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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]

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]

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]

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]

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]

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]

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: 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]

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]