frequency for the highways involving traffic hazards is significantly larger than that for the highways involving no traffic hazards. The influencing factors such as the highway segment length, monthly traffic volume, and pavement width are found to exhibit much bigger effects for the highways involving traffic hazards than for the highways involving no traffic hazards. Results of this study provide supports for the argument that slightly different policies should be developed for the highways involving traffic hazards. For the highways involving traffic hazards, additional measures should be proposed to detect and repair destroyed road barriers as quickly as possible because this type of traffic hazard has a higher probability of causing highway crashes. [ABSTRACT FROM AUTHOR]

This study aims to examine the effects of moving work-zone speed, working lane position, and traffic condition on the travel delay, crash risk, and mortality risk at moving work zones by using microscopic traffic simulation approaches. Two surrogate safety measures including TTC (Time to Collision) and Delta-V are employed to represent the vehicle crash risk and mortality risk, respectively. The simulation experiment is conducted based on the observation data from the road network located in the Haidian District of Beijing. Simulation results show that the moving work-zone speed exhibits higher effects on the travel delay, vehicle crash risk, and mortality risk under the smooth traffic state, as compared with those under the congested traffic state. Greater travel delay and higher crash risk are closely associated with the lanes where there are a larger proportion of vehicles whereas the highest mortality risk is for vehicles traveling in the fast lane. The simulation results also show that the vehicles near the moving work zone are associated with high vehicle crash risk, whereas an increased crash risk is also found for the vehicles far from the moving work zone. [ABSTRACT FROM AUTHOR]

Considering unobserved spatial-temporal interaction effects, this study proposes a Bayesian spatial-temporal interaction model for predicting economic loss from fishing boat collisions using 10-year (2004–2014) collision records from six different areas in the waters of Fujian, China. Results show strong spatial heterogeneity and correlation effects in fishing boat collisions, while the economic loss from boat collisions gradually decreases with the time trend. Collision time, collision location, visibility and the involvement of LNG/LPG/chemical-carrying ships show similar marginal effects on the economic loss for the two collision types: fishing boat collisions and collisions involving no fishing boats. Navigational status and the involvement of cargo ships exhibit much bigger effects in fishing boat collisions compared with collisions involving no fishing boat. Unlike collisions involving no fishing boat, fishing boat collisions are associated with reduced economic loss in poor weather conditions characterised by strong wind/waves because in Fujian waters additional safety measures are adopted for fishing boats in such conditions. The proposed model is useful for policymakers in adopting safety enhancement strategies to decrease the economic loss resulting from fishing boat collisions. [ABSTRACT FROM AUTHOR]

With the Automatic Identification System (AIS) data collected from Donghai Navigation Safety Administration, this study aims to estimate vessel collision frequency in the Yangtze River estuary water areas considering dynamic ship domain sizes. To take into account the possible impacts of ship type, time of the day, and ship relative speed, ship domain size is further modeled as linear functions of these influencing factors based on our questionnaire survey data. Ship results reveal that the calculated vessel collision frequency in the Yangtze River estuary water areas is about 4.29 × 10−3 per ship-year, in which cargo ships have the highest vessel collision frequency, while fishing ships have the lowest frequency. Moreover, head-on collision is the collision type that has the largest collision frequency, followed by overtaking collision and crossing collision in the Yangtze River estuary. Big-sized vessels (e.g., Container ship and Cargo ship) are more likely to encounter head-on collisions, while the majority of small vessels (e.g., Fishing ship and Passenger ship) involved in overtaking collisions. Because of higher vessel traffic flow and density, the daytime period is associated with a larger vessel collision frequency, as compared with the nighttime period. [ABSTRACT FROM AUTHOR]

This study aims to model the complex relationship among the traffic characteristics (i.e. traffic flow, traffic speed, traffic density), environmental conditions (i.e. darkness condition, weather condition and traffic lane width) and frequency of ship collisions in the Yangtze River estuary areas. Taking into account the effects of ship approach angle, ship type, relative speed and darkness condition on the capability of ship collision avoidance, a dynamic ship domain model has been presented to measure ship collision frequency. Considering the big variation associated with the collision frequency, the measured ship collision frequency is further modeled as a loglogistic-distributed function of traffic characteristics and environmental conditions. Results show that the collision frequency is greater for (i) the bigger traffic flow; (ii) the bigger traffic density; (iii) the narrower traffic lane width; and (iv) the adverse weather condition. The darkness condition is the influencing factor that produces the biggest effect on the ship collision frequency. [ABSTRACT FROM AUTHOR]

The objective of this study is to propose a methodology for assessing waterway traffic capacity in the Shanghai estuary of the Yangtze River. To achieve this objective, we first put forward the estimation method which utilises the minimum collision distance taking the dynamic ship domain into consideration. Considering possible effects caused by unknown external factors, the waterway traffic capacity is then represented by a probability distribution. Finally, we quantify the equivalent units of ships with various ship sizes as well as the effects of large-sized ships on the waterway traffic capacity. Results show that a large-sized ship is equivalent to more small-sized ships during the daytime period than at night. In addition, the deployment of large-sized ships could increase the waterway traffic capacity and such an increment highly depends on the increased proportion of large-sized ships in the waterway traffic. [ABSTRACT FROM AUTHOR]

This study aims to estimate ship collision risk considering the occurrence frequency and severity simultaneously, as well as to explore the influence of ship domain shapes on estimation results in the Yangtze River estuary waterway. In contrast to the circular ship domain, the elliptical domain may result in an overestimate for head-on collisions and overtaking collisions, while it may underestimate the small-angle and large-angle crossing collision frequency. Conversely, the sector domain may underestimate the occurrence frequency of all collision types. Results also reveal that overtaking encounters are the most common type with a relatively low severity degree, while large-angle crossing collisions are associated with a lower frequency but a higher potential for causing serious consequences. The collision occurrence likelihood and severity are a little higher for the passenger ship type. Furthermore, two high-risk areas are found to be located between longitudes of 121°33′E and 121°46′E, 121°50′E and 121°58′E, respectively. The results of this study are beneficial for a better understanding of the overall collision risk in the Yangtze River estuary waterway. • Effects of ship domain shapes on ship collision risk estimate are examined. • Collision risk is simultaneously expressed by occurrence frequency and consequence. • Overtaking encounters are the most common type with a relatively low severity. • Two high-risk areas with higher collision frequency and severity are identified. [ABSTRACT FROM AUTHOR]

Human errors are one of the most significant contributory factors in ship accidents. This study aims to explore the quantitative relationship between the occurrence likelihood of human errors and external factors including the environmental characteristics, accident characteristics and ship characteristics. A multinomial logistic regression model has been developed to reflect the relationship between these factors and the occurrence likelihood of human errors using 14 years' ship accident records from Fujian water areas. Model results show that the season of spring, poor visibility and night are more likely to be associated with high occurrence likelihood of negligence and judgment/operation errors. One important finding is that mooring and no strong-wind condition are two circumstances that would highly increase occurrence likelihood of all kinds of human errors. Fishing boats and engineering ships/sand dredgers are the primary ship types which have relatively higher occurrence likelihood of negligence errors than other ship types. • This study explores the quantitative relationship between the occurrence likelihood of human errors and external factors. • A multinomial logistic regression model is developed to reflect the relationship using 14 years' ship accident records. • Negligence and judgment/operation errors are more likely to be associated with season of spring, poor visibility and night. • Mooring and no strong-wind condition will highly increase occurrence likelihood of all kinds of human errors. [ABSTRACT FROM AUTHOR]

The uncertainty-based work zone capacity model is formulated as a mixed linear regression function of explanatory variables where capacity is a random variable following a lognormal distribution. Model parameters are calibrated using a Bayesian approach. Results show that the proposed work zone capacity distribution model can accurately predict the mean and prediction interval of work zone capacity at any given confidence level. It is found that work zones located in urban roads, with a larger number of open lanes or with long-term work duration have a larger mean work zone capacity. A short prediction interval (i.e. low uncertainty) for work zone capacity is found to be associated with the following situations: (a) a bigger number of open lanes; (b) rural work zone; (c) short-term work duration; (d) left lane closure; (e) daytime work and (f) a smaller percentage of heavy vehicles. The predicted interval length for the medium level of work intensity is increased, although the corresponding mean work zone capacity is reduced, as compared with the light level of work intensity. There will be a bigger measured work zone capacity on average if the measurement method is adopted in which work zone capacity is taken as the mean queue-discharge rate. [ABSTRACT FROM AUTHOR]

The investigation of contributory factors in ship traffic accidents is a high-priority issue in maritime safety analysis. In this study, a method based on association rules is proposed to analyze these contributory factors. Using ten years of ship traffic accidents that occurred in Fujian water areas, a total of 66 and 228 association rules is generated for nonserious and serious accidents, respectively. Univariate analysis results show that both severity levels of accidents are probably associated with small ships, good visibility, no strong wind/wave, and the season of spring. The frequency of nonserious accidents is about 33% higher than that of serious accidents in coastal/harbor/port areas. However, the association analysis results show that serious accidents are associated with more influencing factors than are nonserious accidents. Lookout failure is an additional decisive factor in serious accidents but not in nonserious accidents. The association analysis results also reveal that many influencing factors (e.g., navigational status) exhibit effects only under some specific circumstances. [ABSTRACT FROM AUTHOR]

This study develops a generalized F distribution model with random parameters to estimate the ship property damage cost in maritime traffic accidents with 10 years’ shipping accident data in the Fujian waters. Model results show that sinking and capsizing can incur the largest property damage cost, followed by collisions, contact, grounding and fire/explosion. There is a smaller ship property damage cost when the ship is moored or docked. The poor visibility has the least impact on the increment of ship property damage cost. Results reveal that the bigger property damage cost is associated with maritime accidents occurring in the Straits/sea areas and under the strong wind/wave condition and nighttime periods. It is also found that the lookout failure exhibits a bigger effect than the operation error. These results are helpful for policy makers to make efficient strategies for reducing property damage cost in maritime accidents. The developed model is useful for insurance companies in determining the appropriate ship insurance rates. [ABSTRACT FROM AUTHOR]

Abstract This study aims to develop a maximum likelihood regression tree-based (MLRT) ZINB (zero-inflated negative binomial) model to predict shipping accident mortality, and also to examine the factors which affect the loss of human life in shipping accidents. Based upon 23,029 sets of shipping accidents observations collected from 2001 and 2011 in global water areas, a tree comprising 7 terminal nodes is built, each of which is assigned by a separate ZINB model. Model results indicate that the large number of shipping accident casualties are closely related to collision, fire/explosion, sinking, contact, grounding, operating time, capsizing, docking condition, hull/machinery damage, and miscellaneous causes. In addition, it is found that there is a larger casualty count for the accidents occurring under adverse weather conditions or far away from coastal/port areas. In addition, sinking is recognized as the accident type which causes the largest number of casualties. This study can help the decision makers to propose effective strategies to reduce shipping accident casualties. Highlights • Develop a maximum likelihood regression tree-based ZINB model. • The large number of casualties relates to collision operating time, capsizing and docking condition. • Sinking is the accident type causing the largest number of casualties. [ABSTRACT FROM AUTHOR]

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. [ABSTRACT FROM AUTHOR]

This study develops an ordered probit model to evaluate the factors influencing two-ship collision severity using ten years’ ship collision accident data from Fujian sea areas. The model results show that the involvement of big ships has the largest impact in increasing the probability of a serious or very serious accident, followed by the involvement of fishing vessels. There will be a bigger probability of a serious accident if both ships involved in the collision are cargo ships. We found that the season of spring, poor visibility and night time periods are more likely to be factors in high severity levels of ship collision. The results also reveal that lookout failure plays a decisive role in increasing serious accident risk compared with other types of human errors. The results of this study may be beneficial for policy-makers in proposing efficient strategies to reduce the likelihood of serious ship collisions. [ABSTRACT FROM AUTHOR]

This study investigates the drivers’ merging behavior in work zone merging areas during the entire merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. With the actual work zone merging traffic data, we propose a time-dependent logistic regression model considering the possible time-varying effects of influencing factors, and a standard logistic regression model for the purpose of model comparison. Model comparison results show that the time-dependent model performs better than the standard model because the former can provide higher prediction accuracy. The time-dependent model results show that seven factors exhibit time-varying effects on the drivers’ merging behavior, including merging vehicle speed, through lane lead vehicle speed and through lane lag vehicle speed, longitudinal gap between the merging and lead vehicles, longitudinal gap between the merging and through lane lead vehicles, types of through lane lead and through lane lag vehicles. Interestingly, both the through lane lead vehicle speed and the through lane lag vehicle speed are found to exhibit heterogeneous effects at different times of the merging implementation period. One important finding from this study is that the merging vehicle has a decreasing willingness to take the choice of “complete a merging maneuver” as the elapsed time increases if the through lane lead vehicle is a heavy vehicle. [ABSTRACT FROM AUTHOR]

This study develops a quantitative risk assessment (QRA) model to evaluate the risk of ship being involved in ship collisions which takes into account the frequency and consequence of all possible accident scenarios. Two accident consequence types including human life loss and oil pollution which is measured in terms of the volume of oil spilled are considered in this study. The proposed QRA model consists of a collision frequency estimation model, an event tree and consequence estimation models. The event tree comprises five intermediate events including ship type, ship size, loading condition, hull damage and survivability. Two “generic” mathematic models are developed to estimate the human life loss and oil pollution caused by ship collisions, respectively. A case study is finally created using the real-time ship movement data in the Singapore Strait from the Llyod’s Marine Intelligence Unit (Lloyd’s MIU) database. Results show that the container ship, bulk carrier and oil tanker are the three main ship types being involved in collision accidents. Although the passenger/RORO ship has the lowest frequency being involved in collisions, it will suffer the most serious consequence in terms of the human life loss once it is involved in an accident. Considering the relative high percentage of oil tankers involving in ship collisions and their severe consequences, focus should be placed on the tracking and management of oil tanker traffic. [ABSTRACT FROM AUTHOR]

Investigation of the casualty crash characteristics and contributory factors is one of the high-priority issues in traffic safety analysis. In this paper, we propose a method based on association rules to analyze the characteristics and contributory factors of work zone crash casualties. A case study is conducted using the Michigan M-94/I-94/I-94BL/I-94BR work zone crash data from 2004 to 2008. The obtained association rules are divided into two parts including rules with high-lift, and rules with high-support for the further analysis. The results show that almost all the high-lift rules contain either environmental or occupant characteristics. The majority of association rules are centered on specific characteristics, such as drinking driving, the highway with more than 4 lanes, speed-limit over 40 mph and not use of traffic control devices. It should be pointed out that some stronger associated rules were found in the high-support part. With the network visualization, the association rule method can provide more understandable results for investigating the patterns of work zone crash casualties. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine whether the effects of factors contributing to the severity of driver injuries vary between long-term and short-term work zones. Multinomial logistic regression analysis is adopted to model the relationship between the influencing factors and drivers' injury and fatality risks. A case study is created using drivers' injury severity data from the NASS general estimate system, and two separate multinomial logistic regression models are developed. By comparing the model results, it is found that the light conditions, day of the week, age, gender, airbag availability, restraint use, vehicle age and most harmful event show homogeneous effects on the drivers' injury and fatality risks in the two work zone types. However, the weather, speed limit, traffic control device and number of lanes exhibit opposing effects on the drivers' injury and fatality risks in the two work zone types. [ABSTRACT FROM AUTHOR]

This study develops a Zero-Inflated Negative Binomial (ZINB) regression model to evaluate the factors influencing the loss of human life in shipping accidents using ten years' ship accident data in the South China Sea. The ZINB regression model results show that the expected loss of human life is higher for collision, fire/explosion, contact, grounding, hull damage, machinery damage/failure and capsizing accidents occurring in adverse weather conditions during night periods. Sinking can cause the highest loss of life compared to all other accident types. There are fewer fatalities and missing people when the ship involved in an accident is moored or docked. The results also reveal that the loss of human life is associated with shipping accidents occurring far away from the coastal area/harbour/ports. The results of this study are beneficial for policy-makers in proposing efficient strategies to reduce shipping accident casualties in the South China Sea. [ABSTRACT FROM AUTHOR]

This study aims to develop a truncated lognormal distribution model to predict work zone capacity. The distribution model parameters are formulated as linear functions of road type, number of closed lanes, number of opened lanes, lane closure location, work duration, work intensity, work time, heavy-vehicle percentage, and capacity measurement method. To reflect the uncertainty, a prediction band is constructed for the mean work zone capacity. The maximum likelihood estimation technique is used to determine the coefficients of the variables included in the probability distribution-based capacity model. The sensitivity analysis results confirm that the proposed model has the capability of accurately predicting the mean and prediction band of work zone capacity at any given confidence level. In addition, it is found that work zones located in urban roads, with a large number of opened lanes, low heavy-vehicle percentage, or long-term work duration, have larger mean work zone capacity. A work zone with the closure of the right lane has bigger variability of work zone capacity than a work zone with the left-lane closure. In addition, the measured work zone capacity is a little bigger if the hourly traffic volume converted from the maximum 3-/5-/15-minute flow rate is considered as the work zone capacity. The proposed probability distribution-based capacity model can help traffic engineers to evaluate the variability of work zone capacity and travel delay range. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study aims to develop a maximum likelihood regression tree-based model to predict subway incident delays, which are major negative impacts caused by subway incidents from the commuter’s perspective. Using the Hong Kong subway incident data from 2005 and 2009, a tree comprising 10 terminal nodes is selected to predict subway incident delays in a case study. An accelerated failure time (AFT) analysis is conducted separately for each terminal node. The goodness-of-fit results show that our developed model outperforms the traditional AFT models with fixed and random effects because it can overcome the heterogeneity problem and over-fitting effects. The developed model is beneficial for subway engineers looking to propose effective strategies for reducing subway incident delays, especially in super-large-sized cities with huge public travel demand. [ABSTRACT FROM AUTHOR]

To enable the reliability theory to be further applied in roadway geometry design and safety evaluation, it is necessary to explore and establish the relationship between the failure index in reliability theory and the traffic accident rate. Based on the collected data, the risk ranking-based verification method and regression prediction model-based verification method considering the probability of driving failure were used to verify the relationship between the probability of driving failure and traffic accident rate. The Spearman's rank correlation coefficient was calculated and the results show that there is a moderate correlation between the driving failure probability of the selected road segment and the traffic accident rate. Four regression prediction models for both two-lane and four-lane roads were established considering the probability of driving failure and four significant variables including segment length, annual average daily traffic volume, speed limit, and curve radius. The results show that the established regression prediction models can fit accident data well. This research verified and established the relationship between the probability of driving failure and the road traffic accident rate and pointed out that the traffic accident rate has a positive correlation with the probability of driving failure. [ABSTRACT FROM AUTHOR]

This study aims to evaluate ship collision frequency in port fairways. One case study is created using one month's real-time ship movement data from five major Singapore port fairways. Results show that tankers account for the biggest proportion in the Temasek fairway, whereas the percentage of Roll-on-Roll-Off (RORO) and passenger ships is quite small in the Temasek fairway, Sinki fairway, Jong fairway and Southern fairway. Tankers and container ships are the two major ship types involved in dangerous encounters. The largest number of dangerous head-on and overtaking encounters is located in the Jong fairway. The majority of dangerous crossing encounters have occurred in the West Keppel fairway and Jong fairway. Ship collision frequency at night is found to be significantly higher than during the day in these fairways. [ABSTRACT FROM AUTHOR]

This study aims to develop work zone speed-flow and capacity models, which incorporate work zone configuration factors including the number of work zones, geometrical alignment, work zone speed limit, and work zone length. On the basis of the traffic data from six work zone sites with various work zone configurations, two nonlinear traffic speed and flow models including work zone configuration factors are developed for the uncongested and congested traffic conditions, respectively. A work zone capacity model is proposed on the basis of the two models. The three models can further be used to examine the effects of work zone configuration factors on the speed-flow relationship and capacity at work zones. Results show that traffic speed, traffic flow, and work zone capacity increase with the posted speed limit. Traffic speed under uncongested conditions decreases with the geometric alignment, the number of work zones, work zone length, and heavy vehicle percentage. Under congested conditions, the increase of the number of work zones is found to exhibit a larger negative impact on the traffic flow than the increase of geometric alignment. The number of work zones is also found to have the largest negative impacts on work zone capacity, followed by the geometric alignment. Short work zone length exhibits a relatively minor contribution to increasing work zone capacity. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Shipping movements are operated in a complex and high-risk environment. Fatal shipping accidents are the nightmares of seafarers. With ten years’ worldwide ship accident data, this study develops a binary logistic regression model and a zero-truncated binomial regression model to predict the probability of fatal shipping accidents and corresponding mortalities. The model results show that both the probability of fatal accidents and mortalities are greater for collision, fire/explosion, contact, grounding, sinking accidents occurred in adverse weather conditions and darkness conditions. Sinking has the largest effects on the increment of fatal accident probability and mortalities. The results also show that the bigger number of mortalities is associated with shipping accidents occurred far away from the coastal area/harbor/port. In addition, cruise ships are found to have more mortalities than non-cruise ships. The results of this study are beneficial for policy-makers in proposing efficient strategies to prevent fatal shipping accidents. [ABSTRACT FROM AUTHOR]

This study aims to develop a subway operational incident delay model using the parametric accelerated time failure (AFT) approach. Six parametric AFT models including the log-logistic, lognormal and Weibull models, with fixed and random parameters are built based on the Hong Kong subway operation incident data from 2005 to 2012, respectively. In addition, the Weibull model with gamma heterogeneity is also considered to compare the model performance. The goodness-of-fit test results show that the log-logistic AFT model with random parameters is most suitable for estimating the subway incident delay. First, the results show that a longer subway operation incident delay is highly correlated with the following factors: power cable failure, signal cable failure, turnout communication disruption and crashes involving a casualty. Vehicle failure makes the least impact on the increment of subway operation incident delay. According to these results, several possible measures, such as the use of short-distance and wireless communication technology (e.g., Wifi and Zigbee) are suggested to shorten the delay caused by subway operation incidents. Finally, the temporal transferability test results show that the developed log-logistic AFT model with random parameters is stable over time. [ABSTRACT FROM AUTHOR]

This study evaluates rear-end crash risk associated with work zone operations for four different vehicle-following patterns: car–car, car–truck, truck–car and truck–truck. The deceleration rate to avoid the crash ( DRAC ) is adopted to measure work zone rear-end crash risk. Results show that the car–truck following pattern has the largest rear-end crash risk, followed by truck–truck, truck–car and car–car patterns. This implies that it is more likely for a car which is following a truck to be involved in a rear-end crash accident. The statistical test results further confirm that rear-end crash risk is statistically different between any two of the four patterns. We therefore develop a rear-end crash risk model for each vehicle-following pattern in order to examine the relationship between rear-end crash risk and its influencing factors, including lane position, the heavy vehicle percentage, lane traffic flow and work intensity which can be characterized by the number of lane reductions, the number of workers and the amount of equipment at the work zone site. The model results show that, for each pattern, there will be a greater rear-end crash risk in the following situations: (i) heavy work intensity; (ii) the lane adjacent to work zone; (iii) a higher proportion of heavy vehicles and (iv) greater traffic flow. However, the effects of these factors on rear-end crash risk are found to vary according to the vehicle-following patterns. Compared with the car–car pattern, lane position has less effect on rear-end crash risk in the car–truck pattern. The effect of work intensity on rear-end crash risk is also reduced in the truck–car pattern. [ABSTRACT FROM AUTHOR]

This study attempts to incorporate multi-scenario underreporting rates into multivariate imputation using chain equation (MICE) to address underreporting issues in maritime accident records. In addition, the Tobit regression model is utilized to evaluate the economic loss of maritime accidents for both the original and supplemented data. With ten years' maritime accident data in Fujian waters, one empirical study is created to testify the effectiveness of the proposed method. The marginal effect results from the proposed method significantly differ from the conventional Tobit regression model. The proposed method could significantly correct the over- or underestimated impacts related to various variables (e.g., serious/non-serious accident types, fishing vessels, other ships, and liquid cargo ships). This reveals that the proposed method is capable of correcting the systematic deviation of the analysis results to a satisfactory extent. • This study presents a reliable solution to deal with underreporting issues in maritime accident records. • The underreporting issues are transformed into missing data problem through multi-scenario underreporting rates. • The underreporting issues may cause biased maritime accident analysis results. • The systematic deviations of the model results are effectively corrected by the proposed MSUR-MICE method. [ABSTRACT FROM AUTHOR]

SUMMARY This paper proposed a methodology to estimate rear-end crash potential of the merging vehicles traveling in the merge lane, on the basis of the traffic data extracting from the available videotapes. First, we developed a binary logit model to identify drivers' merging behavior in the work zone merging area. Subsequently, the occurrence potential of rear-end crash based on time-to-collision was computed between the merging vehicle and its neighboring vehicles. The overall crash potential of the merging vehicle was finally determined. It was found that the crash potential decreases with the remaining distance to work zone. Moreover, there will be a rear-end crash potential of 4.0% if the merging vehicle fails to complete merging at the end of work zone merging area. If the merging vehicle takes an early merge, there will be a lower rear-end crash potential (1.2%). These findings suggest that we should encourage merging vehicles to take early merges for improving the traffic safety in the work zone merging areas. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Highlights: [•] Provide a critical review on the approaches to estimating work zone capacity and traffic delay in work zones. [•] Identify the limitations and shortcomings of these approaches. [•] Provide some directions and recommendations for future research. [ABSTRACT FROM AUTHOR]

Abstract: To mitigate the negative traffic impact caused by work zones, land transport authorities usually impose constraints on queue length and travel delay. In reality, a single or multiple subwork zone strategy can be adopted to mitigate queue length and travel delay. However, contractors conducting work projects are only concerned with the minimization of the total maintenance cost. From the contractor’s standpoint, this study proposes a total maintenance cost minimization model to determine the optimal subwork zone length and project start time, subject to queue length and travel delay constraints. Using average hourly traffic (AHT) data, this study shows that total user delay is non-differentiable with respect to the subwork zone length and project start time. This interesting finding demonstrates that previous analytic expressions of the optimal subwork zone length cannot hold for AHT data. To solve the proposed model, an enumeration method is designed. Finally, a numerical example created from the roadside tree trimming in Singapore is used to assess the model and solution method proposed in this study. [Copyright &y& Elsevier]

SUMMARY Roadside trees in Singapore are regularly trimmed for the purpose of traffic safety and roadside tree-trimming project is one typical type of short-term work zone projects. To implement such a short-term work zone project, contractors usually divide an entire work zone into multiple subwork zones with the uniform length. This paper aims to determine an optimal subwork zone strategy for the short-term work zone projects in four-lane two-way freeways with time window and uniform subwork zone length constraints. The deterministic queuing model is employed to estimate total user delay caused by the work zone project by taking into account variable traffic speeds. Based on the user delay estimations, this paper proceeds to build a minimization model subject to time window and uniform length constraints for the optimal subwork zone strategy problem. This paper also presents a variation of the minimization model to examine the impact of unequal subwork zone length constraint. Since these minimization models belong to the mixed-integer non-differentiable optimization problems, an iterative algorithm embedding with the genetic simulated annealing method is thus proposed to solve these models. Finally, a numerical example is carried out to investigate the effectiveness of the proposed models. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study aims to use the classification and regression tree (CART) approach, one of the most powerful data mining techniques, to predict drivers' merging behavior in a work zone merging area. On the basis of the eight factors affecting drivers' merging behavior, a binary CART is built using the merging traffic data collected from a short-term work zone site in Singapore. The CART comprises 7 levels and 15 leaf nodes to predict drivers' merging behavior in the work zone merging area. The results show that the CART provides much higher prediction accuracy than the conventional binary logit model. Traffic engineers can easily understand how drivers make merging/nonmerging decisions. This demonstrates that the CART approach is a good alternative for investigating drivers' merging behavior in work zone merging areas. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Abstract: This study aims to analyze the effects of environment, vehicle and driver characteristics on the risky driving behavior at work zones. A decision tree is developed using the classification and regression tree (CART) algorithm to graphically display the relationship between the risky driving behavior and its influencing factors. This approach could avoid the inherent problems occurred in the conventional logistic regression models and further improve the model prediction accuracy. Based on the Michigan M-94/I-94/I-94BL/I-94BR highway work zone driving behavior data, the decision tree comprising 33 leaf nodes is built. Bad weather, poor road and light conditions, partial/no access control, no traffic control devices, turning left/right and driving in an old vehicle are found to be associated with the risky driving behavior at work zones. The middle-aged drivers, who are going straight ahead in their vehicles with medium service time and equipped with an airbag system, are more likely to take risky behavior at lower work zone speed limits. Further, the middle-aged male drivers engage in risky driving behavior more frequently than the middle-aged female drivers. The number of lanes exhibits opposing effects on risky behavior under different traveling conditions. More specifically, the risky driving behavior is associated with the single-lane road under bad light or weather conditions while drivers are more likely to engage in risky behavior on the multi-lane road under good light conditions. [Copyright &y& Elsevier]

Abstract: This paper aims to develop an improved cellular automata (ICA) model for simulating heterogeneous traffic in work zone. The proposed ICA model includes the forwarding rules to update longitudinal speeds and positions of work zone vehicles. The randomization probability parameter used by the ICA is formulated as a function of the activity length, the transition length and the volumes of different types of vehicles traveling across work zone. Compared to the existing cellular automata models, the ICA model possesses a novel and realistic lateral speed and position updating rule so that the simulation of vehicle’s lateral movement in work zone is close to the reality. The ICA model is calibrated and validated microscopically and macroscopically by using the real work zone data. Comparisons of field data and ICA for trajectories, speed and speed–flow relationship in work zone show very close agreement. Finally, the proposed ICA model is applied to estimate traffic delay occurred in work zone. [Copyright &y& Elsevier]

Abstract: This paper aims to investigate the speed-flow relationship and drivers’ merging behavior in work zone merging areas. It first proposes lane-based speed-flow models, incorporating traffic conflicts among the lanes. It proceeds to develop a desired merging location model determining where drivers start to consider merging and a binary logit model that is applied to estimate the probabilities that drivers will merge into current adjacent gaps. A merging distance model is also proposed to find the 85th percentile of the merging distance. Finally, real work zone traffic data in Singapore are used to calibrate and evaluate the developed models. The findings show that the speed-flow relationship in the through lane is affected by the merge lane traffic under uncongested circumstances. Satisfactory results indicate that the merging behavioral models can competently predict drivers’ merging behavior and that the merging distance model could provide accurate information for traffic engineers to calculate the merge lane length. [Copyright &y& Elsevier]

Transition taper length plays a vitally important role in work zone safety operations because too short a transition taper length will result in higher accident risks and too long a transition taper length could increase traffic delay. This paper evaluates transition taper length under various traffic conditions and road geometries using collision avoidance analysis. The longitudinal distances for lane changing and emergency stopping manoeuvres are respectively calculated using collision avoidance analysis. The higher value between the longitudinal lane changing distance and emergency stopping distance is considered as the expected transition taper length. The comparison of transition taper lengths from the collision avoidance analysis and current empirical transition taper formulae shows that the collision avoidance analysis has the capability of evaluating transition taper lengths. This paper also contributes to providing theoretical supports for these empirical formulae. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a genetic algorithm (GA) approach to assessing work zone casualty risk defined as the likelihood of a vehicle occupant being killed or injured in a work zone crash. The proposed GA approach consists of three components: chromosome coding, fitness function and genetic operators. Based on the Michigan highway work zone crash data, 19 classification rules are identified using the proposed GA approach to determine the work zone casualty risk. The results show that the variable of seat position has the most significant effect on reducing the prediction error of the GA approach. The variables of posted speed limit, traffic control devices and truck or bus involved are found to have no effects on improving the prediction performance. The GA approach outperforms the binary logistic regression technique in terms of the prediction accuracy. This demonstrates that the GA approach is a good alternative for the work zone casualty risk assessment. [Copyright &y& Elsevier]

Abstract: Using driver casualty data from the Fatality Analysis Report System, this study examines driver casualty risk and investigates the risk contributing factors in the construction, maintenance and utility work zones. The multiple t-tests results show that the driver casualty risk is statistically different depending on the work zone type. Moreover, construction work zones have the largest driver casualty risk, followed by maintenance and utility work zones. Three separate logistic regression models are developed to predict driver casualty risk for the three work zone types because of their unique features. Finally, the effects of risk factors on driver casualty risk for each work zone type are examined and compared. For all three work zone types, five significant risk factors including road alignment, truck involvement, most harmful event, vehicle age and notification time are associated with increased driver casualty risk while traffic control devices and restraint use are associated with reduced driver casualty risk. However, one finding is that three risk factors (light condition, gender and day of week) exhibit opposing effects on the driver casualty risk in different types of work zones. This may largely be due to different work zone features and driver behavior in different types of work zones. [Copyright &y& Elsevier]

Abstract: This paper aims to evaluate the rear-end crash risk at work zone activity area and merging area, as well as analyze the impacts of contributing factors by using work zone traffic data. Here, the rear-end crash risk is referred to as the probability that a vehicle is involved in a rear-end crash accident. The deceleration rate to avoid the crash (DRAC) is used in measuring rear-end crash risk. Based on work zone traffic data in Singapore, three rear-end crash risk models are developed to examine the relationship between rear-end crash risk at activity area and its contributing factors. The fourth rear-end crash risk model is developed to examine the effects of merging behavior on crash risk at merging area. The ANOVA results show that the rear-end crash risk at work zone activity area is statistically different from lane positions. Model results indicate that rear-end crash risk at work zone activity area increases with heavy vehicle percentage and lane traffic flow rate. An interesting finding is that the lane closer to work zone is strongly associated with higher rear-end crash risk. A truck has much higher probability involving in a rear-end accident than a car. Further, the expressway work zone activity area is found to have much larger crash risk than arterial work zone activity area. The merging choice has the dominated effect on risk reduction, suggesting that encouraging vehicles to merge early may be the most effective method to reduce rear-end crash risk at work zone merging area. [Copyright &y& Elsevier]

Abstract: 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. [ABSTRACT FROM AUTHOR]

In this study, an Association Rule Bayesian Networks (ARBN) method is established to investigate the impacts of external factors (i.e. environmental factors and ship factors) on human errors. The Bayesian networks have been structured by mining association rules from historical collision accident records. In addition, unlike other related studies that have introduced subjective data (i.e. expert knowledge), this study tends to build Bayesian networks with only objective data (i.e. accident data). In order to solve the problem of small sample size during conditional probability table estimating, this study constructs an environmental-human Bayesian network and a ship-human Bayesian network separately. The results reveal that visibility, location, and time of the day are the main environmental factors affecting the occurrence probability of human errors. For more complex scenarios, the probability of occurring judgment/operation errors in ship collision is 83% under the evidence of spring, daytime, and sea area. Among the ship factors, gross tonnage, ship types, and over safe speed show significant effects on occurring human errors. Large ships are more likely to occur judgment/operation errors under the high-speed situation. From the consequence perspective, negligence errors are highly associated with severe collisions. • This study investigates the occurrence likelihood of human errors under different scenarios. • An ARBN method is developed to reflect the relationship using 10 years' collision accident records. • This study constructs concise ARBN models separately according to the types of influencing factors. • The probability of occurring judgment/operation errors is 83% for ship collisions occurring in spring, daytime and sea area. [ABSTRACT FROM AUTHOR]