Overview of traffic system simulation model

Robust calibration of macroscopic traffic simulation models using stochastic collocation

Traffic simulation is a widely used tool to analyze dynamic traffic system. In traffic simulation field, Microscopic simulation offers detailed representation of traffic system, but it is difficult to model large traffic network; Macroscopic and mesoscopic simulations can capture the dynamics of large network, but only on a low level of details. These limitations of mono-resolution traffic simulation emerge more clearly, as the development of its application. Multi-resolution traffic simulation, which uses hybrid traffic simulation model, can overcome those limitations by integrating traffic simulation models on different levels into a hybrid model, which combines advantages of all composing models. In this paper, we introduced UNIFY framework into traffic simulation and developed UNITRANS, a Multiple Representation Entity-based (MRE-based) framework, to integrate traffic simulation models on different resolution levels and maintain the consistency among their jointly-executing. A hybrid model was built using UNITRANS and a three-legged intersection was modeled with it. The results showed that UNITRANS was feasible and effective.

The paper studies multiresolution traffic flow simulation model of urban expressway. Firstly, compared with two-level hybrid model, three-level multiresolution hybrid model has been chosen. Then, multiresolution simulation framework and integration strategies are introduced. Thirdly, the paper proposes an urban expressway multiresolution traffic simulation model by asynchronous integration strategy based on Set Theory, which includes three submodels: macromodel, mesomodel, and micromodel. After that, the applicable conditions and derivation process of the three submodels are discussed in detail. In addition, in order to simulate and evaluate the multiresolution model, “simple simulation scenario” of North-South Elevated Expressway in Shanghai has been established. The simulation results showed the following.(1)Volume-density relationships of three submodels are unanimous with detector data.(2)When traffic density is high, macromodel has a high precision and smaller error and the dispersion of results is smaller. Compared with macromodel, simulation accuracies of micromodel and mesomodel are lower but errors are bigger.(3)Multiresolution model can simulate characteristics of traffic flow, capture traffic wave, and keep the consistency of traffic state transition. Finally, the results showed that the novel multiresolution model can have higher simulation accuracy and it is feasible and effective in the real traffic simulation scenario.

Microscopic traffic simulation models have been playing an important role in the evaluation of transportation engineering and planning practices for the past few decades, particularly in cases in which field implementation is difficult or expensive to conduct. To achieve high fidelity and credibility for a traffic simulation model, model calibration and validation are of utmost importance. Most calibration efforts reported in the literature have focused on the informal practice, and they have seldom proposed a systematic procedure or guideline for the calibration and validation of simulation models. This paper proposes a procedure for microscopic simulation model calibration. The validity of the proposed procedure was demonstrated by use of a case study of an actuated signalized intersection by using a widely used microscopic traffic simulation model, Verkehr in Staedten Simulation (VISSIM). The simulation results were compared with multiple days of field data to determine the performance of the calibrate...

Microscopic traffic simulation models offer an effective way to analyze and assess different transportation systems thanks to their efficiency and reliability. As traffic management issues become more prevalent, notably in urban areas, simulation tools enable a significant opportunity to replicate real-world conditions before implementation. Therefore, the calibration of traffic simulation models plays a substantial role in obtaining accurate and confidential results. Nowadays, urban regions are facing the challenge of restricted space for developing traffic solutions. As a consequence of environmental restrictions, the use of mini-roundabouts rather than larger roundabouts is increasing. Based on the given literature review, it is seen that not much attention was given to the complex modeling and calibration of microsimulation models of mini-roundabouts and unsignalized intersections. The objective of this study is to offer the calibration of microscopic traffic simulation of urban road network, including closely located mini-roundabouts and unsignalized intersection. To this end, an open-source tool called SUMO (Simulation of Urban Mobility) was utilized as a simulation environment in this study. The necessary data for developing a microsimulation model in SUMO was gathered using a videography technique. The traffic count data and speed were considered performance measures between field observations and simulation outputs. The routeSampler tool of SUMO, which has recently emerged in the literature, was used to match traffic count data and the corresponding time interval for traffic volume data calibration. The calibration of car-following model parameters using a trial-and-error approach was employed based on mean absolute percent error (MAPE) between simulated speeds and field-measured speeds. According to the findings of the study, the simulation model fulfilled the calibration aims of the FHWA guideline and is suitable for further research.

Following the principles of agent-oriented analysis and design, the urban traffic micro simulation system was divided into several modules and a micro simulation framework based on multi-agent was obtained on the basis of requirement analysis. The paper discuss agent-oriented traffic micro simulation modeling process, beginning with traffic flow generation model, car-following model, it gives design scheme of agents in the system. Besides, the paper gives simulation systempsilas infrastructure and simulation flow. Thus a reusable and flexible framework of urban traffic micro simulation system was achieved.

The traffic congestion in a city is one of the most important problems that must be taken into account in the smart city. Many cities suffer from the serious traffic congestion as the city population and the number of vehicles increase. To solve the traffic problem, reinforcement learning based research works have been studied for training models for traffic signal control agents and have shown their performance through various traffic simulation. The reason is that it is significantly difficult to acquire traffic data directly from the real-world environments. To effectively model reinforcement learning-based traffic simulations, in this paper, we study a method for integrating deep reinforcement learning into traffic simulation modeling.

The paper emphasizes use of mathematical software for stimulating interests in students of engineering to conduct inquiry into development and understanding of traffic simulation models. Mathematical provides a computer-based tool for students to learn the concepts of traffic simulation and visualize characteristics of traffic flow. Mathematica also provides an integrated and easy to use environment for developing and modifying traffic simulation models and observe different features of traffic flow in varying levels of sophistication. Use of such tools stimulates student interest and motivates them to further refine these models to conduct experiments in traffic simulation.

The two basic problems facing the Trans-Canada Highway through Rogers Pass, namely the winter problem of adequate vehicle storage areas during avalanche control and the summer problem of maintaining an acceptable level of service by ensuring adequate passing opportunities, may be linked through a common denominator — passing lanes. This paper presents the findings of a recently completed study of the Trans-Canada Highway through Mount Revelstoke and Glacier National Park. The study method is based on the fact that traffic flow characteristics, highway conditions, and operational requirements vary considerably from season to season. Thus, the analysis was broken into two parts, namely a separate analysis of winter and summer conditions. A traffic simulation model was used to determine those locations that could serve as potential sites for passing lanes during summer. The traffic simulation model developed for the passing lane analysis utilized files that describe road geometry, summer traffic flow and composition, and vehicle performance. A separate simulation model was developed to determine vehicle storage requirements of ponding areas during avalanche control. The model developed for winter traffic characteristics also provided the basis for a flexible traffic management strategy. Cross-section elements were developed to accommodate an auxiliary lane to be used as a passing lane in summer and as a parking lane to increase the capacity of ponding areas during avalanche control in winter. Design requirements called for triple stacking of vehicles in ponding areas during avalanche control. To accommodate design year traffic volumes at an acceptable level of service during the summer months, 12 passing lanes totalling 23 km in length were recommended. Six ponding areas, totalling 4 km in length, are coincident with four of the passing lane locations. The paper concludes with a general discussion on the benefits of linking traffic simulation with geometric design to demonstrate how the design life of rural two-lane highways can be extended by the use of low-cost operational improvements such as passing lanes. Key words: highway planning and engineering, two-lane highways traffic management during avalanche stabilization, passing lanes, cross-section elements, Trans-Canada Highway.

This paper describes how traffic simulation models in metro lines are widely used in predictive control algorithms for traffic regulation and robustness analysis of timetables. The simulation results are highly dependent on the uncertainty modeling. The two main parameters in the simulation models are running times and dwell times. In lines operated with Automatic Train Operation (ATO) systems, running times are more deterministic than random (consequence of control actions), while dwell times show a higher stochastic behavior due to the influence of passengers and drivers. Typically, simulation models do not include a realistic modeling of dwell time uncertainty, and the confidence on results is affected. This paper focused on the stochastic component of dwell times in order to obtain a realistic model suitable for traffic simulation of metro lines. For this purpose, several statistical studies have been developed considering peak and off-peak hours, incidences, relations with other operation variables, etc. Models have been obtained and validated using data of different days and Metro de Madrid lines.

W-SPSA in practice: Approximation of weight matrices and calibration of traffic simulation models

In Japan, auxiliary lane has been installed with the aim of correcting the lane utilization and increasing traffic capacity as a measure against traffic congestion at sag section of multi-lane motorways. The objective of this paper is to examine an effective method of installing an auxiliary overtaking lane for bottlenecks on motorways. First, a microscopic traffic flow simulation model is calibrated using observation data. Then, the simulation model is applied to study the appropriate installation method (installation location and length, etc.) of auxiliary overtaking lane as a measure against traffic congestion in section where sag is a bottleneck in capacity. As a result, auxiliary overtaking lane should be installed 400m upstream from the beginning of the vertical curve, and should be ended 0.6 to 1.0km from the end of the vertical curve, with a total length of 1.5 to 2.0km.

This paper presents a dynamic hybrid traffic simulation model and its improvement. Here, a hybrid traffic simulation model is defined as a combination of multiple traffic models with different resolutions, which are dynamically switched to each other. The proposed model couples a microscopic and a macroscopic model. In a dynamic hybrid model, the application domains of micro- and macroscopic models can be switched during the simulation to achieve overall speed-up while keeping a high resolution of the area of interest. The authors extended an existing dynamic hybrid model to be applicable to highway merging sections. The proposed model was also validated by data obtained on an actual highway.

Shadow traffic: A unified model for abnormal traffic behavior simulation

This paper presents the conceptual structure of a novel microscopic traffic flow behavior simulation model for motorcycle traffic based on a mobility force structure, called mobility force car-following model. The mobility force is defined as the interactive force of motorcycle by surrounding vehicles and environment of lane layout. The kinetic behavior of the motorcycle will be induced and constrained by the force created due to the spaces surrounding. The concept is to describe the driving behavior using a series of forces of the attraction and repulsion related to the vehicle and spaces surrounding in front of the motorcycle. The model can describe both of the lateral motion and longitudinal motion in views to the motorcycle driving feature. Through a series of calibration for the parameters of the model, the regression statistical significance and the validation of the model output using the field survey data, the results illustrated the enough accuracy of the result of model output. The model is then verified to be suitable to describe the real motorcycle driving behavior preliminarily. Keywords-car-following model; mobility force; force field; microscopic simulation; motorcycle