Quasi-vehicle-trajectory-based real-time safety analysis for expressways

Abdel-Aty, Mohamed; Ma, Wanjing; Hu, Jia; Zhong, Hao

doi:10.1016/j.trc.2019.04.003

Cited by 42 publications

(9 citation statements)

References 32 publications

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“…These data reflect the real state of crashes pretty well. Moreover, Wang et al developed a quasi-vehicle-trajectory-based method to find crash contributing factors, presenting a possible use of real-time data [10]. Based on various methodological and analytical techniques in big data analysis, many prediction models are also obtained and applied, including multinomial logit models, latent class logit models, random parameter (mixed) logit models, ordered logit/probit models, support vector machine, and so on [11,12,13].…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

Chen

Song

2019

IJERPH

145

105

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The existing studies on drivers’ injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers’ injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

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Section: Introductionmentioning

confidence: 99%

Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

Chen

Song

2019

IJERPH

145

105

View full text Add to dashboard Cite

show abstract

“…In addition, another important factor in evaluating the MA performance of a material is the attenuation constant (α), which can be calculated through the following formula: , α = 2 π f c ( μ ″ ε ″ − μ ′ ε ′ ) + false( μ ″ ε ″ − μ ′ ε ′ false) 2 + false( μ ′ ε ″ + μ ″ ε ′ false) 2 where f and c represent the frequency and velocity of the EMW, respectively. It can be seen from the equation that the attenuation constant exhibits a positive correlation with the increase in frequency.…”

Section: Resultsmentioning

confidence: 99%

“…11,74 Figure 9b shows that the Z value of T2 is nearer to 1 than the other three samples, which indicates that the impedance matching of T2 is the best. In addition, another important factor in evaluating the MA performance of a material is the attenuation constant (α), which can be calculated through the following formula: 75,76…”

Section: Resultsmentioning

confidence: 99%

Large Microsphere Structure of a Co/C Composite Derived from Co-MOF with Excellent Wideband Electromagnetic Microwave Absorption Performance

Zhang,

Sun,

Cai

et al. 2023

ACS Appl. Mater. Interfaces

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“…In addition, the length of the experiment field should not be too long or too short; if it is too long it will increase the experiment cost, while, if it is too short, there will be insufficient trajectory observation length. Wang et al ( 21 ) found that some variables in the 0–1 min interval before crashes have a positive impact on real-time safety analysis and have the potential to be applied to improve the safety of CVs and autonomous vehicles. Therefore, continuous vehicle trajectories at least 1 min in duration need to be collected.…”

Section: Experiments Descriptionmentioning

confidence: 99%

MAGIC Dataset: Multiple Conditions Unmanned Aerial Vehicle Group-Based High-Fidelity Comprehensive Vehicle Trajectory Dataset

Zhong

Wang

et al. 2022

Transportation Research Record: Journal of the Transportation R

Self Cite

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High-fidelity vehicle trajectory data contain rich spatiotemporal characteristics and play a major role in the field of transportation research, for example, driving behavior models, traffic flow models, traffic state identification, and driver assistance strategies. There are some coverage issues with the existing datasets recorded in continuous traffic flow facilities, which may limit the further development of research on the safety and efficiency of continuous traffic flow facilities. For example, the observation areas of these datasets lack different traffic states and section types. Therefore, it is necessary to collect a new trajectory dataset. This paper proposes a detailed plan for aerial photography by unmanned aerial vehicle (UAV) group. An experiment was conducted from 7:40 to 10:40 a.m. on a section of the Shanghai Inner Ring, Shanghai, China, with a total length of 4,000 m in both directions including a large radius curve and six ramps. The trajectory dataset, named MAGIC, is extracted and compared with NGSIM US-101 and HIGH-SIM from the aspects of experiment field, traffic states, and so on. Further, to illustrate the advantages of the MAGIC dataset incorporating different traffic states and section types, the MAGIC dataset is evaluated from the three aspects of traffic congestion state, fundamental diagram, and traffic conflict. Overall, there are significant differences in macroscopic traffic flow and traffic safety characteristics between road sections with different section types or traffic states. Therefore, the proposed method presents some unique advantages and may perform effectively in many fields.

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Quasi-vehicle-trajectory-based real-time safety analysis for expressways

Cited by 42 publications

References 32 publications

Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

Large Microsphere Structure of a Co/C Composite Derived from Co-MOF with Excellent Wideband Electromagnetic Microwave Absorption Performance

MAGIC Dataset: Multiple Conditions Unmanned Aerial Vehicle Group-Based High-Fidelity Comprehensive Vehicle Trajectory Dataset

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