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Using VISSIM simulation model and Surrogate Safety Assessment Model for estimating field measured traffic conflicts at freeway merge areas

机译:使用VISSIM仿真模型和代理安全评估模型估算高速公路合并区的实测交通冲突

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摘要

A procedure was developed for using Surrogate Safety Assessment Model (SSAM) and VISSIM for safety assessment at freeway merge areas. The simulated conflicts generated by the VISSIM simulation models and identified by the SSAM approach to those measured in the field using traditional traffic conflicts techniques. Of particular interest was to identify if the consistency between the simulated and the field-measured traffic conflicts could be improved by calibrating the VISSIM simulation models and adjusting the threshold values in SSAM. A two-stage procedure was proposed to calibrate and validate the VISSIM simulation models. The transferability of the calibrated simulation models was also tested. It was found that the two-stage calibration procedure reduced the mean absolute prevent error (MAPE) for total conflicts from 78.1 to 33.4%. More specifically, the MAPE value was reduced from 76.6 to 33.5% for the rear-end conflicts, and from 79.5 to 35.8% for the lane-change conflicts. Linear regression models and the Spearman rank correlation coefficient were also developed to study the relationship between the simulated and the observed conflicts. Data analysis results showed that there was a reasonable consistency between the simulated and the observed conflicts.
机译:开发了使用代理安全评估模型(SSAM)和VISSIM在高速公路合并区进行安全评估的程序。由VISSIM模拟模型生成的模拟冲突,并通过SSAM方法识别为使用传统交通冲突技术在现场测得的冲突。特别令人感兴趣的是,确定是否可以通过校准VISSIM仿真模型并调整SSAM中的阈值来提高模拟交通冲突与现场交通冲突之间的一致性。提出了一个两阶段的程序来校准和验证VISSIM仿真模型。还测试了校准模拟模型的可传递性。发现两阶段校准程序将总冲突的平均绝对预防误差(MAPE)从78.1降低到33.4%。更具体地说,对于后端冲突,MAPE值从76.6降低到33.5%,对于车道变更冲突,MAPE值从79.5降低到35.8%。还开发了线性回归模型和Spearman等级相关系数,以研究模拟冲突与观察到的冲突之间的关系。数据分析结果表明,模拟和观察到的冲突之间存在合理的一致性。

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