Traffic Microsimulation Models Research Articles

Calibration of Microsimulation Models – The Effect of Calibration Parameters Errors in the Models’ Performance

Microsimulation models are now widely used. However, the capacity of a model to represent the reality with high level of accuracy depends significantly on the calibration process. This paper presents a sensitivity analysis to test how the expected accuracy of the traffic microsimulation models’ outputs can be affected by different errors’ types and degrees in the estimation of calibration parameters.Using Aimsun software it was possible to establish different relations between the level of the calibration parameters errors, and the corresponding errors in the simulated results. The significant importance of the “reaction time” and “minimum distance between vehicles” was confirmed.

Validation of the Surrogate Safety Assessment Model for Assessment of Intersection Safety

The surrogate safety assessment model (SSAM) is a software application that reads trajectory files generated by microscopic simulation programs and calculates surrogate measures of safety. This approach eliminates the subjectivity associated with the conventional conflict analysis technique and allows assessment of the safety of a facility under a controlled environment before accidents occur. The specific goal of this research was to validate SSAM as a tool for accident prediction at urban intersections. Two methods were used for validation. The first method compared the simulated number of conflicts from the use of SSAM and the predicted number of injury accidents from analytic models in three reference intersection layouts (four-leg priority intersection, four-leg staggered intersection, and single-lane roundabout). The second method compared SSAM results with conflicts observed on site in four real intersections: two priority ones and two roundabouts. The results indicate that, despite some limitations related to the nature of current traffic microsimulation models, SSAM analysis is an extremely promising approach to assessing the safety of new facilities or innovative layouts.

An integrated modelling approach to estimate urban traffic emissions

An integrated modelling approach is adopted to estimate microscale urban traffic emissions. The modelling framework consists of a traffic microsimulation model developed in PARAMICS, a microscopic emissions model (Comprehensive Modal Emissions Model), and two dispersion models, AERMOD and the Quick Urban and Industrial Complex (QUIC). This framework is applied to a traffic network in downtown Toronto, Canada to evaluate summer time morning peak traffic emissions of carbon monoxide (CO) and nitrogen oxides (NOx) during five weekdays at a traffic intersection. The model predicted results are validated against sensor observations with 100% of the AERMOD modelled CO concentrations and 97.5% of the QUIC modelled NOx concentrations within a factor of two of the corresponding observed concentrations. Availability of local estimates of ambient concentration is useful for accurate comparisons of predicted concentrations with observed concentrations. Predicted and sensor measured concentrations are significantly lower than the hourly threshold Maximum Acceptable Levels for CO (31 ppm, ∼90 times lower) and NO2 (0.4 mg/m3, ∼12 times lower), within the National Ambient Air Quality Objectives established by Environment Canada.

Speed Harmonization

The objective of this study was to explore the impacts of early shock wave detection on breakdown formation and driving hazards (safety) and the possible corresponding improvements from the use of speed harmonization as a control strategy. Several efforts have been made to evaluate speed harmonization systems by means of various traffic microsimulation models. However, further related behavioral-based studies are needed, especially in light of the development of connected-vehicle technology. The adopted approach relies on a cognitive risk-based microscopic simulation model capable of endogenously accounting for incidents to study the effects of speed harmonization strategies on traffic flow characteristics and safety. An algorithm based on wavelet transform—to detect shock wave formation—was combined with a reactive speed limit selection algorithm to implement speed harmonization within the microscopic simulation model. Three sets of scenarios were simulated. The results showed significant improvement in traffic flow characteristics through the implementation of the speed harmonization control strategy under congested conditions. Analysis of a fundamental diagram revealed the existence of an optimal location to implement the speed limit changes upstream of the point of shock wave detection. The analysis also revealed the role of speed limit compliance for the success of a speed harmonization system.

Drivers’ Lane Utilization for United Kingdom Motorways

Lane utilization represents how the rate of traffic flow is distributed among the available number of lanes in a given section. This utilization or split is affected by several factors, including traffic flow rates and the presence and amount of heavy-goods vehicles (HGVs) within the traffic. It is important to study lane utilization because it is one of the input parameters for any traffic microsimulation models, which are increasingly being used to assess and suggest solutions for traffic problems. This paper uses two sources of data to model lane utilization—motorway incident detection and automatic signaling (MIDAS) data and individual-vehicles raw data. The latter source of data is specifically used to model how HGVs are distributed between motorway lanes as flow increases because MIDAS data do not specify the proportions of HGVs by lanes. Because the data used to develop the models in this paper are based on a relatively large set of data (compared with those represented by older models), one could argue that these models are more representative of current lane utilization on United Kingdom motorways. The development of lane-utilization models for HGV traffic will help in providing more realistic predictions of traffic behavior when represented by microsimulation models and in assessing such commercial vehicles using the lanes when it comes to pavement design.

Calibration of a New Microsimulation Package for the Evaluation of Traffic Safety Performances

Recently, some studies have confirmed that the reproduction by simulation of user behaviour under different flow and geometric conditions, can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network [1], [2], [3]. In this paper a calibration and validation technique of a microsimulation model for short–term road safety analysis is presented. The microscopic model developed allows the estimation of road safety performance through a series of indicators (Crash Potential Index, Deceleration Rate to Avoid Crash, Maximum Available Deceleration Rate, Time to Collision, etc.), representing interactions in real time between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The calibration procedure was applied using an optimization algorithm to systematically modify the 5 parameters of the core behavior model (the General Motors car following model that is a module of the main traffic microsimulation model) in order to fit travel times obtained from simulations to the measured travel times. Experimental measures where obtained in one measurement site from a survey on a two lane undivided rural highway and were provided using a specifically developed video digital processing algorithm. In order to assess the capability of the microsimulation model to reflect reality and, consequently, to make further predictions, a validation technique was carried out. In the validation process the optimization algorithm shows the ability to increase the goodness of fit of estimated travel times to measured values. The estimated car following model parameters are used in estimating the goodness of fit with a set of observed data which have not previously been used in the calibration process. This procedure has brought very good results that show how the travel times estimation errors can be greatly reduced, even in different traffic conditions relatively to the calibration scenario, by using the set of parameters obtained in the optimization procedure.

Traffic Microsimulation Model to Predict Variability of Red-Light Running Influenced by Traffic Light Operations in Urban Area

Based on previous potential conflicts analysis studies and recent research from the authors [1], this paper address the need to demonstrate the transferability of a new modelling approach by testing the model using a 4 arms signalised junction in Enna (Italy), where an extensive period of continuous video recording has been carried out. Different cycle and green time settings have been implemented in order to measure the effects on the RLR rates. Then the measured RLR rates have been evaluated and compared to the modelling results as a validation exercise improving and extending the prediction capability of the proposed model.

Novel application of red-light runner proneness theory within traffic microsimulation to an actual signal junction

Building on previous research a conceptual framework, based on potential conflicts analysis, has provided a quantitative evaluation of ‘proneness’ to red-light running behaviour at urban signalised intersections of different geometric, flow and driver characteristics. The results provided evidence that commonly used violation rates could cause inappropriate evaluation of the extent of the red-light running phenomenon. Initially, an in-depth investigation of the functional form of the mathematical relationship between the potential and actual red-light runners was carried out. The application of the conceptual framework was tested on a signalised intersection in order to quantify the proneness to red-light running. For the particular junction studied proneness for daytime was found to be 0.17 north and 0.16 south for opposing main road approaches and 0.42 east and 0.59 west for the secondary approaches. Further investigations were carried out using a traffic microsimulation model, to explore those geometric features and traffic volumes (arrival patterns at the stop-line) that significantly affect red-light running. In this way the prediction capability of the proposed potential conflict model was improved. A degree of consistency in the measured and simulated red-light running was observed and the conceptual framework was tested through a sensitivity analysis applied to different stop-line positions and traffic volume variations. The microsimulation, although at its early stages of development, has shown promise in its ability to model unintentional red light running behaviour and following further work through application to other junctions, potentially provides a tool for evaluation of alternative junction designs on proneness. In brief, this paper proposes and applies a novel approach to model red-light running using a microsimulation and demonstrates consistency with the observed and theoretical results.

Applicability of Traffic Microsimulation Models in Vehicle Emissions Estimates

Efforts in estimating emissions by an integration of traffic simulation models and emissions models have become a fast-evolving research area. However, because of the lack of effective methods and indicators to characterize traffic behaviors, the accuracy of emissions by such an approach has not been effectively verified or evaluated. The current study is intended to examine the applicability of traffic microsimulation models in vehicle emissions estimates on the basis of the explanatory parameter of vehicle emissions—the vehicle-specific power (VSP) distribution. Analyzing massive real-world and simulated vehicle activity data showed that the results from traffic simulation could not represent real-world driving behaviors for emissions estimates. The simulated vehicle- specific power distribution led to errors that were as high as 82.8%, 53.6%, and 29.6% for nitrogen oxides, hydrocarbons, and carbon monoxide emissions, respectively. Then a sensitivity analysis of 16 adjustments on eight parameters of simulation models was conducted to determine their effects on simulated VSP distributions: systematic errors existed in the use of traffic simulation models to represent second-by-second driving behaviors. The errors could not be reduced by parameter calibration on the simulation model. This study concluded that the traditional approach of integrating traffic simulation models with emissions models was not applicable for vehicle emissions estimates. The primary reasons for the errors need to be investigated further from the internal mechanism of submodels of microsimulation. On the basis of these findings, several recommendations are proposed for future studies.

Evaluating Safety at Railway Level Crossings with Microsimulation Modeling

Safety at railway level crossings (RLXs) is a worldwide issue that increasingly attracts the attention of relevant transport authorities, the rail industry, and the general public. The differences in the operation characteristics of varying types of warning devices, together with differences in crossing geometry, traffic, or train characteristics, leads to different driver behaviors at crossings. The aim of this study was to use traffic microsimulation modeling based on field video recording data to compare the safety performance of varying conventional RLX warning systems. The widely used microsimulation model VISSIM was modified to produce safety-related performance measures, namely, collision likelihood, delay, and queue length. The results showed that RLXs with an active warning system were safer than those with a passive sign by at least 17%. Integration of surrogate measures in conjunction with traffic simulation models determined which safety approach was more efficient for specified traffic and train volumes.

Vehicle-Type Dependent Car-Following Model for Heterogeneous Traffic Conditions

Car-following behavior forms the kernel of traffic microsimulation models and is extensively studied for similar vehicle types. However, in heterogeneous traffic having a diverse mix of vehicles, following behavior also depends on the type of both the leader and following vehicles. This paper is an attempt to modify the widely used Gipps’s car-following model to incorporate vehicle-type dependent parameters. Performance of the model is studied at microscopic and macroscopic levels using data collected from both homogeneous and heterogeneous traffic conditions. The results indicate that the proposed modifications enhance the prediction of follower behavior and suggest the need of incorporating vehicle-type combination specific parameters into traffic simulation models.

Modeling Factors Influencing the Capacity of Motorway Merge Sections Controlled by Ramp Metering

This paper focuses on studying factors which are likely to affect motorway merge capacity when ramp metering controls are in use. A newly developed traffic micro-simulation model has been used for this purpose and the well known ALINEA and Demand-Capacity local ramp metering algorithms were integrated within it. Several parameters such as critical occupancy to trigger the signals, position of ramp traffic signals, position of loop detectors and length of ramp were considered. The effectiveness of ramp metering for a range of traffic flow conditions has been tested for various scenarios to show the range of values where ramp metering is beneficial.

Traffic Management for Planned Special Events Using Traffic Microsimulation Modeling and Tabletop Exercises

This article describes the use of microsimulation for traffic management of special events, including evacuations and traffic incidents. Specifically, the research employed tabletop exercises using the microsimulation software TransModeler to present traffic management alternatives for special events to stakeholders. The exercises involved analysis of evacuation or egress conditions with current traffic management plans, review of possible high-impact incident scenarios, and testing and formulation of improvements to current traffic management procedures, including incident response. Two case studies were developed for the tabletop exercises; one the evacuation of a minor-league baseball stadium and another concerned with vehicular egress plans for a large urban indoor arena. Both venues were in New York State's Capital District region. The results demonstrated that the real-time use of microsimulation during a tabletop exercise elicited many new traffic management strategies. Also, a cost–benefit analysis of using microsimulation models in conjunction with tabletop exercises for these types of events was explored. The project was made possible by funding from the New York State Department of Transportation and the Federal Highway Administration.

Scheduling Buses to Take Advantage of Transit Signal Priority

Transit signal priority can improve bus operations when it is applied to a route without making any changes to its route design or management; however, benefits can be greater if service design and management policies are purposely altered to take advantage of transit signal priority. Service design issues include generating carefully constructed schedules for use with conditional priority and deciding whether to locate stops on the near side or far side of intersections. Management issues include using conditional priority as a means to give priority only to late buses and deciding whether to hold buses at bus stops until a scheduled departure time, in case conditional priority itself does not offer the desired level of operational control. An optimal level of aggressiveness in the running time schedule is sought as a balance between mean running time with and without priority, assuming that priority will be conditional. With a more aggressive schedule, buses will be late and therefore will request (and get) priority more often; however, a more aggressive schedule also offers less slack to compensate for random delays. Analysis uses both a spreadsheet-based simulation model and a traffic microsimulation model that account for random delays at dispatch and at traffic signals, the effect of crowding on dwell time, and choice of priority and operational control tactics. It is found that optimal performance uses conditional priority and holding, but with an aggressive schedule, leading to substantial reductions in mean running time, standard deviation of running time, headway irregularity, and crowding.

Traffic Microsimulation Modeling to Study a Traffic Signal Incident Reduction Function

This paper demonstrates the use of a discrete event traffic micro-simulation model to study the safety impacts of the introduction of an incident reduction (IR) function into a vehicle-actuated traffic signal controller. The IR function is based on that used in signal controllers in Sweden. The IR function is designed to reduce the number of stop-or-go decisions by drivers when caught in the dilemma zone at the onset of the amber signal. A correctly adapted IR function was found to greatly enhance the safety performance of signalized intersections. The simulation experiment described in the paper is based on empirical data from a suburban vehicle-actuated signalized intersection. It was conducted specifically to investigate the effects of the standard IR function on three proximal safety indicators: time to collision, red light violations, and required braking rates. The simulation results demonstrate a significant improvement in the time to collision (22%), red light violations (6%), and required braking rate when the IR function was in operation and a small positive influence on traffic movement through the intersection. Importantly, this study has illustrated the potential for using traffic microsimulation modeling for traffic safety evaluation.

How Parameters of Microscopic Traffic Flow Models Relate to Traffic Dynamics in Simulation

Several methodological issues in setting up a calibration process for traffic microsimulation models are still unresolved. The influence of individual parameters of microscopic models on simulated traffic dynamics is also far from clear. To address those issues, the paper sets up a methodology based on the sensitivity analysis of traffic flow models (the one used here is AIMSUN). Sensitivity analysis was performed by means of a series of 30 analyses of variance. These were designed to evaluate the effect of parameters on the variance of the simulated outputs and to draw a general inference about ( a) the proper interval for the aggregation of measurements, ( b) the proper measure of performance (e.g., traffic counts versus speeds), ( c) the proper traffic measurement locations, and ( d) the subset of parameters to calibrate. The analysis allowed quantification of the effect of the single parameters on different traffic phases. For example, it was possible to quantify the extent of the influence of the parameter reaction time on simulated outputs in locations in which free flow, rather than congested conditions, occurs. The great differences between parameters in affecting the different traffic phases suggested that parameters are likely to be calibrated independently, that is, using data from different locations. The first evidence of the possibility of breaking the calibration problem into two subproblems is given. This entails great benefits in regard to computational time, given the exponential computational complexity of the calibration problem.

The principles of calibrating traffic microsimulation models

Traffic microsimulation models normally include a large number of parameters that must be calibrated before the model can be used as a tool for prediction. A wave of methodologies for calibrating such models has been recently proposed in the literature, but there have been no attempts to identify general calibration principles based on their collective experience. The current paper attempts to guide traffic analysts through the basic requirements of the calibration of microsimulation models. Among the issues discussed here are underlying assumptions of the calibration process, the scope of the calibration problem, formulation and automation, measuring goodness-of-fit, and the need for repeated model runs.

Comparison of Simulation-Based and Model-Based Calibrations of Traffic-Flow Microsimulation Models

Parameter calibration of traffic microsimulation models usually takes the form of a simulation-based optimization problem, that is, an optimization in which every objective function evaluation calls for a simulation. It is recognized that such a problem is computationally intractable. Running time grows exponentially both in the number of parameters and in the digits accuracy. In addition, considerable computing time is required by each objective function evaluation. This means that only heuristic techniques can be applied. Accordingly, results of the application of the OptQuest/Multistart algorithm to the calibration of AIMSUN microsimulation model parameters on a freeway network are presented. Furthermore, it is claimed that the search for an effective solution to the calibration problem cannot be exhausted by the choice of the most efficient optimization algorithm. The use of available information concerning the phenomenon could allow calibration performance to be enhanced, for example, by reducing dimensions of the domain of feasible solutions. It is argued that this goal could be achieved by using information from the stationary counterpart of microscopic traffic-flow models that depict the aggregate variables of traffic flows as a function of drivers’ microscopic parameters. Because they have a closed analytical formulation, they are well suited for faster calibrations. Results show that values of parameters from stationary model-based calibrations are not far from the optimal ones. Thus the integration of the two approaches cannot be excluded but is worth investigating.

Estimation of the distribution of travel times by repeated simulation

In recent years, the reliability of transport systems has been widely recognised as a key issue in transport planning and evaluation. To analyse the level of reliability we need information about the distribution of travel times. Transport analysts are in a serious need for tools to estimate this distribution in hypothetical scenarios, but there are currently few such tools. In this paper we raise the question of whether it is possible to look at the outputs of each single run of a traffic microsimulation model as estimates of traffic conditions on a single day, while accounting for the fact that randomness and heterogeneity are in the nature of traffic phenomena. If it is possible to establish an analogy between a single run and a single day, then the distribution of outputs between runs can be used as an estimate of the respective distribution in the real network. Investigating this issue is vital since many practitioners wrongly assume that such analogy can be taken for granted. We discuss here methodological, statistical and computational aspects that this question brings in, and illustrate them in a series of experiments, where a special procedure for calibrating the microsimulation model has a key role.

A new approach to evaluating on-road public transport priority projects: balancing the demand for limited road-space

Despite widespread growth in on-road public transport priority schemes, road management authorities have few tools to evaluate the impacts of these schemes on all road users. This paper describes a methodology developed in Melbourne, Australia to assist the road management authority, VicRoads, evaluate trade-offs in the use of its limited road-space for new bus and tram priority projects. The approach employs traffic micro-simulation modelling to assess road-space re-allocation impacts, travel behaviour modelling to assess changes in travel patterns and a social cost benefit framework to evaluate impacts. The evaluation considers a comprehensive range of impacts including the environmental benefits of improved public transport services. Impacts on public transport reliability improvements are also considered. Although improved bus and tram reliability is a major rationale for traffic priority its use in previous evaluations is rare. The paper critiques previous approaches, describes the proposed method and explores some of the results found in its application. A major finding is that despite a more comprehensive approach to measuring the benefits of bus and tram priority, road-space reallocation is difficult to economically justify in road networks where public transport usage is low and car usage high. Strategies involving the balanced deployment of bus and tram priority measures where the allocation of time and space to PT minimises negative traffic impacts is shown to improve the overall management of road-space. A discussion of the approach is also provided including suggestions for further methodology development.