تجزیه و تحلیل حساسیت از CORSIM با توجه به روند شکست جریان آزاد راه در نقاط گلوگاه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|26563||2012||10 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Simulation Modelling Practice and Theory, Volume 22, March 2012, Pages 197–206
Various microscopic simulation models have been used for studying traffic operations along freeway segments. An important desirable function of these models is their ability to obtain capacity and replicate the breakdown process realistically. The objectives of this paper are to evaluate the capability of a microsimulation model, CORSIM, to replicate the process of breakdown and to perform a sensitivity analysis on driver behavior parameters. The research findings indicate that CORSIM has some strengths and some weaknesses with respect to the breakdown process. Sensitivity analysis shows the different effects of these parameters on the breakdown occurrence and provides recommendations on the application of these parameters to provide a more realistic representation of traffic operations.
Microscopic simulation models have been extensively used to replicate freeway operations. These models are typically based on algorithms modeling driver behavior. Attaining freeway capacity and replicating the freeway breakdown process in a model can be very important for obtaining realistic results when evaluating congested conditions. However, no previous research on how well existing simulation tools can replicate the breakdown process was found in the literature. This study evaluates a popular simulation model with respect to its ability to replicate the breakdown process at a freeway on-ramp, and the effect of driver behavior-related parameters on modeling the breakdown. The objectives of this paper are: • To evaluate how well CORSIM (Version 6.0) replicates freeway breakdown events at a typical bottleneck location (a freeway merge). • To perform a sensitivity analysis on driver behavior parameters of CORSIM and determine which parameters affect the breakdown process. The findings of this research provide useful guidance for calibrating and validating the process of the freeway-flow breakdown at active bottlenecks. The first section of this paper summarizes literature related to the breakdown process at bottlenecks as well CORSIM’s capabilities and driver behavior-related algorithms. The next section evaluates CORSIM in terms of its ability to replicate the breakdown process at freeway merges. Following that, the paper presents the sensitivity analysis results for five factors that affect traffic operations and breakdown at freeway merging sections. The last part of the paper provides conclusions and recommendations.
نتیجه گیری انگلیسی
The focus of this research was to evaluate CORSIM for its capability of replicating the breakdown occurrence at typical freeway bottlenecks such as the merging segments, as well as to evaluate the effect of driver behavior parameters on breakdown. Based on the analysis, CORSIM describes well the abrupt speed decrease that is associated with the beginning of congestion. However, in CORSIM all breakdowns were first detected at the downstream detector, while in the field the breakdown location varies (sometimes it is first detected upstream, and sometimes downstream of the bottleneck). The sensitivity analysis showed that all five driver behavior parameters affect the time to breakdown and the associated ramp flow; however the three flow parameters (maximum pre-breakdown flow, breakdown flow and average queue discharge flow) were relatively unaffected throughout the sensitivity analysis. As part of the sensitivity analysis, the speeds, lane changes and lane distributions were extracted upstream and downstream of the bottleneck to understand how exactly each parameter affects the merging operations and the breakdown occurrence. The following were concluded: • Increased variability in the car-following sensitivity results in delaying breakdowns and suggests that conditions actually improve (less extent of congestion, breakdowns at higher ramp flows). • Regarding the minimum separation, the sensitivity analysis showed that, traffic operations are more volatile when the minimum separation is small (i.e., smaller headways), i.e., speed drops lead to immediate breakdown events and high flow rates are sustained for a very short period of time. • An increase of the advantage threshold results in reduction in the number of lane changes and fewer opportunities for the ramp vehicles to merge. This also results in the reduction of the bottleneck capacity which causes the section to break down at a lower ramp demand. • Low multiplier for desire to make a discretionary lane change results in large by-lane speed differences that contribute to breakdowns occurring sooner. • Increased variability of the free-flow speed multiplier results in increased lane changing activity upstream of the merge and vehicle segregation by lane. This leads to fewer opportunities for the ramp vehicle to merge, therefore less turbulence and delayed breakdown events. It should be noted that the findings of this study cannot be transferred per se to other microsimulation models, since alternative models typically implement different behavioral algorithms and associated parameters (i.e., for describing lane changing and car-following activity). However, the methodology presented in this paper provides useful guidance to researchers to evaluate the ability of other microsimulation models in replicating breakdown events. In addition, the results of the sensitivity analysis can be proven useful when calibrating flow breakdowns at bottleneck locations in CORSIM, but they also highlight the importance of sensitivity analysis on model calibration, especially when exploring the capabilities of any microsimulation model with respect to a complex phenomenon such as the breakdown event. Future work should evaluate the capabilities of CORSIM to replicate breakdown in a quantitative manner. Field data should be used to evaluate the magnitude and time of speed drop as predicted by CORSIM vs. the respective speed drop observed in the field. It would also be useful to evaluate the impacts of various driver behavior-related parameters in the field and compare them to those observed in CORSIM.