Evaluation of Freeway Mobile Work Zone Safety using Driving Simulations

Author(s):  
Hyunjin Park ◽  
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Cheol Oh ◽  
Jaepil Moon
2020 ◽  
Vol 14 (1) ◽  
pp. 67-77
Author(s):  
Carlos Sun ◽  
Huang Feng ◽  
Yaw Adu-Gyamfi

Work zones often deviate from normal conditions in terms of geometrics (e.g. lane closure, narrow lanes), striping/markings, signs, and traffic. A Mobile Work Zone (MWZ) is a special category of a work zone where the location of the work zone keeps changing, often rapidly. Despite MWZ safety being of great interest to transportation agencies, they have not studied it formally. This paper presents an examination of MWZs and collisions involving Truck-Mounted Attenuators (TMAs). This examination utilized data fusion of three major databases from Missouri: crash reports, department of transportation claim reports, and MWZ schedules. The fused dataset involved 139 crashes from 2012-2017. The areas of interest included initial impact location, contributing factors, third-party versus employee fault, vehicle type, work zone activity, seasonality, speed limit, time of day, collision lane, and work train configuration. The majority of the crashes were the fault of third parties (>80%) and distraction/inattentiveness was the largest contributory factor (66%). Public outreach and education should emphasize on the difficulty in providing early warnings of MWZs. There is a significant percentage of crashes involving lane changing (39.2%) and even collision of the middle TMA truck (21.8%). Thus, it is important for the public to understand that an entire work train is an integral unit. Higher speed limit dominated MWZ crashes (>75%), even though they only represented 3.6% of the MWZs scheduled. The results of this study on MWZs provide some foundation for other researchers to pursue statistical modeling, assuming that a larger database of MWZ crashes could be developed.


Author(s):  
Ana Maria Elias ◽  
Zohar J. Herbsman

Construction sites or work zones create serious disruptions in the normal flow of traffic, resulting in major inconveniences for the traveling public. Furthermore, these work zones create safety hazards that require special consideration. Current legislation and programs, at both state and national levels, emphasize the need for a better understanding of work zone problems to address work zone safety. This reality—coupled with the temporary closure of more miles of highway every year for rehabilitation and maintenance—makes the analysis of safety at construction sites a serious matter. A summary of a comprehensive study associated with the development of a new practical approach to address highway safety in construction zones is presented. Because empirical models require sample sizes that are not attainable due to the intrinsic scarcity of construction zone accident data, the problem was studied from the point of view of risk analysis. Monte Carlo simulations were used to develop risk factors. These factors are meant to be included in the calculations of additional user costs for work zones, or simply applied as risk measurements, to optimize the length and duration of closures for highway reconstruction and rehabilitation projects. In this way, it will be possible to assess the danger of work zones to the traveling public and minimize adverse effect of work zones on highway safety.


2003 ◽  
Author(s):  
Christopher Huebschman ◽  
Camilo Garcia ◽  
Darcy Bullock

2018 ◽  
Vol 3 (1) ◽  
pp. 62-71 ◽  
Author(s):  
Umar Ibrahim Khalil ◽  
Bashir Samir
Keyword(s):  

Author(s):  
Nipjyoti Bharadwaj ◽  
Praveen Edara ◽  
Carlos Sun

Identification of crash risk factors and enhancing safety at work zones is a major priority for transportation agencies. There is a critical need for collecting comprehensive data related to work zone safety. The naturalistic driving study (NDS) data offers a rare opportunity for a first-hand view of crashes and near-crashes (CNC) that occur in and around work zones. NDS includes information related to driver behavior and various non-driving related tasks performed while driving. Thus, the impact of driver behavior on crash risk along with infrastructure and traffic variables can be assessed. This study: (1) investigated risk factors associated with safety critical events occurring in a work zone; (2) developed a binary logistic regression model to estimate crash risk in work zones; and (3) quantified risk for different factors using matched case-control design and odds ratios (OR). The predictive ability of the model was evaluated by developing receiver operating characteristic curves for training and validation datasets. The results indicate that performing a non-driving related secondary task for more than 6 seconds increases the CNC risk by 5.46 times. Driver inattention was found to be the most critical behavioral factor contributing to CNC risk with an odds ratio of 29.06. In addition, traffic conditions corresponding to Level of Service (LOS) D exhibited the highest level of CNC risk in work zones. This study represents one of the first efforts to closely examine work zone events in the Transportation Research Board’s second Strategic Highway Research Program (SHRP 2) NDS data to better understand factors contributing to increased crash risk in work zones.


2019 ◽  
Author(s):  
LuAnn Theiss and Gerald L. Ullman ◽  
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