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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]

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]

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 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 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]

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]

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: 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]