Collection, Analysis, and Reporting of Kentucky Traffic Incident Management Performance

2021 ◽  
pp. 036119812110010
Author(s):  
Xu Zhang ◽  
Reginald R. Souleyrette ◽  
Eric Green ◽  
Teng Wang ◽  
Mei Chen ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Management Strategies ◽  
Incident Management ◽  
Vehicle Crashes ◽  
Clearance Time ◽  
Emergency Responders ◽  
Traffic Incident ◽  
Choropleth Maps ◽  
Traffic Incident Management ◽  
Secondary Crashes

Traffic incidents remain all too common. They negatively affect the safety of the traveling public and emergency responders and cause significant traffic delays. Congestion associated with incidents can instigate secondary crashes, exacerbating safety risks and economic costs. Traffic incident management (TIM) provides an effective approach for managing highway incidents and reducing their occurrence and impacts. The paper discusses the establishment and methods of calculation for five TIM performance measures that are used by the Kentucky Transportation Cabinet (KYTC) to improve incident response. The measures are: roadway clearance time, incident clearance time, secondary crashes, first responder vehicle crashes, and commercial motor vehicle crashes. Ongoing tracking and analysis of these metrics aid the KYTC in its efforts to comprehensively evaluate its TIM program and make continuous improvements. As part of this effort, a fully interactive TIM dashboard was developed using the Microsoft Power BI platform. Dashboard users can apply various spatial and temporal filters to identify trends at the state, district, county, and agency level. The dashboard also supports dynamic visualizations such as time-series plots and choropleth maps. With the TIM dashboard in place, KYTC personnel, as well as staff at other transportation agencies, can identify the strengths and weaknesses of their incident management strategies and revise practices accordingly.

Evaluation of incident management strategies and technologies using an integrated traffic/incident management simulation

2009 ◽  
Vol 2 (2/3) ◽  
pp. 155 ◽  
Author(s):  
Kaan M.A. Ozbay ◽  
Weihua Xiao ◽  
Gaurav Jaiswal ◽  
Bekir Bartin ◽  
Pushkin Kachroo ◽  
...  
Keyword(s):  
Management Strategies ◽  
Incident Management ◽  
Traffic Incident ◽  
Traffic Incident Management

Secondary Crash Identification using Crowdsourced Waze User Reports

2021 ◽  
pp. 036119812110130
Author(s):  
Zhihua Zhang ◽  
Yuandong Liu ◽  
Lee D. Han ◽  
Phillip Bradley Freeze
Keyword(s):  
Clustering Algorithm ◽  
Contour Plot ◽  
Incident Management ◽  
Threshold Method ◽  
Accurate Identification ◽  
Traffic Incident ◽  
Traffic Incident Management ◽  
Secondary Crashes ◽  
Static Threshold

Secondary crashes are crashes that occur as a result of the nonrecurrent congestion originating from primary crashes, and always have a greater impact on safety and traffic than a single crash. A better understanding of secondary crashes would benefit traffic incident management, and this requires accurate identification of secondary crashes. This study explores using crowdsourced Waze user reports to identify secondary crashes. A network-based clustering algorithm is proposed to extract the primary crash cluster, including all user reports originating from the primary crash, and any crash that occurred within the cluster would be a secondary crash. This method works as a filter to select accurate primary–secondary relationships, thus precisely identifying secondary crashes. A case study is performed with crashes occurring from June to December 2019 on a 30-mi stretch of I-40 in Knoxville, TN. A static threshold method (crash duration and 10 mi) was used to preselect the potential primary–secondary crash pairs, and 75 out of 708 crashes were identified as potential secondary crashes. Based on the preselected primary–secondary crash pairs, 17 secondary crashes were obtained with the proposed method and the results were compared with one of the commonly used methods, the speed contour plot method. Though the proposed method captured fewer secondary crashes, it did identify several secondary crashes that could not be observed with the speed contour plot method. The results showed the applicability of the method and the potential of crowdsourced Waze user reports in secondary crash identification.

User Cost Analysis of UDOT’s Traffic Incident Management Program

2021 ◽  
Author(s):  
Mitchell G. Hadfield ◽  
Logan S. Bennett ◽  
Grant G. Schultz ◽  
Mitsuru Saito ◽  
Dennis L. Eggett
Keyword(s):  
Cost Analysis ◽  
Management Program ◽  
Incident Management ◽  
User Cost ◽  
Traffic Incident ◽  
Traffic Incident Management

Traffic Incident Duration Estimation Based on a Dual-Learning Bayesian Network Model

2018 ◽  
Vol 2672 (45) ◽  
pp. 196-209 ◽  
Author(s):  
Haozhe Cong ◽  
Cong Chen ◽  
Pei-Sung Lin ◽  
Guohui Zhang ◽  
John Milton ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Expert Knowledge ◽  
Transportation Systems ◽  
Practical Significance ◽  
Incident Management ◽  
Highway Traffic ◽  
Traffic Incidents ◽  
Traffic Incident ◽  
Incident Duration ◽  
Traffic Incident Management

Highway traffic incidents induce a significant loss of life, economy, and productivity through injuries and fatalities, extended travel time and delay, and excessive energy consumption and air pollution. Traffic emergency management during incident conditions is the core element of active traffic management, and it is of practical significance to accurately understand the duration time distribution for typical traffic incident types and the factors that influence incident duration. This study proposes a dual-learning Bayesian network (BN) model to estimate traffic incident duration and to examine the influence of heterogeneous factors on the length of duration based on expert knowledge of traffic incident management and highway incident data collected in Zhejiang Province, China. Fifteen variables related to three aspects of traffic incidents, including incident information, incident consequences, and rescue resources, were included in the analysis. The trained BN model achieves favorable performance in several areas, including classification accuracy, the receiver operating characteristic (ROC) curve, and the area under curve (AUC) value. A classification matrix, and significant variables and their heterogeneous influences are identified accordingly. The research findings from this study provide beneficial reference to the understanding of decision-making in traffic incident response and process, active traffic incident management, and intelligent transportation systems.

Vulnerability Assessment of Urban Intersections apropos of Incident Impact on Road Network and Identification of Critical Intersections

2020 ◽  
Vol 2674 (8) ◽  
pp. 672-686
Author(s):  
Kaniska Ghosh ◽  
Bhargab Maitra
Keyword(s):  
Expert Opinion ◽  
Vulnerability Assessment ◽  
Road Network ◽  
Transportation Network ◽  
Management Strategies ◽  
Management Program ◽  
Incident Management ◽  
Present Context ◽  
Aggregate Network ◽  
Traffic Incident Management

One of the major challenges in a transportation network management program is responding to traffic incidents such as traffic crashes, disabled vehicles, spilled cargo, road debris, and so forth, at or near intersections. Intersections are vulnerable with respect to their susceptibility to incidents, therefore, it is important to assess their vulnerability to identify critical intersections for preparing traffic incident management strategies. In the present work, vulnerability of an intersection was measured in relation to the incident impact on surrounding road network using average aggregate network delay. Taking the case study of an urban arterial road network in Kolkata city, a methodology was demonstrated to assess the vulnerability of intersections using traffic microsimulation during peak and off-peak periods. A traffic microsimulation model was developed for this purpose and different incident scenarios were simulated to assess the vulnerability of various intersections. The intersections were then ranked in order of their vulnerability. Some key factors governing vulnerability of intersections were identified and an expert opinion survey was also conducted to assess the location-specific relevance of those factors for both peak and off-peak hour conditions using fuzzy analysis. Based on the analysis of expert opinion data, intersections were also ranked as per their vulnerability for comparative purposes. The rankings of intersections as obtained from traffic microsimulation and expert opinion analyses were found to be in agreement in the present context. However, traffic microsimulation as an approach is preferred over expert opinion because of its inherent strengths for vulnerability assessment and identification of critical intersections.

Improving Traffic Incident Management Using Team Cognitive Work Analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 152-173
Author(s):  
Vanessa Cattermole-Terzic ◽  
Tim Horberry
Keyword(s):  
Incident Management ◽  
Cognitive Work Analysis ◽  
Work Analysis ◽  
Traffic Incident ◽  
Cognitive Work ◽  
Study Team ◽  
Traffic Incident Management ◽  
To Come ◽  
And Performance ◽  
Senior Officers

Effective traffic incident management requires separate responder agencies, with different and sometimes competing priorities and purposes, to come together as a team. Their priorities include optimizing casualty outcomes, minimizing the disruption to the flow of traffic, and maintaining responder team safety. In this study, team Cognitive Work Analysis was used in a desktop exercise setting to analyze a complex traffic incident management exercise. The study investigated decisions made at the scene of an incident to determine system issues and system support solutions. Participants were all senior officers and decision makers in traffic incident management environments. Results indicated that team Cognitive Work Analysis was highly beneficial in determining gaps in team coordination, communication, and structures. Information regarding shared and not shared work elements between agencies highlighted novel coordination and education requirements within and between agencies, such as disparate priorities at the scene creating the risk of interoperability issues. Analyses of operational, coordination, and structural strategies offered new insights into the traffic incident management work domain and recommendations for improvements to the safety and performance of the overall traffic incident management system.

Sign in / Sign up

Export Citation Format

Share Document