Work Zone Configurations Research Articles

Assessing the impact of driver compliance on traffic flow and safety in work zones amid varied mixed autonomy scenarios

The safety of work zones is a critical issue for drivers, transportation agencies, and governing authorities. In particular, the vehicles that perform lane changes in the proximity of the work zones involving lane closure, pose a significant threat to the safety of the public and the work zone workers, as they need to complete a forced merging. Yet, there is no comprehensive simulation framework to examine the work zone traffic safety under different compliance distributions of the drivers to the warning delivery for the work zone in a mix-autonomy operation of autonomous and human-driven vehicles. To fill this void, we present an integrated microsimulation framework to assess the correlation between the number of vehicles that perform late merge at the taper (LMT) and traffic mobility and safety under different empirical compliance distributions of the drivers to the warning delivery for the downstream work zone.We employ different work zone configurations to illustrate the relationship between late merges at the taper and performance indicators for traffic mobility and safety of the work zone under a variety of work zone configurations. Simulation results show that compliance distribution significantly impacts the number of late merges at the taper (LMTs) and thereby traffic safety and efficiency. Our findings demonstrate that when human-driven vehicles exhibit high compliance behavior to the merging warning signs, it can offset the impact of the lower percentage of market penetration rate (MPR) levels for autonomous operation to achieve comparable traffic safety and efficiency. We further employ the conflation of microsimulation observations and data-driven models to design a regression model to predict LMTs as an indicator for traffic conditions using the work zone configuration as input variables. In particular, we address the heterogeneity induced by the compliance distribution of drivers by sampling the data points from the distribution to capture the diversity in compliance behaviors of the drivers. Our findings can provide insights for practitioners and researchers regarding the optimal compliance distribution using the performance measurements demonstrated in this work.

Assessing the effects of geometry and non-geometry related factors in work-zone crashes

Objective Work zones are unique in geometry and traffic management, utilizing special traffic signs, standard channelizing devices, appropriate barriers, and pavement markings. These configurations can introduce unexpected driving conditions, potentially posing risks to drivers. This analysis aims to explore potential differences in contributing factors between work-zone crashes where geometry was identified as a factor and those where it was non-geometry factor. To gain insights into driver injury severities in single-vehicle work-zone crashes, this study analyzed work zone crash data from Florida. Method This study employed random parameters logit models, accommodating potential variations in parameter estimates’ means and variances. The dataset encompassed a wide array of factors known to influence driver injury severity, encompassing crash characteristics, vehicle attributes, roadway features, prevailing traffic volume, driver profiles, and spatial and temporal considerations. Results This analysis yielded significantly distinct parameters for work-zone crashes, distinguishing between geometry-related and non-geometry-related factors (primarily the human factors). This distinction suggests a complex interplay between these factors. Notably, the marginal effects of individual parameter estimates exhibited marked differences between these two categories – geometry and non-geometry factors. Conclusion These findings contribute to the growing body of research indicating that geometric restrictions within work zones introduce a distinct set of risk factors compared to non-geometry-related factors. Recognizing the significance of geometric restrictions, beyond typical driving conditions, holds the implications for enhancing safety within various work zone configurations and offers valuable insights for crash scene investigators to pinpoint contributing factors accurately.

Development and Evaluation of Statistical and Machine-Learning Models for Queue-Length Estimation for Lane Closures in Freeway Work Zones

Freeway maintenance and rehabilitation work usually require closing one or multiple lanes, interrupting traffic flows, and creating queues upstream of the work zone. Public agencies can use queue length as a criterion to determine the maximum duration of lane closures and necessary traffic diversions. Previous studies of estimating queue length due to work zone lane closures are data- and time-intensive. This study presents an efficient approach for estimating queue length estimation due to work zone lane closures by developing various statistical and machine-learning models. The inputs for these queue length estimation models were vehicle demand, lane closure duration, active work zone length, and heavy vehicle percentage. The extent of the queues caused by short-term work zones on freeways for 2-to-1 (one-lane closure on a two-lane freeway), 3-to-1 (one-lane closure on a three-lane freeway), and 3-to-2 (two-lane closure on a three-lane freeway) lane-closure configurations can be estimated with these models. The primary scientific contribution of this study is the applicability of the queue length estimation models in any freeway network with work zone configurations and geometric features such as those used for model development. This research evaluated the efficacy of both statistical and machine-learning models for estimating the queue length considering different work zone scenarios. The accuracy of the queue length estimation models was evaluated for a different network that the original models had not seen previously. Among the statistical models, the quantile regression model had the best accuracy based on mean absolute percentage error (MAPE) for the 2-to-1 lane-closure configuration (88%), and the multiple linear regression had the best accuracy for the 3-to-1 (76%) and 3-to-2 (72%) lane-closure configurations. Among the machine-learning models, the stacking regressor model had the best accuracy for 2-to-1 (95%), 3-to-1 (90%), and 3-to-2 (89%) lane-closure configurations. Based on the analysis, it was observed that machine-learning models performed better than the traditional statistical models in estimating queue lengths.

How effective is reducing traffic speed for safer work zones? Methodology and a case study in Pennsylvania

Transportation agencies post and enforce reduced speed limits in work zones to ensure work zone safety, since traffic speed is found to be associated with work zone crash risks. However, prior findings on the relationship between speed and crash rate in work zones are inconsistent. This may be attributed to the methods of statistical associations between traffic speed and crash risks that do not necessarily discover true causal relations. In fact, work zone presence could lead to the reduction of actual traffic speed that influences crash risks, where it may also directly impose effects on crash risks as a result of work zone configurations. The actual traffic speed (not posted speed limit) is also known as a “mediator” where work zones can indirectly impact the crash risks. It is challenging to rigorously separate the causal effect of traffic speed on work zone crash risk from that directly caused by work zones. The underlying causal relation could help to determine what reduced post speed limit (with enforcement) is necessary to ensure work zone safety under the most desired “actual traffic speed”. This study proposes to use the sequential g-estimation and the regression discontinuity design to estimate the controlled direct effect of traffic speed on work zone crashes. Two research gaps are identified and filled: inaccurate inferences of the effect of reduced speed limit in work zones as a result of ignoring (1) potential post-treatment bias since traffic speed is a mediator; and (2) potential confounding bias caused by unobservable roadway characteristics. The proposed methodology was applied to 4008 work zones in Pennsylvania from 2015 to 2017, and the results were validated through a series of robustness tests. The results indicate that the direct causal effect of the presence of work zones on crash risk is significantly positive when the traffic speed is relatively low (i.e., lower than 55 mph in this case study), while traffic speed has a positive causal effect on crash occurrences when the actual traffic speed is high (i.e., greater or equal to 55 mph). It suggests that strictly enforcing reduced posted speed limits in work zones is particularly effective when the actual traffic speed is greater than 55 mph. This is particularly true on roadways with high traffic volume (i.e., AADT > 20,000 vehicles per day), long, and daytime work zones (i.e., > 3000 m). On the other hand, the effect of enforcing reduced speed on work zone safety is unclear when the actual speed is already low. In this case, improving work zone configurations and driving behaviors may be more effective in reducing crash risks.

Inferring heterogeneous treatment effects of work zones on crashes

The increasing number of work zone crashes has been a significant concern for road users, transportation agencies, and researchers. Crashes can be caused by work zones, and this effect changes across different work zone configurations, traffic volumes, roadway functional classifications, and weather conditions. This is typically represented by Crash Modification Functions (CMFunctions). However, current methods for developing work zone CMFunctions have two major limitations: (1) They focus on analyzing statistical associations and fail to mitigate the confounding bias due to possible unobservable roadway characteristics; and (2) They cannot address CMFunctions of multiple variables simultaneously, such as weather and traffic conditions, since they are represented using mixed data types (continuous and categorical) that could potentially affect the causal effect of work zones on crashes. In this study, we develop a method that utilizes causal forest with fixed-effect modeling to mitigate the confounding bias while identifying CMFunctions conditioning on various environmental characteristics, including work zone configurations, traffic volume, roadway functional classification, and weather conditions. The developed method was applied to 3378 work zones that occurred in Pennsylvania between 2015 and 2017. The results were validated via a series of robustness tests. The validations demonstrate that this method can mitigate the confounding bias and identify CMFunctions of multiple variables. The results also show that the causal effect of a work zone on crash occurrence is significantly positive (p<0.05) on roadways with high traffic volumes (e.g., > 20,000 vehicles per day) and on medium length (e.g., 2000 to 5000 m) work zones. It appears that having medium–long (e.g., between 6000 and 8000 m) work zones or long duration (e.g., longer than 4 h) work zones do not necessarily lead to extra crashes.

Work Zone Crash Occurrence Prediction Based on Planning Stage Work Zone Configurations Using an Artificial Neural Network

Work zones are essential to maintain and improve road infrastructure. However, work zones affect traffic safety, and crashes and fatalities associated with work zones in the U.S.A. have increased substantially. Most existing work zone crash studies are not able to support the improvement of work zone planning and configuration, despite providing insights about individual crash level attributes. This study proposes an artificial neural network-based approach to predict the crash occurrence in work zones using only work zone configurations and design parameters. The goal is to explore whether using simple work zone configuration features available at the planning stage as the input can achieve satisfactory work zone crash prediction. The performance of the proposed model is satisfactory and comparable with existing studies using more comprehensive features. The proposed approach, early in the work zone design and planning stage, can provide designers and decision-makers with quick work zone safety evaluation for design alternatives and suggest extra resources and attention needed.

Countermeasures to Reduce Truck-Mounted Attenuator (TMA) Crashes: A State-of-the-Art Review

To support worker and driver safety, this study conducted a comprehensive literature review to identify methods of enhancing TMA visibility, improving work zone configurations, and ensuring worker safety. To increase TMA recognition, this study observed that the use of a 6-to-8-inch wide yellow and black inverted ‘V’ pattern of retroreflective chevron markings, sloped at a 45-degree angle downward in both directions from the upper center of a rear panel is effective in alerting drivers to work zones. This study also recommends applying amber and white warning LEDs, which flash in an asynchronous pattern at a 1 Hz frequency and are mounted against a solid-colored background for a 360-degree view visible at least 1500 feet from the work zone. In addition, a work zone vehicle configuration consisting of a lead, buffer, and advance warning truck with a buffer space between 100 and 150 ft is suggested to reduce the risk of lateral intrusions and TMA roll-ahead. In parallel, workers should wear high-visibility vests noticeable at a minimum distance of 1000 feet and headwear with at least 10 square inches of retroreflective material. Some intelligent transport systems are also suggested to enhance TMA recognition and potentially minimize work zone fatalities. Application of the recommended guidelines will potentially improve current practices and significantly reduce the occurrence of TMA crashes in construction and maintenance work zones.

Inferring the causal effect of work zones on crashes: Methodology and a case study

The increasing number of crashes occurring in work zones has received considerable attention in recent years. Previous studies have mainly focused on associations between work zone configurations and crash occurrence. Although identification of associational relations helps us understand how work zones co-exist with crashes, it does not provide interventional guidelines necessary to improve safety of work zone operations. In this paper, a causal inference model based on the potential outcome framework is proposed to rigorously infer the causal effects of work zone presence on crash risks under various work zone configurations, along with robustness tests. In developing such a causal model, three research gaps are identified and addressed: (1) potential confounding bias due to unobservable roadway characteristics; (2) potential bias caused by unobserved variables in multisource data; and (3) lack of actually observed traffic data and weather information at the exact time when a crash occurred and lack of large-scale high-granular data. The proposed methodology is applied to 5,006 work zones in Pennsylvania from 2015 to 2017, and the results are validated via a series of robustness tests. The results show that the causal effect of a work zone on crash occurrence is significantly positive, especially on roadways with high traffic volumes, on long-distance work zones, and work zones conducted during daytime. It appears that conducting work zones during nighttime with the current deployment strategies on Pennsylvania state roads does not necessarily increase crash risks, but a work zone significantly increases crash risks during day time.

Analysis of Headway and Speed Based on Driver Characteristics and Work Zone Configurations Using Naturalistic Driving Study Data

The objective of this paper is to analyze headway and speed distribution based on driver characteristics and work zone (WZ) configurations by utilizing Naturalistic Driving Study (NDS) data. The NDS database provides a unique opportunity to study car-following behaviors for different driver types in various WZ configurations, which cannot be achieved from traditional field data collection. The complete NDS WZ trip data of 200 traversals and 103 individuals, including time-series data, forward-view videos, radar data, and driver characteristics, was collected at four WZ configurations, which encompasses nearly 1,100 vehicle miles traveled, 19 vehicle hours driven, and over 675,000 data points at 0.1 s intervals. First, the time headway selections were analyzed with driver characteristics such as the driver’s gender, age group, and risk perceptions to develop the headway selection table. Further, the speed profiles for different WZ configurations were established to explore the speed distribution and speed change. The best-fitted curves of time headway and speed distributions were estimated by the generalized additive model (GAM). The change point detection method was used to identify where significant changes in mean and variance of speeds occur. The results concluded that NDS data can be used to improve car-following models at WZs that have been implemented in current WZ planning and simulation tools by considering different headway distributions based on driver characteristics and their speed profiles while traversing the entire WZ.

Study of work zone traffic safety under adverse driving conditions with a microscopic traffic simulation approach

Work zone traffic safety under adverse weather conditions has been a serious concern for drivers and transportation agencies. Existing studies on work zone traffic safety with statistical approaches are limited by the availability of data from historical crashes. To date, there is no comprehensive simulation framework to assess work zone traffic safety under adverse driving environments by considering both multi-vehicle and single-vehicle crashes. To fill this gap, this paper presents an integrated framework to evaluate traffic safety in work zone under adverse driving conditions by considering specific work zone configuration, weather and road surface conditions. A new risk index is introduced to assess the traffic safety risk of work zones by integrating the risks of multi-vehicle crashes and single-vehicle crashes. Traffic safety of a typical work zone under different weather conditions is studied to demonstrate the proposed framework. The impacts of the differential speed limits (DSL) and truck proportion on the work zone traffic safety are also investigated. Results show that adverse weather may increase the crash risk in work zones. The effect of DSL on the work zone traffic safety is found to be insignificant while the truck ratio influences the work zone safety in the rainy and snowy weather by primarily affecting the multi-vehicle crash risks.

Safety analysis of work zone complexity with respect to driver characteristics — A simulator study employing performance and gaze measures

Driving is a complex task that consists of several physical (motor-related) and physiological (biological changes within the body) processes occurring simultaneously. The complexity of the task depends on several factors, but this research focuses on work zone configurations and their effect on driver performance and gaze behavior. The increase in work zone fatalities in the United States between 2015 and 2018 coupled with the limited literature of driver behavior in these complex environments requires a more comprehensive study. Given the nature of these crashes, typically lane departures, gaze behavior provided an additional physiological dimension to the present research. A framework that comprises of the interactions between driver characteristics, mental workload, and situation awareness, with longitudinal control, lateral control, and gaze behavior is proposed. Crash analysis and a simulator study with 90 participants were carried out to investigate the performance and gaze-based changes with respect to various work zone configurations. Distracted driving was also studied by including a secondary task. The results showed a significant interaction between the longitudinal control and the standard deviation of horizontal gaze position in predicting lateral control. Also, significant differences in lateral control and horizontal gaze variations were observed between genders. Female drivers showed lower lateral position deviations and lower horizontal gaze variability. This was a key finding given the inherently higher number of work zone crashes involving male drivers. Placing work zone barriers further away, by up to one meter from pavement edges, could significantly decrease mental workload and improve safety in work zones.

Discussion of active safety countermeasures of motorway work zone

A series of comparison analyses of work zone configurations, traffic organizations and work management among China and oversea countries are carried out. Taking into consideration of human, vehicles, roads, environment as well as management factors, the causes of traffic accidents in work zone areas are deeply discussed. Based on road safety in work zone areas, a series of active traffic safety improvement countermeasures for both workers and drivers in work zone areas have been introduced from the respects from traditional safety devices and traffic control measures to information and intelligent measures, which will provide inspires for the improvement of work safety and operation safety in work zone areas.

Calibration of Vissim Models for Rural Freeway Lane Closures: Novel Approach to the Modification of Key Parameters

The definition of freeway work zone capacity has been a topic of debate for several decades, leaving agencies with limited guidance on predicting the behavior of traffic flow at given volumes for various work zone configurations. The methodology presented in the recently published 6th edition of the Highway Capacity Manual (HCM) is a substantial improvement over historical guidance and provides estimates of the mean queue discharge rate under a variety of prevailing site conditions. However, it is limited by the fact that its outputs are deterministic, while traffic flow and breakdown are stochastic phenomena. Recently, well-calibrated microsimulation models have shown promise as a freeway work zone traffic analysis tool, but most guidance is focused on site-specific modeling. This research aimed to address these shortcomings by presenting a novel approach to developing and calibrating generalizable microsimulation models for rural freeway lane closures in Vissim, a traffic simulation software package developed by the PTV Group. Specifically, it was determined that such models may best replicate field conditions at rural freeway work zones when time headway is described by a field-measured distribution and truck characteristics are representative of the United States (U.S.) fleet. The results suggested that the default desired acceleration for heavy trucks should be set between 2 and 3 ft/s2 and that separate time headway distributions should be constructed for passenger cars and trucks. The methodology presented herein may be extended to obtain stochastic estimates of capacity for sites exhibiting a variety of geometric, traffic, and environmental characteristics.

Modeling Highway Performance under Various Short-Term Work Zone Configurations

AbstractFederal rules mandate state departments of transportation and metropolitan planning organizations to measure and report on the performance of highways within their jurisdictions. Those rule...

Analysis of passenger-car crash injury severity in different work zone configurations

Work zone safety remains a priority to the Federal Highway Administration, State Highway Departments, highway engineers, and the traveling public. Work zones create a hospitable environment for crashes; an issue that gained tremendous share of attention in recent years. Therefore, every effort should be sought out to reduce the injury severity of crashes in work zones. In this paper we attempt to investigate factors contributing to the injury severity of passenger-car crashes in different work zone configurations. Considering the discrete ordinal nature of injury severity categories, a Mixed Generalized Ordered Response Probit (MGORP) modeling framework was developed. The model estimation was undertaken by compiling a database consisting of 10 years of crashes that involved at least one passenger car, and occurred in a work zone. Revealing the underlying factors contributing to injury severity levels for different work zone configurations will allow for distinguishing mitigation methods for higher severity outcomes that best suit each of the depicted work zone layouts. This can be accomplished through the implementation of specific safety measures based on the specific configuration of a work zone as a potential crash location. Elasticity analysis suggests that partial control of access, roadways classified as rural, crashes during evening times, crashes during weekends, and curved roadways are key factors that increase the likelihood of severe outcomes. Also, the effects of several covariates were found to vary across the different work zone configurations.

Estimation of Saturation Headway in Work Zones on Urban Streets

Work zones and lane closures on urban arterials can cause significant disruptions to the traveling public, and methods are increasingly needed to estimate the reductions to saturation flow rates that result from work zones at signalized intersections. A set of statistical models that estimate saturation headways as a function of the presence and configuration of the work zone on signalized arterial streets is presented. More than 10,000 individual vehicular headway observations were collected from video observations in and after work zones at six study sites in North Carolina. Conventional multiple-regression and path-based-regression models (structural equation model) were used to develop the saturation headway models. Three models are provided at different aggregation levels of the collected data with identical work zone configurations. The models developed at cycle-length, 15-min, and full aggregation produced adjusted R-squared values of .3259, .7209, and .895, respectively. The proposed model incorporates the effects of lane configuration, pavement condition, turning percentage from shared lanes, work intensity, and number of closed exclusive turning lanes. Based on path analysis, the structural equation model satisfies all the rule-of-thumb criteria for goodness-of-fit indices. The model uses Highway Capacity Manual default values for turning-vehicle headway effect as its intercept coefficient value.

Drivers׳ merging behavior data in highway work zones.

There have been growing research interests in finding a suitable work zone layout to improve work zone safety and traffic efficiency. This paper contains data supporting the research article entitled: Effects of work zone configurations and traffic density on performance variables and subjective workload (Shakouri et al., 2014 [1]). A full factorial experiment was conducted to compare the efficiency of two work zone configurations by using a driving simulator with two levels of work zone configuration, two levels of traffic density and three levels of sign placement as fixed factors. Seven female and 23 male participants completed the experiment. In this paper we present the data relating to demographic information of participants, driving simulator data and subjective workload evaluation of participants for each work zone.

Work Zone Crash Cost Prediction with a Least Median Squares Linear Regression Model

Traffic safety considerations are an important component of work zone design and implementation plans. This study aimed to develop a safety estimation approach on the basis of work zone scheduling and configuration parameters to help engineers and decision makers during the work zone traffic management design stage. This approach has its basis in the fusion of multiple years of statewide work zone records, work zone–related crash reports, and traffic detection data. First, a matching algorithm was used to integrate those data sets to provide detailed circumstances of work zone crashes. Second, the actual vehicle miles traveled in work zones were calculated and used as the exposure measure. The work zone crash costs also were calculated. Third, a least median squares linear regression model was used to build the crash cost prediction tool on the basis of the work zone configurations and vehicle miles traveled. This model was tested, and the results indicated that it could accurately predict work zone crash costs. Recommendations for work zone scheduling and configuration parameters therefore could be made. Although the Wisconsin Lane Closure System work zone configurations are used for operational purposes and differ from the ones in the Manual on Uniform Traffic Control Devices, other types of work zone configurations in similar systems can be incorporated easily into this approach. Thus this approach would be easy to adopt for use with the existing traffic management plan process as a proactive method to avoid high-risk work zone scenarios.

Traffic Flow at a Freeway Work Zone with Reversible Median Lane

Work zones on freeways usually affect the quality of service for road users. Aiming to reduce traffic flow disruptions to a minimum, Hessen Mobil – Road and Traffic Management installed an innovative reversible lane system in a work zone on Autobahn A 3 south-east of Frankfurt, Germany. The section with three lanes and temporary hard shoulder running in both directions carries a high amount of commuter traffic with considerable fluctuations in peak traffic flow direction. During road works, four lanes in the peak direction and three lanes in the non-peak direction could be maintained through the use of a reversible lane system. The paper discusses the effects of the reversible lane system on traffic flow and road safety. Radar measurements revealed a maximum traffic volume of roughly 1500 veh/h on the reversible lane, which is around 25% of the total traffic volume during peak hours. The capacity of the work zone was estimated with the stochastic capacity estimation technique based on models for censored data. Compared with the capacity of the unaffected three-lane carriageway with temporary hard shoulder running, a decrease of the capacity by 14% to 17% was estimated for the four-lane work zone configuration including the reversible lane, depending on the direction. The difference between the capacities in both directions can be explained by the different lane geometries at the respective beginning of the work zone, leading to a higher number of lane changing manoeuvers directly upstream of the lane diverge in one direction. The traffic flow analysis also yielded a considerable impact of the work zone on peak hour traffic demand volumes, which were reduced by approximately 1000 veh/h. Similar to other freeway work zones, the road safety analysis revealed an increase of accident rates during road works. However, based on police accident reports only 10% of the total number of accidents and none of the severe accidents could be linked to particular features of the reversible lane system. Altogether, the investigation shows that a reversible lane system is a useful, safe and accepted instrument of intelligent traffic management for freeway work zones with high fluctuations in peak traffic flow direction. At the analyzed work zone, estimated travel time losses of 400000 veh*h could be saved during two months of road works by the application of the reversible lane compared with a permanent lane reduction in one direction.

Innovative Work Zone Capacity Models from Nationwide Field and Archival Sources

Freeway work zone capacity has been the focus of significant research, but most studies were limited to specific geographic regions or work zone configurations or both. To date, no work zone predictive capacity model exists for U.S. freeways that is based on a geographically representative data set or sensitive to key geometric and operational attributes of the work zone. This paper proposes a new capacity model for freeway work zones, developed from nationwide field data fused with data obtained from an in-depth review of archived literature of prior work zone capacity studies in the United States. The proposed model estimates work zone capacity as a function of the lane closure severity index, barrier type, area type, lateral clearances, and daytime or nighttime work conditions. The model was successfully validated with 25% of the combined data that were not used for the model development. In addition, findings from literature archives suggested a 13.4% difference between prebreakdown, uninterrupted capacity and the ensuing queue discharge rate. The developed capacity model is intended to be incorporated into the next release of the Highway Capacity Manual and provides important insights on the relative effects of work zone configuration and other variables on the expected capacity of freeway work zones.