Automatic calibration of microscopic simulation models for the analysis of urban intersections

2017 ◽  
pp. 769-776
Author(s):  
Sara Oliveira ◽  
Luís Vasconcelos ◽  
Ana Bastos Silva
Author(s):  
Iisakki Kosonen ◽  

The microscopic simulation is getting increasingly common in traffic planning and research because of the detailed analysis it can provide. The drawback of this development is that the calibration and validation of such a detailed simulation model can be very tedious. This paper summarizes the research on automatic calibration of a high-fidelity micro-simulation (HUTSIM) at the Helsinki University of Technology (TKK). In this research we used ramp operation as the case study. The automatic calibration of a detailed model requires a systematic approach. A key issue is the error-function, which provides a numeric value to the distance between simulated and measured results. Here we define the distance as combination of three distributions namely the speed distribution, gap distribution and lane distribution. We developed an automated environment that handles all the necessary operations. The system organizes the files, executes the simulations, evaluates the error and generates new parameter combinations. For searching of the parameter space we used a genetic algorithm (GA). The overall results of the research were good demonstrating the potential of using automatic processes in both calibration and validation of simulation models.


2015 ◽  
Vol 2534 (1) ◽  
pp. 101-108 ◽  
Author(s):  
Mingjun Liao ◽  
Gang Liu

The nonpayment area at urban transit stations in China usually becomes extremely crowded during peak hours because many passengers queue to buy tickets and pass through the fare gates. How to evaluate the performance of these activities is a critical issue for the design and management of the nonpayment area. This study used microscopic simulation models to investigate passenger behavior in the nonpayment area. The study developed a queue choice model, a passenger movement model, and a path navigation model. Some new ideas were involved. First, the study introduced the concepts of dynamic queue length and dynamic distance between the current passenger and alternative queues into the queue choice model. Second, a new factor, called direction of goal, was proposed to navigate a passenger through the dynamic end of a queue or other goals. This factor was used to construct the transition probability function of a cellular automata model. Finally, the proposed models were calibrated and verified on the basis of a field survey and sensitivity analysis. The results show that the proposed models can capture passenger behaviors in the nonpayment area and perform well for queue estimation.


Author(s):  
Serge P. Hoogendoorn ◽  
Hein Botma

A simple analysis to derive Branston’s generalized queueing model for (time-) headway distributions is presented. It is assumed that the total headway is the sum of two independent random variables: the empty zone and the free-flowing headway. The parameters of the model can be used to examine various characteristics of both the road (e.g., capacity) and driver-vehicle combinations (e.g., following behavior). Furthermore, the model can be applied to vehicle generation in microscopic simulation models and to safety analysis. To estimate the different parameters in the model, a new estimation method is proposed. This method, which was developed on the basis of Fourier-series analysis, was successfully applied to measurements collected on two-lane rural roads. The method was found to be both computationally less demanding and more robust than traditional parameter techniques procedures, such as maximum likelihood. In addition, the method provides more accurate results. Parameters in the model were examined with the developed estimation method. Estimates of these parameters at a specific period and a specific measurement location were to some extent transferable to other periods and locations. Application of the method to road capacity estimation is discussed.


Author(s):  
Meng Xie ◽  
Michael Winsor ◽  
Tao Ma ◽  
Andreas Rau ◽  
Fritz Busch ◽  
...  

This paper aims to evaluate the sensitivity of the proposed cooperative dynamic bus lane system with microscopic traffic simulation models. The system creates a flexible bus priority lane that is only activated on demand at an appropriate time with advanced information and communication technologies, which can maximize the use of road space. A decentralized multi-lane cooperative algorithm is developed and implemented in a microscopic simulation environment to coordinate lane changing, gap acceptance, and car-following driving behavior for the connected vehicles (CVs) on the bus lane and the adjacent lanes. The key parameters for the sensitivity study include the penetration rate and communication range of CVs, considering the transition period and gradual uptake of CVs. Multiple scenarios are developed and compared to analyze the impact of key parameters on the system’s performance, such as total saved travel time of all passengers and travel time variation among buses and private vehicles. The microscopic simulation models showed that the cooperative dynamic bus lane system is significantly sensitive to the variations of the penetration rate and the communication range in a congested traffic state. With a CV system and a communication range of 150 m, buses obtain maximum benefits with minimal impacts on private vehicles in the study simulation. The safety concerns induced by cooperative driving behavior are also discussed in this paper.


Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.


1998 ◽  
Vol 1644 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Yunlong Zhang ◽  
Larry E. Owen ◽  
James E. Clark

The purpose of this paper is to explore various traffic modeling aspects and theories that may overcome some of the limitations in existing microscopic simulation models. A multiregime microscopic traffic simulation approach has been formulated featuring realistic and comprehensive carfollowing and lane-changing logic. A prototype implementation of the multiregime approach was developed in C++ and extensively tested. The multiregime simulation results demonstrate the efficiency and validity of the proposed models for a broad range of traffic scenarios. The test and validation results indicate that the model and program outperformed traditional methods and other existing traffic simulation programs. The validity and efficiency of the model is attributed to the fact that the regimes were added to the model incrementally to reflect increasing agreement with real-world traffic flow. The techniques and corresponding models will be used to improve existing microscopic traffic simulation models and programs.


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