Traffic Simulation Model Research Articles

Calibration of Vissim for Bus Rapid Transit Systems in Beijing Using GPS Data

Bus Rapid Transit systems have grown in popularity in recent years. With the rapid development of computer technologies, using microscopic simulation models to study various strategies on planning, implementation and operation of BRT systems has become a hot research area in the field of public transportation. To make the simulation models accurately replicate field traffic conditions, model calibration is crucial. This paper presents an approach for calibrating the microscopic traffic simulation model VISSIM using GPS data for application to Beijing BRT systems. The Sum of Squared Error (SSE) of the collected versus simulated vehicle speeds at the cross-sections along the test route is specified as the evaluation index. A Genetic Algorithm is adopted as the optimization tool to minimize the SSE. Taking the Beijing North-South Central Axis BRT Corridor as a case study, it shows that the proposed approach is a practical and effective method for the model calibration.

Comparing the Observable Response Times of ACC and CACC Systems

This paper analyzes trajectory observations from vehicles driving in platoon formation and they are equipped with Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) systems; aiming to quantify response delays. When a preceding vehicle induces a perturbation, the delay until the reaction of the following vehicle, often quoted as observable response time, can have negative implication to the traffic flow and other factors such as energy consumption, stability and safety. Quantifying such delays can help towards more realistic traffic simulation modeling. The analysis is performed based on empirical observations from three well-known experimental campaigns in the literature with data from ACC-driven and CACC-driven vehicle platoons. Three state-of-the-art techniques were implemented to provide quantitative results for the observed response times. The benefits and downsides of each technique are discussed as well. The results show that ACC systems do not exhibit a significant improvement compared to human drivers, yet, it can be concluded that the additional vehicle-to-vehicle communication incorporated in the CACC systems allows for a substantially higher traffic flow and possibly other benefits.

Evaluating zone of influence for traffic-related emissions generated near bus stops: a case study in Nanjing, China

ABSTRACT The estimation of zone of influence (ZoI) at bus stops is the basis for accurately modelling vehicle emissions and assessing the exposure of pedestrians to airborne toxins at emission hotspot locations. The purpose of this study was to investigate the changes in ZoIs for traffic-related emissions at different bus stops. An integrated approach coupling a traffic simulation model (VISSIM) with an emission model (MOVES) was implemented to estimate the vehicle emissions in ZoIs at bus stops for different scenarios. The results demonstrated that lane management mode and traffic conditions had a significant impact on vehicle emissions near different bus stops, and the emission factors (EFs) of pollutants were highest in the acceleration sublink. In addition, the length of the acceleration and queue sublinks mainly determined the length of the ZoIs of bus stops. Owing to the stop-and-go condition, the average contribution of CO, PM2.5, and PM10 towards the ZoI at curbside bus stop and bus bay without exclusive bus lane was significantly higher than under cruising condition. The sensitivity analysis also showed that the emission was more sensitive to acceleration than deceleration. Therefore, the emissions of the departure links for bus stops were significantly higher than those of the approach links. Commuters should reduce the long-time waiting at bus stops, wait downstream of bus stop when waiting for the bus stop, and the vehicles at the bus stop should accelerate slowly when leaving, which will all help to minimize the exposure of commuters to pollutants.

Quantum harmonic oscillator model for fine-grained expressway traffic volume simulation considering individual heterogeneity

Accurate and robust fine-grained expressway traffic volume simulation is a critical issue in intelligent transportation systems and real-time traffic-related applications. However, the fine-grained expressway traffic volumes aggregated from vehicle trajectories heavily rely on individual heterogeneity, making it challenging for modeling and accurate simulation. In order to eliminate the influence of individual heterogeneity on the modeling and simulation of the fine-grained expressway traffic volume, this paper proposes a novel method named Quantum Harmonic Oscillator Model for Fine-grained Expressway Traffic Volume Simulation (FGTVS-QHO). FGTVS-QHO adopts the wave function of the quantum harmonic oscillator model to describe the irregular evolution of the location of the vehicle. Then several optimization strategies are applied to the numerical solution of the wave function. FGTVS-QHO is validated with the expressway traffic volumes of six exits along the Nanjing-Shanghai Expressway in China. The simulation performance of FGTVS-QHO is compared with the methods of Long and Short-Term Memory (LSTM) networks and Autoregressive Integrated Moving Average (ARIMA). FGTVS-QHO shows higher simulation accuracy, less time cost, and lower parameter complexity. Especially, the average simulation accuracy of FGTVS-QHO is improved by 24.80% and 58.05% compared with the above two methods, respectively. The scale effects of FGTVS-QHO also indicate that it is adaptive to simulate the expressway traffic volume at fine time granularity. This paper provides a new potential method for fine-grained expressway traffic volume simulation with strong individual heterogeneity.

Modeling of Air Traffic Flow Using Cellular Automata

Fast simulation technology is very important to explore the consequences of air traffic management decision. Although a variety of simulation tools have been developed to make decisions for air traffic controllers, the cognitive process of air traffic controllers is not effectively integrated into these tools. This article studies a probabilistic cellular automata (CA) model for air traffic flow simulation. By introducing the safety distance parameter into the CA model, the equilibrium property of air traffic system is studiedusing the statistical physics method. The simulation results show that the data are in good agreement with the measured results.

Multiobjective Timetable Development Tool for Railway Strategic Planning in Norway

Strategic planning is critical in helping railways develop optimal programs for improving their business by making service more attractive and efficient. Preparing a strategic plan requires comparing multiple alternatives and options, each requiring time-consuming planning, evaluation, and analysis. To improve this process Jernbanedirektoratet, Norway’s Railway Directorate, began a research project to develop a state-of-the-art railway timetable generation tool that could be integrated into the agency’s existing timetable-planning process. The new tool, called Automatic Timetabler with Multiple Objectives, is designed to transform conceptual passenger and freight service requirements into working timetables, while ensuring robustness and minimizing time losses. It is designed to bridge the gap between less detailed (macroscopic) models used in timetable development and detailed (microscopic) traffic simulation models. More specifically, it is a mesoscopic model, simplifying some infrastructure elements while using more detailed representations of others (e.g., using specific track allocations in stations). In practice, the tool quickly provides planners with many feasible and good timetables using high-level timetable requirement data. This ability is very useful for strategic planning because it enables planners to quickly evaluate alternative timetable concepts. This paper describes the new timetable generator tool, its development, and the results of a case study application.

Analisis Tingkat Layanan Ruas Jalan dan Persimpangan di Kecamatan Gandus Akibat Pembangunan Jalan Tol Kayu Agung – Palembang - Betung

The construction of Musi V Bridge is part of the series of Kapal Betung Toll Road, with the toll road in and out of Social Street which is connected to Lettu Karim Kadir Street. This study aims to obtain the performance of roads and intersections in Gandus District, obtain transportation modeling of traffic movements due to KayuAgung-Palembang-Betung Toll Road interchange, obtain predictions of the performance of roads and intersections resulting from traffic simulation models and provide policy suggestions in the form of strategies and traffic engineering management techniques. Data processing used the 2014 PKJI method and simulation with Vissim program. Results of data processing show that the performance of roads and intersections in existing conditions is still able to accommodate traffic flow, indicated by the degree of saturation that meets 2014 PKJI requirements, namely (DJ ≤ 0.85) with service level C and Vissim simulation results show the largest delay and queue length located in segment 3 (M Amin Fauzi Street -Tph Sofyian Kenawas Street) which is 138.18 meters and 21.02 seconds and on Lettu Karim Kadir Street (Direction of Musi II) of 14.04 seconds and 58.96 meters. After the operation of the Musi V Bridge, there was an increase in traffic volume which resulted in decreased performance of roads and intersections. Therefore, to improve its performance, road widening is carried out. The results of 2014 PKJI analysis showed a decrease in the degree of saturation from 0.43 to 0.35, a delay from 9.02 seconds / cur to 8.22 seconds / cur and the chances of queuing from 8.50 - 20.39% to 6.04 - 15.91% on Lettu Karim Kadir Street (Musi II Direction).

Government Policy Analysis to Develop the Krian-Manyar-Gresik Toll in order to Reduce Traffic Jam using A Dynamic System Approach

Infrastructure development in an area, including the construction of toll roads, is aimed at developing a region and increasing the economy of the region. The construction of the toll road which is connected from Krian-Manyar-Gresik is carried out to facilitate traffic connecting the two cities. Traffic jams often occur at the link between the two cities. Congestion that occurs is usually caused by an increase in the volume of vehicles. Therefore, the construction of a toll road connecting the two cities is the best alternative. This research aimed to know government policies effectiveness in the construction of this toll road. The method used in this research is to use a dynamic system approach. From the results of the traffic simulation model design, it is found that the construction of toll roads is considered very influential and can be a way out of congestion problems. This is due to a decrease in the degree of saturation of congestion and although there is an increase from year to year, it is only slightly and not too significant. So the researchers suggest to continue the planned toll road construction project.

Traffic operation analysis for underground and ground roads using microscopic traffic simulation

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.

RISK ANALYSIS OF CYCLING ACCIDENTS USING A TRAFFIC DEMAND MODEL

Abstract. In Germany, accidents are collected nationwide, including also bicycle accidents. To determine accident-prone locations, it is necessary to not only look at the number of accidents but also in relation to the absolute number of cyclists traversing that location. Thus, this study exploits a collection of bicycle accidents in combination with estimated cyclist volumes on street level in Hanover (Germany). The basis for the generated bicycle volumes is the resulting origin-destination demand for bicycle mode from an agent-based traffic simulation model. A normalization of the accidents by an absolute bicycle volume allows to estimate a risk score and to compare high frequented ways with less popular minor paths in an objective manner. This method is used to show locations with comparatively high risk for cyclists. Besides highlighting these spots on a map, e.g. for city planners, the resulting risk scores can be integrated into bicycle routing to avoid those areas for future trips.

DEVELOPMENT OF LANE CHANGE MODELS THROUGH MICROSCOPIC SIMULATION UNDER MIXED TRAFFIC

The number of motor vehicles and traffic demand is growing in tandem with society's rapid economic development and the quickening process of urbanization. In India, traffic congestion has become the most serious issue. Vehicle's poor lane-changing behaviors have a significant impact on the speed of the traffic system. The lane change behavior was observed in the study with the traffic flow simulation model VISSIM. The purpose of this investigation is to estimate the number of lane changes by simulating them at different volume levels. The study also shows the capacity estimate and its relationship with the lane change. The maximum traffic flow and lane changes were calculated based on the proportions of each vehicle type in the standard car traffic flow. The maximum number of lane change models for known traffic compositions on 4-lane, 6-lane, and 8-lane divided highways has been developed. According to the results, the number of observed lane changes depends on the volume of traffic and the number of lanes provided for a particular direction of travel. The composition and vehicle types also have a significant influence on lane changes and highway capacity, which involves uncertainties in the analysis of traffic flow properties.

Impact of Lowering Speed Limit on Urban Transportation Network

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.

An Improved Charging Navigation Strategy of Electric Vehicles via Optimal Time-of-Use Pricing

Electric vehicles (EVs) have attracted worldwide attention and have been vigorously promoted by the government. However, users’ mileage anxiety and the intermittent charging load are still great challenges to the popularization of EVs. To tackle these problems, this paper proposes an improved charging navigation model, aiming at maximizing the benefits of multiple parties by setting time-of-use (TOU) price of fast charging stations (FCSs) to attract EVs to charge at off-peak hours and saving the costs of EVs with real-time navigation. It is modeled as a Stackelberg game, in which the FCSs operator and EVs are the leader and followers respectively. First, a rigorous and dedicated traffic simulation model, air conditioner energy consumption model and queuing model of EVs are established. Then, by researching the impact of prices on charging choices, an EV strategy including the selection of charging time, charging energy, charging station and routes is proposed to minimize EV’s cost. Based on EV charging response behavior, the optimal TOU pricing strategy for FCSs is formulated to maximize FCSs’ revenue. The simulation results confirm that the proposed approach is beneficial to EVs and FCSs, and can effectively reduce the peak-to-average ratio and the peak-valley difference of the power system.

Modeling pedestrian–vehicle mixed-flow in a complex evacuation scenario

Traffic simulation model has been widely used in urban traffic evacuation and pedestrian evacuation. However, few research efforts have been devoted to a complex evacuation scenario that includes vehicles and pedestrians. Even some of the research studies have focused on pedestrian–vehicle mixed-flow simulation models; they can hardly simulate the pedestrian–vehicle interaction dynamics in complex evacuation scenarios such as intersections, parking lots, and so on. This paper developed a pedestrian–vehicle mixed-flow model based on the Social Force Model (SFM), a car-following model, and a lane change model to solve this problem. Further, the vehicle–pedestrian force and Time to Conflict (TTC) model the interaction between people and vehicles. In the case study of parking lot evacuation, the model is proved to be effective in simulating the behavior of pedestrian–vehicle flow in a complex scenario.

Minimum spacing of continuous entrance and exit on the collector-distributor road of alfalfa leaf interchange

The spacing between the same side of entrance and downstream exit (continuous entrance and exit) of the interchange has not yet specified in the highway route design specification (JTG D20—2017). When the spacing is small, the interweaved traffic flow affects each other, which not only reduces the traffic capacity, but also affects the traffic safety. In this paper, the collector-distributor road is set in the main line of alfalfa leaf interchange. By analyzing the operation characteristics of vehicles in this area, we obtain the calculation model of minimum spacing of continuous entrance and exit, and determine the key parameters such as the weaving type and the vehicle speed of the weaving area according to 'China Highway Capacity Manual'. Then we calculate the length and saturation of weaving area and examine the length and service level of weaving area. Finally we propose the recommended minimum spacing of continuous entrance and exit of alfalfa leaf interchange. We use the VisSim software to build the traffic simulation model of continuous entrance and exit section, take the conflict rate as the safety evaluation index, and evaluate the simulation conflict rate of the recommended minimum spacing under different design speed combinations. The evaluation results show that the safety levels of the recommended minimum spacing of entrance and exit are safe, relatively safe or criticality safe, indicating that the recommended spacing is reasonable. The research results can provide a reference for the design of continuous entrance and exit on the collector-distributor road of alfalfa leaf interchange, and help to improve the revelent specifications and design rules. <fig fig-type="abstract-image" id="F1" orientation="portrait" position="float"><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="1000-2618-2022-39-3-305/FA80BD8A-2C47-438f-B2C4-18EB183AC195-F001.jpg"/></fig>

An improved micro model for stochastic traffic load simulation with consideration of axle load and microscopic behavior

Simulating the stochastic traffic load has been an important issue for bridge condition evaluation. This paper proposes an improved cellular automaton for stochastic traffic load simulation with consideration of axle load and microscopic interaction. The cells, neighbors, transition rules and boundary conditions in the improved model are all redefined. The cell length can be manually defined with any value. The vehicle load can be precisely simulated using axle load if the cell length is set small or using concentrated load when a large cell length is defined. Acceleration based transition rules are proposed, and different acceleration for each vehicle can be computed to more reasonably simulate the microscopic behavior. The feasibility of the proposed model is validated through comparisons on traffic flow simulation and load effect quantification with in-field weigh in motion data and other models. The results indicate that the proposed model improves the existing models both in vehicle load simulation and traffic flow simulation and can be used for stochastic traffic load simulation for bridges with any length.

A general framework for combining traffic flow models and Bayesian network for traffic parameters estimation

This work focuses on traffic parameters estimation based on trajectory data in an arterial corridor with multiple signalized intersections. We develop a general framework that can combine various traffic flow models with Bayesian Network (BN) for estimating the overall traffic parameters using partially observed vehicle trajectory data (with unknown penetration rate). The BN is formulated to establish the probabilistic relationship between the traffic arrival process, traffic states, traffic flow model parameters and observed vehicle trajectories. More specifically, given traffic arrival information (e.g., traffic arrival volume) and fundamental diagram parameters (e.g., capacity, jam density, and free flow speed), vehicle trajectories are derived or simulated based on traffic flow modelling (e.g., shockwave analysis, Cell Transmission Model (CTM), or microscopic traffic simulation model VISSIM). Here, the extracted entry time of an observed vehicle at a pre-defined location upstream of the signal and its travel time are used to establish the probabilistic relationship. On the other hand, they are also the input parameters of the model for the estimation. Then, by combining a dynamic traffic flow model with Bayesian inference, we develop a framework to establish the learning process for traffic parameters estimation, such as traffic volume and traffic flow model parameters. The proposed framework is evaluated with different traffic flow models using the NGSIM dataset of an arterial corridor with three signalized intersections. For the CTM-BN model, the mean absolute percentage error (MAPE) of the estimation is generally below 5% when the penetration rate is above 12%. Regarding the VISSIM-BN model, the MAPE of the estimation is generally below 5% when the penetration rate is above 6%. These results demonstrate the applicability of the framework even under a relatively low penetration rate, and that the fidelity of the dynamic traffic model used does influence the estimation performance.

Trajectory-based characteristic analysis and decision modeling of the lane-changing process in intertunnel weaving sections.

Existing lane-changing models generally neglect the detailed modeling of lane-changing actions and model lane-changing only as an instantaneous event. In this study, an intertunnel weaving section was taken as the background, the lane-changing duration and distance in the lane-changing process were taken as the main research objects. The detailed modeling of a lane-changing action was emphasized. Aerial videos of intertunnel weaving sections were collected, and accurate vehicle trajectory data were extracted. Basic data analysis shows that the lane-changing duration has a lognormal distribution and the lane-changing distance has a normal distribution. To analyze the difference of the lane-changing behavior characteristics in different lane-changing environments, based on the lead spacing and lag spacing in the target lane, a hierarchical clustering algorithm was applied to classify the lane-changing environment into six different types. Then, a deep neural network regression model was applied to model the lane-changing process for each environment type. The results show that the horizontal distribution, vertical distribution and statistical characteristics of the lane changing points under different lane-changing environments are significantly different. The prediction accuracy of the lane-changing distance after classification is improved by at least 61%, and the prediction accuracy of the lane-changing duration after classification is improved by at least 57%. It is also found that lane-changing behavior characteristics with large or small lag spacing are easier to predict, while in the other cases, the randomness of the lane-changing behavior characteristics is more obvious. The research results can be incorporated into lane-changing decision assistance systems and micro traffic simulation models to make the assistance system safer and more effective, and the simulation outputs should be more realistic and accurate.

Traffic simulation in the LoRaWAN network

LoRaWAN is one of the most commonly used technologies serving the internet of things (IoT) and machine-to-machine (M2M) devices. The traffic growth in the LoRaWAN network gives rise to many problems, which are solved using mathematical modelling. The actual task, in this case, is the development of a traffic simulation model in the LoRaWAN network. This article discusses the issues of traffic simulation in the LoRaWAN network and its research using the MATLAB system. The authors have developed a LoRaWAN network server model as a queuing system with incoming self-similar traffic in the MATLAB system using a separate subsystem for the input traffic modelling allowing to change the number of sources in the LoRaWAN network. The simulation results made it possible to establish the dependences of the network server’s buffer memory, the probability of packet loss from the incoming self-similar traffic parameters, and reveal the possibilities of traffic modelling in the MATLAB system.

Evaluation of driver Acceleration/Deceleration behavior at signalized intersections using vehicle trajectory data

ABSTRACT Vehicle Acceleration/Deceleration (A/D) characteristics are fundamental measures often used in designing intersection geometrics, A/D lanes, analyzing vehicle fuel consumption and emission, and traffic simulation modeling. The flow scenario at a signal-controlled intersection involves stop-and-go conditions with variability of A/D characteristics. This study attempts to analyze the vehicle’s A/D behavior at an urban signalized intersection under weak lane disciplined mixed traffic stream using vehicle trajectory data. The result shows that vehicles like car and motorized two-wheeler are associated with high acceleration behavior at lower speeds and need less time and distance to accelerate. Also, these vehicles can decelerate at a higher rate at a lower speed during the stop or clearing of the intersection. The statistical results show that a single and multi-regime polynomial model is more suitable to represent the behavior of A/D characteristics in terms of the approach speed of vehicles.