Training of Traffic Incident Responders

Owens, Nicholas; Guzman, Juan; Ford, Kevin Graham; Fields, Janice; Armstrong, April; Beasley, Kari; Armstrong, Christopher; Mitchell, Coral; Bedsole, Lisa; Brewster, Rebecca; McGinnis, Kevin; Moore, R. L.; Gallagher, Caroline; Williams, Gary; Connor, Jennifer J.

doi:10.17226/22810

Cited by 9 publications

(14 citation statements)

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“…Communications are performed via radio, email, in person, and by phone. Currently, there is research on improvements to the methodology of TIMs through training processes (Owens et al, 2012). However, with an average of 110 traffic incidents a day at the local DoT (Performance (May): Traffic Managment Center, 2017), there is a need for a program that allows TIMs to quickly and successfully clear incidents by facilitating communication and multitasking in a unified UI.…”

Section: Traffic Incident Managementmentioning

confidence: 99%

Developing an Optimized UI for Traffic Incident Managers

Helgerson

Walton

Loya

et al. 2018

Proceedings of the Human Factors and Ergonomics Society Annual

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Traffic Incident Managers (TIMs) coordinate first responders and help resolve traffic-related incidents. Currently, some use over fifteen different software applications with unique functionalities across three monitors to manage incidents, leading to redundant data entry, unnecessary task switching, and delayed responses. 40 hours of TIMs' screens were recorded during their normal work hours at the Iowa Department of Transportation (DoT). The resulting task analysis from these videos greatly influenced the design of a simplified, web-based, user interface (UI) prototype. The new UI offers a 42.9% reduction in the steps required to manage an incident by combining the functionality of the fifteen different applications used in the existing system into a single, structured UI. This research approach offers a UI model to other DoTs that can lead to faster and more effective incident management.

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Section: Traffic Incident Managementmentioning

confidence: 99%

Developing an Optimized UI for Traffic Incident Managers

Helgerson

Walton

Loya

et al. 2018

Proceedings of the Human Factors and Ergonomics Society Annual

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“…SHRP 2 developed a national TIM training course for TIM responders and managers through a series of projects (9). The course was initially developed under SHRP 2 Project L12, Improving Traffic Incident Scene Management.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Framework for Planning and Assessment of Traffic Incident Management Programs

Jin

Hossan

Gan

et al. 2014

Transportation Research Record

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This paper presents a comprehensive framework for traffic incident management (TIM) covering major components and key elements that contribute to the success of a TIM program. The proposed framework starts with three broad categories of components-strategic, tactical, and support-and then expands with detailed elements that are essential to accomplishing the goals for each component. The strategic component focuses on establishing and promoting institutional, organizational, and financial contexts, and the support component addresses information and communication aspects of TIM. Both components are critical to the performance of the tactical component, which covers the core activities in incident clearance and traffic management. The framework builds on federal guidance for major components and strategies in TIM while adding more structured details and perspectives that serve as the basic guidelines in planning and assessment of TIM programs. The paper also presents a case study that links the Florida Department of Transportation District 4's TIM practices with the framework. The case study can be seen as examples of (best) practices for each subelement of the framework. In addition, this study demonstrates the role of the framework in providing guidance for program planning and assessment.

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“…Traffic incidents frequently affect traffic operations, accounting for more than half of all urban traffic delays and almost all rural traffic delays ( 1 ). Furthermore, traffic incidents expose other vehicles to the risk of becoming involved in an SC ( 2 ). A crash is considered as an SC if it occurs: ( a ) at the scene of the primary incident (PI) ( 3 , 4 ); or ( b ) within the queue upstream of the PI ( 3 ); or ( c ) within the queue in the opposite direction of the PI and caused by driver distraction (i.e., rubbernecking effect) ( 5 ).…”

mentioning

confidence: 99%

“…SCs are nonrecurring in nature; not only do they affect traffic operations, but they also impose risk to the safety of road users and traffic incident responders. The U.S. Department of Transportation estimated that SCs alone are responsible for ∼18% of all freeway traffic fatalities and 20% of all crashes ( 2 ). Compared with PIs, SCs have a significant impact on traffic management resource allocation ( 6 , 7 ).…”

mentioning

confidence: 99%

“…Prevention of SCs has therefore been highlighted as a high priority task for traffic incident managers ( 8 ). In fact, FHWA uses the reduction of SCs as one of the performance measures for state incident management systems ( 2 ). Several state agencies, including Florida, are considering SC identification and mitigation strategies in allocating funding for on-road help services (e.g., Road Rangers) and the development of traffic incident management (TIM) programs ( 9 ).…”

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confidence: 99%

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Identification of Secondary Crash Risk Factors using Penalized Logistic Regression Model

Kitali

Alluri

Sando

et al. 2019

Transportation Research Record

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Secondary crashes (SCs) have increasingly been recognized as a major problem leading to reduced capacity and additional traffic delays. However, the limited knowledge on the nature and characteristics of SCs has largely impeded their mitigation strategies. There are two main issues with analyzing SCs. First, relevant variables are unknown, but, at the same time, most of the variables considered in the models are highly correlated. Second, only a small proportion of incidents results in SCs, making it an imbalanced classification problem. This study developed a reliable SC risk prediction model using the Least Absolute Shrinkage and Selection Operator (LASSO) penalized logistic regression model with Synthetic Minority Oversampling TEchnique-Nominal Continuous (SMOTE-NC). The proposed model is considered to improve the predictive accuracy of the SC risk model because it accounts for the asymmetric nature of SCs, performs variable selection, and removes highly correlated variables. The study data were collected on a 35-mi I-95 section for 3 years in Jacksonville, Florida. SCs were identified based on real-time speed data. The results indicated that real-time traffic variables and primary incident characteristics significantly affect the likelihood of SCs. The most influential variables included mean of detector occupancy, coefficient of variation of equivalent hourly volume, mean of speed, primary incident type, percentage of lanes closed, incident occurrence time, shoulder blocked, number of responding agencies, incident impact duration, incident clearance duration, and roadway alignment. The study results can be used by agencies to develop SC mitigation strategies, and therefore improve the operational and safety performance of freeways.

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Training of Traffic Incident Responders

Cited by 9 publications

References 0 publications

Developing an Optimized UI for Traffic Incident Managers

Developing an Optimized UI for Traffic Incident Managers

Comprehensive Framework for Planning and Assessment of Traffic Incident Management Programs

Identification of Secondary Crash Risk Factors using Penalized Logistic Regression Model

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