Identification of Critical Factors for Non-Recurrent Congestion Induced by Urban Freeway Crashes and Its Mitigating Strategies

Chung, Younshik

doi:10.3390/su9122331

Cited by 16 publications

(11 citation statements)

References 39 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Seven factors (crash occurrence at night, the existence of three or fewer traffic lanes in a freeway section, etc.) were identified to be statistically significant in contributing to non-recurrent congestion motived by crashes [12].…”

Section: Safety Analysis On Roadwaysmentioning

confidence: 99%

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Zhu

Zhang

et al. 2019

Sustainability

View full text Add to dashboard Cite

Crashes that occur on curved roadways are often more severe than straight road accidents. Previously, most studies focused on the associations between curved sections and roadway geometric characteristics. In this study, significant factors such as driver behavior, roadway features, vehicle factors, and environmental characteristics are identified and involved in analyzing traffic accident severity. Bayesian network analysis was conducted to deal with data, to explore the associations between variables, and to make predictions using these relationships. The results indicated that factors including point of impact, site of location, accident side of road, alcohol/drugs condition, etc., are relatively critical in crashes on horizontal curves. Accident severity increases when crashes occur on bridges. The sensitivity of accident severity to vehicle use, traffic control, point of impact, and alcohol/drugs condition is relatively high. Moreover, a combination of negative factors will aggravate accident severities. The results also proposed some suggestions regarding the design of vehicles, as well as the construction and improvement of curved roadways.

show abstract

Section: Safety Analysis On Roadwaysmentioning

confidence: 99%

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Zhu

Zhang

et al. 2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…The research on the temporal and spatial impact propagation of accidents can further grasp the dynamic evolution process of accidents and help to predict the potential degrees of congestion caused by accidents. Researchers mostly have used the deterministic queuing diagram and the motion wave (shock wave) theory to analyze the influence of accidents on the surrounding road network and the principle of accidents from the perspective of time and space [15][16][17][18]. Moskowitz and Newman first proposed a deterministic queuing graph method to study the impact of the downstream capacity of bottleneck sections, that is, to estimate the cumulative total delay value of vehicles from the queuing graph, but it is difficult to reflect the repeated congestion after the accident [19]; Lawson et al proposed an improved queuing graph method to measure the spatiotemporal impact of bottlenecks, but there are still limitations in practical applications, especially when capacity changes occur many times [20].…”

Section: Literature Review 21 Propagation Mechanism Of Accidents Impactmentioning

confidence: 99%

Ellipse-Like Radiation Range Grading Method of Traffic Accident Influence on Mountain Highways

Wang

Long

et al. 2022

Sustainability

View full text Add to dashboard Cite

To improve the efficiency of accident treatment on mountain highways and reduce the degree of disruption from traffic accidents, the grading method of the ellipse-like radiation range of traffic accident impact is proposed. First, according to the propagation law of traffic accidents, the general function of mountain highways affected by traffic accidents was constructed based on the Gaussian plume model. Then, based on the gravity field theory, the influence of the accident source point on the accident road was analyzed in the aftermath of a supposed accident. Additionally, considering the cascading failure of the road network, the influence of the accident-intersecting roads was demarcated by the cascading failure load propagation function. Based on this analysis, the ellipse-like radiation range models of traffic accidents on the accident road and the intersecting roads were proposed, respectively. Next, the adjustment parameter was further introduced to incorporate the different levels of influence of traffic accidents on the surrounding road network into the model, and the grading impacts of the accident on the potentially utilized opposite lane were discussed. Finally, according to the queuing theory model, simulation design, and portability analysis, the accuracy of the ellipse-like radiation range grading model was verified. The research results show that, compared with queuing theory and simulation results, the error of the grading model of the ellipse-like radiation range affected by traffic accidents was within a reasonable range; that is, the model can reasonably quantify the difference of traffic accident propagation on the accident road and the intersecting roads. Moreover, the heterogeneity of traffic accident propagation was verified by taking the non-occupied opposite lanes as an example. The grading method of influence radiation range utilized for traffic accidents on mountain highways can quickly provide corresponding auxiliary decision support for accident rescue within varying influence ranges.

show abstract

“…At extant traffic condition (congestion) can be classified as either recurrent or non-recurrent. A definition of non-recurrent congestion is as follows; delay caused by an incident, a work zone, adverse weather, or other non-repetitive event [12,[19][20][21][22][23][24][25]. Chung [21] defines non-recurrent congestion as the extra delay caused by incidents compared with the annual average section travel speed.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Dynamic thresholds overcome some of these limitations [23,24,29,30]. Chou and Miler-Hooks [29] created a "simulation-based secondary incident filtering" method (SPSIF).…”

Section: Literature Reviewmentioning

confidence: 99%

Crash Classification by Congestion Type for Highways

Song

Kim²,

Williams

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

Effective management of highway networks requires a thorough understanding of the conditions under which vehicular crashes occur. Such an understanding can and should inform related operational and resource allocation decisions. This paper presents an easily implementable methodology that can classify all reported crashes in terms of the operational conditions under which each crash occurred. The classification methodology uses link-based speed data. Unlike previous secondary collision identification schemes, it neither requires an a priori identification of the precipitating incident nor definition of the precipitating incident’s impact area. To accomplish this objective, the methodology makes use of a novel scheme for distinguishing between recurrent and non-recurrent congestion. A 500-crash case study was performed using a 274 km section of the I-40 in North Carolina. Twelve percent of the case study crashes were classified as occurring in non-recurrent congestion. Thirty-seven percent of the crashes in non-recurrent congestion classified were identified within unreported primary incidents or crashes influence area. The remainder was classified as primary crashes occurring in either uncongested conditions (84%) or recurrent congestion (4%). The methodology can be implemented in any advanced traffic management system for which crash time and link location are available along with corresponding archived link speed data are available.

show abstract

Identification of Critical Factors for Non-Recurrent Congestion Induced by Urban Freeway Crashes and Its Mitigating Strategies

Cited by 16 publications

References 39 publications

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Ellipse-Like Radiation Range Grading Method of Traffic Accident Influence on Mountain Highways

Crash Classification by Congestion Type for Highways

Contact Info

Product

Resources

About