The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation

Wang, Junhua; Kong, Yumeng; Fu, Ting; Stipancic, Joshua

doi:10.1371/journal.pone.0184564

Cited by 15 publications

(15 citation statements)

References 31 publications

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“…The VISSIM simulation software has been applied in the field of traffic simulation for more than 40 years [ 63 ]. Some achievements have been made in the research on some key parameters in traffic flow [ 64 ], including the car following model [ 65 , 66 ], driving behavior model [ 39 ], lane change model [ 67 ] and U-turn model [ 68 ]. The accuracy of VISSIM in traffic flow simulation is widely recognized [ 18 , 69 ].…”

Section: Problem Statement and Design Schemesmentioning

confidence: 99%

Evaluating Signalization and Channelization Selections at Intersections Based on an Entropy Method

Shao

Claudel

2019

Entropy

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Direct left turns (DLTs) could cause traffic slowdown, delay, stops, and even accidents on intersections, especially on no-median roads. Channelization and signalization can significantly diminish negative impact of DLTs. In China, a total of 56 large and medium-sized cities, including 17 provincial capitals, have adopted vehicle restriction policies due to traffic congestion, vehicle energy conservation and emission reduction, which cause travel inconvenience for citizens. This paper mainly studies signalization and channelization selections at intersections based on an entropy method. Based on the commonly used three evaluation indexes, the number of vehicles, CO emissions and fuel consumption have been added. The entropy evaluation method (EEM) method is innovatively used to objectively calculate the weight of the six indexes, which carry out the optimal traffic volume combinations for intersections of present situation, channelization and signalization. A VISSIM simulation is also used to evaluate the operating status of three conditions. The results show that EEM could help enormously in choosing different methods at a certain intersection. With the EEM, six indexes decrease by 20–70% at most.

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Section: Problem Statement and Design Schemesmentioning

confidence: 99%

Evaluating Signalization and Channelization Selections at Intersections Based on an Entropy Method

Shao

Claudel

2019

Entropy

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“…To address the limitations of SMoS mentioned above, we propose a new SMoS named RCRI, which considers the crash probability and crash severity at the same time, to quantify the risk of rear-end crash. According to the changes in the speed and distance of the LV and the FV before the crash, the process of rear-end crash can be divided into four categories, as shown in Figure 4 [35,36].…”

Section: Rear-end Crash Risk Index (Rcri)mentioning

confidence: 99%

Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure

Shangguan

Wang

et al. 2021

Journal of Advanced Transportation

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Traditional surrogate measures of safety (SMoS) cannot fully consider the crash mechanism or fail to reflect the crash probability and crash severity at the same time. In addition, driving risks are constantly changing with driver’s personal driving characteristics and environmental factors. Considering the heterogeneity of drivers, to study the impact of behavioral characteristics and environmental characteristics on the rear-end crash risk is essential to ensure driving safety. In this study, 16,905 car-following events were identified and extracted from Shanghai Naturalistic Driving Study (SH-NDS). A new SMoS, named rear-end crash risk index (RCRI), was then proposed to quantify rear-end crash risk. Based on this measure, a risk comparative analysis was conducted to investigate the impact of factors from different facets in terms of weather, temporal variables, and traffic conditions. Then, a mixed-effects linear regression model was applied to clarify the relationship between rear-end crash risk and its influencing factors. Results show that RCRI can reflect the dynamic changes of rear-end crash risk and can be applied to any car-following scenarios. The comparative analysis indicates that high traffic density, workdays, and morning peaks lead to higher risks. Moreover, results from the mixed-effects linear regression model suggest that driving characteristics, traffic density, day-of-week (workday vs. holiday), and time-of-day (peak hours vs. off-peak hours) had significant effects on driving risks. This study provides a new surrogate safety measure that can better identify rear-end crash risks in a more reliable way and can be applied to real-time crash risk prediction in driver assistance systems. In addition, the results of this study can be used to provide a theoretical basis for the formulation of traffic management strategies to improve driving safety.

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“…The VISSIM simulation software has been applied in the field of traffic simulation for more than 40 years [41]. Some achievements have been made in the research on some key parameters in traffic flow [42], including car-following model [43, 44], driving behavior model [45, 46], lane change model [46] and U-turn model [47]. The accuracy of VISSIM in traffic flow simulations is recognized [30, 48].…”

Section: Model Developmentmentioning

confidence: 99%

Evaluating the sustainable traffic flow operational features of an exclusive spur dike U-turn lane design

Shao

Han

et al. 2019

PLoS ONE

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The traditional U-turn design has significantly improved traffic operations for relieving traffic congestion. However, the U-turn diversion and merge segments still cause traffic conflicts and delays. In this paper, an exclusive spur dike U-turn lane (ESUL) is proposed with the aim of addressing the disadvantages of the traditional U-turn design. ESUL provides a separate U-turn lane to diverge, decelerate, U-turn, accelerate and merge without interacting with through traffic. The effectiveness of ESUL is demonstrated through a field data investigation, simulation and analysis with VISSIM software. The proposed design is evaluated in terms of three parameters: travel time, delay and number of stops. Compared to the traditional U-turn design, ESUL can reduce travel time by 29.15%, delay by 66.70% and the number of stops by 100% at most. The results showed that ESUL has better performance than the traditional U-turn design and could be implemented to reduce traffic congestion and the potential hazards caused by U-turn maneuvers.

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The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation

Cited by 15 publications

References 31 publications

Evaluating Signalization and Channelization Selections at Intersections Based on an Entropy Method

Evaluating Signalization and Channelization Selections at Intersections Based on an Entropy Method

Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure

Evaluating the sustainable traffic flow operational features of an exclusive spur dike U-turn lane design

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