Development and Validation of a Vehicle Dynamics Integrated Traffic Simulation Environment Assessing Surrogate Safety

So, Jaehyun; Park, Byungkyu; Wolfe, Sage M.; Dedes, G.

doi:10.1061/(asce)cp.1943-5487.0000403

Cited by 21 publications

(15 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the neural network still does not achieve 100% of prediction accuracy, this is a very acceptable and practical methodology as an alternative to the VISSIM-CarSim-SSAM integrated traffic simulation because it reduced a significant amount of computation time. This is because the VISSIM-CarSim-SSAM integrated simulation approach was demonstrated to be a more effective and valid way in representing the surrogate safety than the traditional traffic simulator only (i.e., VISSIM) approach in the previous study [79]. In addition, the effectiveness of the neural network approach in terms of the representativeness of surrogate safety was demonstrated through the correlation analysis and the t-test.…”

Section: Discussionmentioning

confidence: 95%

“…The performance of the trained neural network can be accepted when the correlation coefficient is higher than that of the VISSIM only simulation approach. Note that the traffic conflicts obtained from the VISSIM‐CarSim‐SSAM integrated simulation indicated a 0.72 correlation strength with the confidence interval between 0.71 and 0.73, whereas the traffic conflicts obtained from the VISSIM only simulation showed a 0.61 correlation strength with the confidence interval between 0.60 and 0.62 in the previous study . spss Statistics version 20.0 was used to estimate the Pearson product moment correlation coefficient and p ‐value .…”

Section: Correlation Analysis With the Predicted Conflictsmentioning

confidence: 90%

“…Two freeway corridors (i.e., Interstate 495 and State Road 267) in the Tysons Corner area, located in Fairfax, Virginia, were selected as shown in Figure and constructed in a microscopic traffic simulation model, VISSIM. This VISSIM network was calibrated by matching the traffic counts by links and used to generate vehicle trajectories that are used for the modeling input and output. The Interstate Highway 495 is approximately 2.7 miles long, and the State Road 267 is about 3.3 miles long.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Classification modeling approach for vehicle dynamics model‐integrated traffic simulation assessing surrogate safety

Park

Yun

2014

J of Advced Transportation

View full text Add to dashboard Cite

SUMMARYTo assess safety impacts of untried traffic control strategies, an earlier study developed a vehicle dynamics model-integrated (i.e., VISSIM-CarSim-SSAM) simulation approach and evaluated its performance using surrogate safety measures. Although the study found that the integrated simulation approach was a superior alternative to existing approaches in assessing surrogate safety, the computation time required for the implementation of the integrated simulation approach prevents it from using it in practice. Thus, this study developed and evaluated two types of models that could replace the integrated simulation approach with much faster computation time, feasible for real-time implementation. The two models are as follows: (i) a statistical model (i.e., logit model) and (ii) a nonparametric approach (i.e., artificial neural network). The logit model and the neural network model were developed and trained on the basis of three simulation data sets obtained from the VISSIM-CarSim-SSAM integrated simulation approach, and their performances were compared in terms of the prediction accuracy. These two models were evaluated using six new simulation data sets. The results indicated that the neural network approach showing 97.7% prediction accuracy was superior to the logit model with 85.9% prediction accuracy. In addition, the correlation analysis results between the traffic conflicts obtained from the neural network approach and the actual traffic crash data collected in the field indicated a statistically significant relationship (i.e., 0.68 correlation coefficient) between them. This correlation strength is higher than that of the VISSIM only (i.e., the state of practice) simulation approach. The study results indicated that the neural network approach is not only a time-efficient way to implementing the VISSIM-CarSim-SSAM integrated simulation but also a superior alternative in assessing surrogate safety.

show abstract

Section: Discussionmentioning

confidence: 95%

Section: Correlation Analysis With the Predicted Conflictsmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Classification modeling approach for vehicle dynamics model‐integrated traffic simulation assessing surrogate safety

Park

Yun

2014

J of Advced Transportation

View full text Add to dashboard Cite

show abstract

“…(Gettman et al, 2008;Pu and Joshi, 2008). This software, in conjunction with a microsimulation model, has been used in a number of safety studies (Gettman et al, 2008;So et al, 2015). Note that most of the SSAM models are focused on obtaining surrogate safety measures based on the individual vehicle trajectories, and their associated conflicts, output form the model.…”

Section: Safety Treatmentsmentioning

confidence: 99%

“…Note that most of the SSAM models are focused on obtaining surrogate safety measures based on the individual vehicle trajectories, and their associated conflicts, output form the model. Because the model developers never developed their models to have an accurate conflict resolution process some authors have questioned the validity of this approach (So et al, 2015). In addition, because the safety counter-measures in this paper seek to eliminate, or at least reduce, the most serious conflicts it was decided to 1) focus on an approach that explicitly models driver behavior with respect to the traffic signs and 2) uses MOEs that are directly related to the countermeasures that are analyzed.…”

Section: Safety Treatmentsmentioning

confidence: 99%

Development of a statistically-based methodology for analyzing automatic safety treatments at isolated high-speed signalized intersections

Wojtal

Rilett

2017

AoT

View full text Add to dashboard Cite

Crashes at isolated rural intersections, particularly those involving vehicles traveling perpendicularly to each other, are especially dangerous due to the high speeds involved. Consequently, transportation agencies are interested in reducing the occurrence of this crash type. Many engineering treatments exist to improve safety at isolated, high-speed, signalized intersections. Intuitively, it is critical to know which safety treatments are the most effective for a given set of selection criteria at a particular intersection. Without a well-defined decision making methodology, it is difficult to decide which safety countermeasure, or set of countermeasures, is the best option. Additionally, because of the large number of possible intersection configurations, traffic volumes, and vehicle types, it would be impossible to develop a set of guidelines that could be applied to all signalized intersections. Therefore, a methodology was developed in in this paper whereby common countermeasures could be modeled and analyzed prior to being implemented in the field. Due to the dynamic and stochastic nature of the problem, the choice was made to employ microsimulation tools, such as VISSIM, to analyze the studied countermeasures. A calibrated and validated microsimulation model of a signalized intersection was used to model two common safety countermeasures. The methodology was demonstrated on a test site located just outside of Lincoln, Nebraska. The model was calibrated to the distribution of observed speeds collected at the test site. It was concluded that the methodology could be used for the preliminary analysis of safety treatments based on select safety and operational measures of effectiveness.

show abstract

Safety Evaluation at Urban Intersections Using Surrogate Measures

Tigari¹,

Puwar

Rao

et al. 2020

Recent Advances in Traffic Engineering

View full text Add to dashboard Cite

Development and Validation of a Vehicle Dynamics Integrated Traffic Simulation Environment Assessing Surrogate Safety

Cited by 21 publications

References 26 publications

Classification modeling approach for vehicle dynamics model‐integrated traffic simulation assessing surrogate safety

Classification modeling approach for vehicle dynamics model‐integrated traffic simulation assessing surrogate safety

Development of a statistically-based methodology for analyzing automatic safety treatments at isolated high-speed signalized intersections

Safety Evaluation at Urban Intersections Using Surrogate Measures

Contact Info

Product

Resources

About