Traffic Simulation with MITSIMLab

Microscopic simulation models have been widely used as tools to investigate the operation of traffic systems and different intelligent transportation systems applications. The fidelity of microscopic simulation tools depends on the driving behavior models that they implement. However, current models commonly do not consider human-related factors, such as distraction. The potential for distraction while driving has increased rapidly with the availability of smartphones and other connected and infotainment devices. Thus, an understanding of the impact of distraction on driving behavior is essential to improve the realism of microscopic traffic tools and support safety and other applications that are sensitive to it. This study focuses on car-following behavior in the context of distracting activities. The parameters of the well-known GM and intelligent driver models are estimated under various distraction scenarios using data collected with an experiment conducted in a driving simulator. The estimation results show that drivers are less sensitive to their leaders while talking on the phone and especially while texting. The estimated models are implemented in a microscopic traffic simulation model. The average speed, coefficient of variation of speed, acceleration noise and acceleration and deceleration time fractions were used as measures of performance indicating traffic flow and safety implications. The simulation results show deterioration of traffic flow with texting and to some extent talking on the phone: average speeds are lower and the coefficient of variation of speeds are higher. Further experimentation with varying fractions of texting drivers showed similar trends.

Aiming at the problems of heavy workload of basic data collection, complicated manual parameters calibration and inaccurate calibration in the traditional microscopic traffic simulation model parameter calibration, an adaptive microscopic traffic simulation model parameter calibration method based on floating car data is proposed. First, the basic data of the simulation road network were obtained by using the floating car technology. Secondly, the parameters calibration process of the microscopic traffic simulation model was constructed, and the self- adaptive orthogonal genetic was used to achieve the model parameters calibration. Finally, using the actual data of the South Ring Road main line, District Changping, Beijing to simulate and verify. The results show that the proposed method in this paper can not only reduce the workload of manual calibration, but also the model parameter calibration is more accurate, which proves the feasibility and effectiveness of the method.

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

With the continuous improvement of national economic strength, the transportation field has also been developed at an unprecedented speed, and the transportation system simulation is an important technology and method in the field of transportation engineering. Establishing rele-vant models through traffic system simulation can not only improve the efficiency of urban traf-fic utilization in urban planning, but also optimize some existing traffic problems and promote the sustainable development of the traffic field. This paper first describes the specific concept of the traffic system simulation model, and discusses the development status of the traffic system simulation model from the microscopic traffic simulation model, the mesoscopic traffic simula-tion model, and the macroscopic traffic simulation model, as well as the characteristics and dif-ferences of the three types of models. Finally, it selects examples of each type of simulation model for specific analysis. The overview of the traffic system simulation model can improve the public's awareness of the traffic system simulation and help the specific development of urban traffic.

Traffic simulation is an effective tool for urban planners, traffic engineers, and researchers to study traffic. In particular, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, has demonstrated its importance in analyzing and managing transportation systems. However, integrating data from various sources, generating traffic scenarios, and importing information into traffic simulators to conduct microscopic simulations have always been a challenge. This paper presents a solution to overcome this challenge: RealTwin, a comprehensive tool for automated scenario generation for microscopic traffic simulation. Following a streamlined scenario generation and calibration workflow, RealTwin effectively bridges gaps between traffic data from various sources and traffic simulators, making microscopic traffic simulation more accessible for researchers and engineers across various levels of expertise. Using RealTwin to generate a real-world traffic scenario in Simulation of Urban Mobility (SUMO), VISSIM, and AIMSUN, RealTwin’s ability is demonstrated in the construction of realistic and consistent traffic scenarios in different simulators. Furthermore, this paper introduces and illustrates RealTwin’s capability for technology (e.g., autonomous vehicle) scenario generation. This feature can contribute to more comprehensive microscopic simulations, facilitating the analysis of potential effects of various technological innovations on mobility, energy efficiency, and safety. Finally, RealTwin is used to calibrate a simulation in SUMO. The calibration module enhances RealTwin’s ability to generate consistent simulations across different platforms and more realistic simulations that reflect real-world traffic operations.

This study analyzed traffic congestion scenarios in underground roads diverging and merging sections and underground sections that run parallel to ground roads using a microscopic traffic simulation model. The appropriate ratio of the ramp inflow or outflow of traffic volume to the entry traffic volume at the starting section of the underground road network was analyzed. Furthermore, the effect of traffic operation such as adequate throughput, average traffic speed, occupancy, and volume versus capacity (V/C) ratios before the occurrence of traffic congestion in all three road networks was properly produced. To maintain a minimum level of service of all underground sections at the D–E level, the underground inflow traffic volume should be equal to approximately 70% of the 4000 pcph inflow traffic volume from an open road to the underground. The results of this study are a useful reference for establishing traffic control application standards to minimize underground traffic congestion. They also provide useful insights for underground road design.

Recently, increasing attention has been put on the use of automated vehicle control systems to reduce traffic crashes due to driver errors. Proposed systems rely on either onboard range sensors or vehicle-to-vehicle wireless communications to obtain pertinent information about surrounding vehicles and to determine appropriate acceleration or deceleration commands. Although numerous studies have used microscopic traffic simulation to study the effects that these systems might have on traffic flows, generally these studies did not consider all factors that may affect their operation. A particular element that has been ignored is delay in data acquisition. Using a microscopic traffic simulation model that was developed to simulate intelligent transportation system applications relying on the use of onboard vehicle sensors or wireless transmissions, this paper attempts to quantify the safety effects created by the use of delayed information in automated vehicle control systems. The study clearly indicates that information delay affects the operation of vehicle control systems, particularly when sensor or transmission delays result in the use of information older than a certain threshold, found in this case to be 0.5 s.

Recently, increasing attention has been put on the use of automated vehicle control systems to reduce traffic crashes due to driver errors. Proposed systems rely on either onboard range sensors or vehicle-to-vehicle wireless communications to obtain pertinent information about surrounding vehicles and to determine appropriate acceleration or deceleration commands. Although numerous studies have used microscopic traffic simulation to study the effects that these systems might have on traffic flows, generally these studies did not consider all factors that may affect their operation. A particular element that has been ignored is delay in data acquisition. Using a microscopic traffic simulation model that was developed to simulate intelligent transportation system applications relying on the use of onboard vehicle sensors or wireless transmissions, this paper attempts to quantify the safety effects created by the use of delayed information in automated vehicle control systems. The study clearly indicates that information delay affects the operation of vehicle control systems, particularly when sensor or transmission delays result in the use of information older than a certain threshold, found in this case to be 0.5 s.

Traffic congestion is increasingly becoming a severe problem in many large cities around the world. The problem is more complex in developing countries where cities are growing at a much faster rate than those in the developed world. Advanced Traffic Management Systems (ATMS) are one of the Intelligent Transport Systems (ITS) technologies that have been recommended and used as a tool to ease congestion problems in many large cities in the developing world. However, it is unknown how specific local conditions commonly observed in these cities, such as poor lane discipline and complex road user interactions, affect the performance of these systems. GETRAM (Generic Environment for Traffic Analysis and Modeling) was used in this research as a tool to develop microscopic traffic simulation models for the city of Bandung in Indonesia. The field data in this research, comprising throughputs, queue lengths and travel times, were collected during peak and off peak periods from all 90 signalised intersections connected to SCATS (Sydney Co-ordinated Adaptive Traffic System). This field data is believed to comprise one of the largest sets of “real world” data available for the development and validation of microscopic traffic simulation models. Two data sets were collected for this research: the first was used to develop and calibrate the simulation model and the second was used for validation. A number of statistical tests were used to determine the adequacy of the model in replicating traffic conditions. The results of statistical tests clearly showed that all of the calibrated and validated models reproduced field conditions with an acceptable degree of confidence. Therefore, the models were accepted as accurate and valid replications of the “real world”. The validated models were then used to evaluate the performance of SCATS which was implemented in Bandung in June 1997 as a pilot project. The results of comparative evaluation of the models under SCATS and under the Fixed Time control (without SCATS) demonstrated that SCATS did not necessarily always produce better results than the Fixed Time control. Furthermore, the performance of SCATS was strongly influenced by specific local conditions in the city. The multiple regression method was used to investigate the relationship between the traffic performance measures and significant basic variables. Based on this analysis, the main findings were: first, throughput was found to increase at intersections with higher v/c (volume to capacity) ratios. Second, throughput was found to decrease at intersections with higher numbers of phases and movements, longer widths of leg intersections, and farther distances to adjacent intersections. Third, queue length was found to increase at intersections with higher numbers of phases and movements. Based on the above findings, a number of improvements were recommended to enhance the performance of SCATS. This research also used traffic simulation to evaluate the impacts of these recommended improvements in increasing the performance of SCATS. The main findings from this evaluation were: first, restricted number of phases and movements at selected intersections substantially increased the traffic flow (78%) and decreased the queue length (by 55 to 67%) at the intersection. Second, making leg intersections wider—without physically building additional road capacity but by changing the stream with higher road hierarchy and higher v/c ratio from a two-way road into a one-way road—has a great impact on enhancing the performance of SCATS. Traffic flows were found to increase between 7 and 106%, and queue lengths were found to markedly decrease between 77 and 100% at all the suggested intersections. Third, the application of SCATS at intersections which are not closely spaced was not effective. Therefore, it is recommended that intersections which are not closely spaced remain under the Fixed Time control. The results and findings from this study provide road authorities in developing countries with an appreciation and enhanced understanding of the factors that influence the performance of traffic management systems in cities with similar characteristics to those in Bandung. These findings will also assist traffic engineers determine the best practices for the implementation of advanced traffic control systems in their cities.

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.

This study examines the calibration and validation of an AIMSUN microscopic traffic simulation model of the Western Brisbane Commuting Corridor. In particular, the study focuses on the two areas of data collection/collation and comparison of model outputs with field data. Collection of travel times for Milton Road and Coronation Drive during morning, evening and off peak conditions was performed using GPS and analyzed with the aid of the Geographic Information System Mapinfo. Achieving the ideal 90% statistical reliability in travel times for peak traffic conditions is a rigorous process, as it requires ongoing data analysis and computation of sample mean and standard deviation. Statistics on vehicle composition and vehicle attributes suitable for model input were gathered from Austroads and Australian Bureau of Statistics. Results of travel times produced from an AIMSUN simulation model of Coronation Drive under morning peak conditions show poor correspondence with recorded travel times. Model error is most pronounced for travel times heading inbound towards the Brisbane CBD, where the simulator produces a mean trip time of less than 4 minutes compared with a observed mean trip time of 13 minutes. This disparity exists because the model considers a 50/50 directional split in traffic volumes, but collected field data indicates a strong imbalance of traffic volumes with a higher portion of commuters traveling inbound under morning peak conditions. Further research into attaining updated statistics regarding traffic volumes and travel demands is therefore recommended. Results also show high error rates in modeling segments of road that are closer to driver destinations, and where lane changes and merges among vehicles are more common. Under congested conditions, parameters that describe driver behavior, or how each vehicle will move and interact in a network, have greater impact. In light of this, key areas of model calibration that will need to be reassessed in order for the traffic simulator to achieve closer correspondence with observed data are driver parameters and dynamic route selection.

The purpose of this study is to analyze the impact of lowering speed limit on an urban transportation network. A microscopic traffic simulation model, Vissim was utilized to measure the impact. Also, various traffic inputs were tested with different signal coordination scenarios to investigate the impact in different traffic conditions. It was found that during early morning hours with very light traffic, the impact of lowering speed limit was significant. During congested time periods, including level of service E and F, the travel speed reduction from lowering speed limit was not significant. As suggested in other studies, the results demonstrated that lowering the speed limit does not have a significant impact on average travel speed in congested traffic networks. Also, different signal coordination was tested. As expected, signal coordination based on the lowered speed limit performed better than the case with signal coordination based on the previous higher speed limit. The results of this study are expected to provide insights when considering lowering speed limit for existing traffic networks.

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...

Traffic simulators can capture the complex dynamics of road networks thus are widely used to understand the behavior of the traffic system and predict the effects of transportation technologies, events and new policy changes. To build a traffic simulation model that can accurately capture the real traffic conditions, the Origin-Destination (OD) matrix is needed to be fed into the simulator as an input. In general, it is difficult to acquire information about the real OD matrix of a network. In this paper, we propose a neural network model for estimating the OD matrix that excites the microscopic simulation model for complex traffic networks to reproduce real world traffic flows using only the flow rate information of a small subset of links in the traffic network, which is relatively easy to collect. An optimization method is used to generate the training dataset of the neural network. Combining the OD matrix estimation model, the training dataset generation method, and the microscopic traffic simulator, an integrated traffic simulation-prediction system is developed to predict the behavior of the transportation system. We test the proposed system on the road network of the central terminal area of the Los Angeles International Airport and demonstrate that the integrated traffic simulation-prediction system can reproduce the real world traffic flow with low relative root mean square errors especially for high volume links and can be used to simulate the behavior of real world traffic scenarios.

Effect of Information Provision around Signalized Intersection on Reduction of CO2 Emission from Vehicles