Microscopic Traffic Simulation Model Research Articles

Study of Feasibility Analysis for the Protected-Permissive Left-Turn Signal Control in Three-Leg Signalized Intersections Using a Microscopic Traffic Simulation Model

PURPOSES : This study evaluated the feasibility of implementing protected-permissive left-turn (PPLT) signals at three-leg signalized intersections. METHODS: A three-leg signalized intersection with permissive left-turn was first selected. A VISSIM simulation model was constructed using data collected from the test site. The VISSIM network was calibrated by adjusting related parameter values in order to minimize the difference between the simulated and surveyed critical gap. The calibrated network was validated by the number of waiting left-turning vehicles per cycle. Finally, the mobility and safety measures were extracted from simulation runs in which permissive, protected left turns as well as PPLTs were realized based on diverse traffic volume scenarios. RESULTS : The mobility-related measures of effectiveness (MOEs) of the case with PPLT outperformed the other two left-turn treatment scenarios. In particular, the average waiting time per cycle for the left-turn vehicles in the case with PPLT was reduced by 30 s. The safety-related MOEs of the case with PPLT were somewhat higher than those in the case with protected left-turns and much higher than those in the case with permissive left-turns. CONCLUSIONS : Based on the mobility- and safety-related MOEs generated from the VISSIM simulation runs, the use of PPLT seems to be feasible at three-leg signalized intersections where the left-turn is permissive and a pedestrian signal exists at the conflicting approach. However, in order to use the PPLT in earnest, it is necessary to revise the road traffic act, traffic signs, and related manuals.

Energy-Efficient Urban Traffic Management: A Microscopic Simulation-Based Approach

Microscopic urban traffic simulators embed the most detailed traveler behavior and network supply models. These simulators represent individual vehicles and can therefore account for vehicle-specific technologies. They can be coupled with instantaneous fuel consumption models to yield detailed network-wide fuel consumption estimates. Nonetheless, there is currently a lack of computationally efficient optimization techniques that enable the use of these complex integrated models to design sustainable transportation strategies. This paper proposes a methodology that combines a stochastic microscopic traffic simulation model with an instantaneous vehicular fuel consumption model. The combined models are embedded within a simulation-based optimization algorithm and used to address a signal control problem that accounts for both travel times and fuel consumption. The proposed technique couples detailed, stochastic, and computationally inefficient models, yet is an efficient optimization technique. Efficiency is achieved by combining simulated observations with analytical approximations of both travel time and fuel consumption. This methodology is applied to a network in the Swiss city of Lausanne. Within a tight computational budget, the proposed method identifies signal plans with improved travel time and fuel consumption metrics. It outperforms traditional methodologies, which use only simulated information or only analytical information. The case study illustrates the added value of combining simulated and analytical information when performance metrics with high variance, such as fuel consumption, are used. This method enables the use of disaggregate instantaneous vehicle-specific information to inform and improve traffic operations at the network-scale.

Capacity of Freeway Merge Areas with Different On-Ramp Traffic Flow

This paper is aimed at investigating the influence of different types of traffic flows on the capacity of freeway merge areas. Based on the classical gap-acceptance model, two calculating models were established specifically considering randomly arriving vehicles and individual difference in driving behaviours. Monte-Carlo simulation was implemented to reproduce the maximum traffic volume on the designed freeway merge area under different situations. The results demonstrated that the proposed calculating models have better performance than the conventional gap-acceptance theory on accurately predicting the capacity of freeway merge areas. The findings of research could be helpful to improve the microscopic traffic flow simulation model from a more practical perspective and support the designing of freeway merge areas as well.

Calibration of traffic flow models using a memetic algorithm

A Memetic Algorithm (MA) for the calibration of microscopic traffic flow simulation models is proposed in this study. The proposed MA includes a combination of genetic and simulated annealing algorithms. The genetic algorithm performs the exploration of the search space and identifies a zone where a possible global solution could be located. After this zone has been found, the simulated annealing algorithm refines the search and locates an optimal set of parameters within that zone. The design and implementation of this methodology seeks to enable the generalized calibration of microscopic traffic flow models. Two different Corridor Simulation (CORSIM) vehicular traffic systems were calibrated for this study. All parameters after the calibration were within reasonable boundaries. The calibration methodology was developed independently of the characteristics of the traffic flow models. Hence, it is easily used for the calibration of any other model. The proposed methodology has the capability to calibrate all model parameters, considering multiple performance measures and time periods simultaneously. A comparison between the proposed MA and the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm was provided; results were similar between the two. However, the effort required to fine-tune the MA was considerably smaller when compared to the SPSA. The running time of the MA-based calibration was larger when it was compared to the SPSA running time. The MA still required some knowledge of the model in order to set adequate optimization parameters. The perturbation of the parameters during the mutation process must have been large enough to create a measurable change in the objective function, but not too large to avoid noisy measurements.

Towards data-driven car-following models

Car following models have been studied with many diverse approaches for decades. Nowadays, technological advances have significantly improved our traffic data collection capabilities. Conventional car following models rely on mathematical formulas and are derived from traffic flow theory; a property that often makes them more restrictive. On the other hand, data-driven approaches are more flexible and allow the incorporation of additional information to the model; however, they may not provide as much insight into traffic flow theory as the traditional models. In this research, an innovative methodological framework based on a data-driven approach is proposed for the estimation of car-following models, suitable for incorporation into microscopic traffic simulation models. An existing technique, i.e. locally weighted regression (loess), is defined through an optimization problem and is employed in a novel way. The proposed methodology is demonstrated using data collected from a sequence of instrumented vehicles in Naples, Italy. Gipps’ model, one of the most extensively used car-following models, is calibrated against the same data and used as a reference benchmark. Optimization issues are raised in both cases. The obtained results suggest that data-driven car-following models could be a promising research direction.

Developing a 24-Hour Large-Scale Microscopic Traffic Simulation Model for the Before-and-After Study of a New Tolled Freeway in the Washington, DC–Baltimore Region

AbstractFor determining highly disaggregate details about traffic dynamics, microscopic traffic simulation has long proven to be a valuable tool for the evaluation of development plans and operation/control strategies. With recent advances in computing capabilities, research interest in large-scale microscopic simulation has never been greater. This case study develops a 24-h large-scale microscopic traffic simulation model for the Washington, DC, metropolitan area. The model consists of over 7,000 links, 3,500 nodes, 400 signalized intersections, and over 40,000 origin-destination pairs. Various field measurements, such as time-dependent traffic counts and corridor travel times, have been used for model calibration/validation. The EPA’s Motor Vehicle Emission Simulator is linked with the microscopic simulation model for the estimation of environmental impacts. The calibrated model system has been used to comprehensively evaluate a newly built toll road in Maryland, the Intercounty Connector. Various netw...

Empirical Estimation of Desired Speed Distributions for Microscopic Traffic Simulation

The desired speed is an important parameter for microscopic traffic simulation. The desired speed can only be directly measured for free-flowing vehicles. However, the average speeds of unimpeded vehicles are systematically lower than the desired speeds of all vehicles. Recently, a new estimation technique in which the speeds of impeded vehicles were considered as censored values was introduced. Here, this method was applied with empirical traffic data in a modified version to estimate desired-speed distributions for two freeway sections in Germany. On the basis of simulation studies the method was shown to deliver consistent desired-speed distributions that allowed for a realistic representation of driver speed behavior within microscopic traffic simulation models.

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO2) concentrations as the effect observed on nitrogen oxide (NOx) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO2 levels increased between 0.1% and 10% with respect to the base-case while changes in NOx emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO2 concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO2 levels.

Development of simulated driving cycles for light, medium, and heavy duty trucks: Case of the Toronto Waterfront Area

Driving cycles are an important input for state-of-the-art vehicle emission models. Development of a driving cycle requires second-by-second vehicle speed for a representative set of vehicles. Current standard driving cycles cannot reflect or forecast changes in traffic conditions. This paper introduces a method to develop representative driving cycles using simulated data from a calibrated microscopic traffic simulation model of the Toronto Waterfront Area. The simulation model is calibrated to reflect road counts, link speeds, and accelerations using a multi-objective genetic algorithm. The simulation is validated by comparing simulated vs. observed passenger freeway cycles. The simulation method is applied to develop AM peak hour driving cycles for light, medium and heavy duty trucks. The demonstration reveals differences in speed, acceleration, and driver aggressiveness between driving cycles for different vehicle types. These driving cycles are compared against a range of available driving cycles, showing different traffic conditions and driving behaviors, and suggesting a need for city-specific driving cycles. Emissions from the simulated driving cycles are also compared with EPA’s Heavy Duty Urban Dynamometer Driving Schedule showing higher emission factors for the Toronto Waterfront cycles.

Integration of signal timing estimation model and dynamic traffic assignment in feedback loops: system design and case study

SummaryThis paper presents an integrated framework for effective coupling of a signal timing estimation model and dynamic traffic assignment (DTA) in feedback loops. There are many challenges in effectively integrating signal timing tools with DTA software systems, such as data availability, exchange format, and system coupling. In this research, a tight coupling between a DTA model with various queue‐based simulation models and a quick estimation method Excel‐based signal control tool is achieved and tested. The presented framework design offers an automated solution for providing realistic signal timing parameters and intersection movement capacity allocation, especially for future year scenarios. The framework was used to design an open‐source data hub for multi‐resolution modeling in analysis, modeling and simulation applications, in which a typical regional planning model can be quickly converted to microscopic traffic simulation and signal optimization models. The coupling design and feedback loops are first demonstrated on a simple network, and we examine the theoretically important questions on the number of iterations required for reaching stable solutions in feedback loops. As shown in our experiment, the current coupled application becomes stable after about 30 iterations, when the capacity and signal timing parameters can quickly converge, while DTA's route switching model predominately determines and typically requires more iterations to reach a stable condition. A real‐world work zone case study illustrates how this application can be used to assess impacts of road construction or traffic incident events that disrupt normal traffic operations and cause route switching on multiple analysis levels. Copyright © 2014 John Wiley & Sons, Ltd.

Evaluation of right-turn lanes at signalized intersection in non-lane-based heterogeneous traffic using microscopic simulation model

In developing countries like India, the traffic on urban roads is highly heterogeneous in nature, with vehicles of widely varying static and dynamic characteristics. This type of traffic is characterized by lack of queue and lane discipline (lane-less movement) based on availability of spaces near intersections. Moreover, at intersections, straight-through, left-, and right-turning vehicles seek to occupy the same physical space. In such situations, the through vehicles are susceptible to delays in the absence of turn lanes for the left-turning and right-turning vehicles and vice versa. Models suitable for analysis of such traffic flow hardly exist, and most of the available models are limited in scope. In the current study, a microscopic traffic simulation model for signalized intersection is developed specifically for heterogeneous traffic. This model covers different vehicle types and allows for some special behavior, such as seepage of two-wheelers to fronts of queues. Detailed study of queue formation and dissipation were done microscopically under non-lane-based traffic conditions near intersection area. The model was calibrated and tested with data from Chennai city, India, and its predictions were found to be in close agreement with the field data. In addition, the model makes a significant contribution to the study of right-turn lane (RTL) on delays to vehicles. In general, RTL is found to be advantageous for most cases of approach volumes and right-turn proportions. The optimal lengths of RTL are suggested for various approach volumes and right-turn proportions.

Driving Behavior Parameter Sensitivity Analysis Based on VISSIM

The determination of the parameter set to be corrected is the premise and key of microscopic traffic simulation model’s calibration. In order to find out the sensitive parameter, this paper chooses Ronghua Road and Wing King Street intersection and the Shangdi Roundabout as experiments, and selects the queue length and travel time as the evaluation index, makes sensitivity analysis of calibrated parameters by microscopic traffic simulation software Vissim. It adopts a line chart method, range analysis and sensitivity coefficients to make comparative analysis of the evaluation results. At last, sensitivity parameters in intersection and roundabout are not identical.

Speed–Flow–Geometry Relationships and Capacity for Two–Lane Single Carriageway Roads

The current Malaysian practice in road capacity analysis, Malaysian Highway Capacity Manual 2011 (MHCM) is based on a method adopted from the Highway Capacity Manual(HCM) of the United States. All the analysis elements appear to be taken directly from the manual. The rationale for using such a method for Malaysian conditions is not well defined. This paper deliberates the background of the methodology used in the development of speed, flow and geometry relationships and the capacity for single carriageway roads. A microscopic traffic simulation model which is capable of simulating traffic operations on single carriageway roads for a range of road geometry configurations and traffic flow conditions was developed and used to evaluate the potential capacity of a single carriageway road. The results of the analysis indicate that a two-lane single carriageway road is capable of accommodating traffic flow higher than the values derived from the previous HCM. The current version of the HCM also appears to underestimate the vehicles’ travel speed for a range of traffic flows when compared with the results of the simulation model. The MHCM 2011, on the other hand, estimated travel speeds higher than the travels speeds predicted by both the HCM 2010 and simulation model. It shows that there is a different interpretation of LOS F in term of speed between HCM 2010 and MHCM 2011.

Development and Validation of a Vehicle Dynamics Integrated Traffic Simulation Environment Assessing Surrogate Safety

A vehicle dynamics model was integrated with a microscopic traffic simulation model for a surrogate safety assessment. The research reported in this paper was initiated from the idea that existing microscopic traffic simulation models could be complemented with a vehicle dynamics model having an enhanced capability of realizing the vehicle dynamics including pitch, yaw, and roll and generating realistic vehicle trajectories. In addition, a driver aggressiveness model derived from a lane change vehicle trajectories model was incorporated into the lane change vehicles in the microscopic traffic simulation model. The resulting microscopic traffic simulation model vehicle trajectories were processed through the vehicle dynamics model to account for the vehicle dynamics and the traffic conflicts were identified through the surrogate safety assessment model. The integrated microscopic traffic/vehicle dynamics simulation environment resulted in 9.5% fewer traffic conflicts as compared with the microscopic traffic simulation model only approach. The results of the two conflict estimation approaches, from the (1) proposed integrated approach, and (2) microscopic traffic simulation model only approach, were analyzed to estimate their correlation with the actual traffic crashes. These correlations were then used to compare the effectiveness of these approaches in assessing surrogate safety. This analysis from the research reported in this paper showed that the traffic conflicts obtained from the proposed approach exhibited a stronger correlation (i.e., 0.72 correlation coefficient) with traffic crashes than the existing approach did (i.e., 0.61 correlation coefficient). A cross-validation test on the confidence intervals of the correlation coefficients showed that the correlation coefficients have very tight confidence intervals (i.e., 0.02 for both cases) indicating that the newly developed vehicle dynamics model-integrated surrogate safety simulation environment is a superior and valid alternative in assessing the surrogate safety. Language: en

Bi-Objective Optimization Approach for Exclusive Bus Lane Scheduling Design

Implementation of an exclusive bus lane (XBL) requires proper planning as it reduces road capacity for nonbus traffic and could possibly worsen traffic congestion in urban cities. Exclusive bus lane scheduling (XBLS) has been implemented in several cities but a systematic methodology on the design of such schedules is yet to be made available. This paper proposes a biobjective optimization model to optimize a bus lane schedule taking into consideration bus and nonbus traffic performances. A hybrid nondominated sorting genetic algorithm (NSGA II) with a microscopic traffic simulation model was adopted to solve the optimization model. Through the analyses presented in this paper, it was found that the proposed model is capable of producing XBL schedules to relieve traffic congestion, while being sensitive to key parameters (such as population size, travel demand level, and minimum duration for implementation). Pareto solutions from the model allow engineers to decide the appropriate trade-off for improving bus performance without overdeteriorating nonbus traffic performance. This is crucial for sustainable transport planning in which the performances of multimode transport systems need to be balanced.

From a Link-Node-Based Network Representation Model to a Lane-Based Network Representation Model: Two-Dimensional Arrangements Approach

Most mesoscopic and microscopic traffic simulation studies require the road network under analysis to be detailed at the lane level. Lane-based network representation models could serve as a more realistic platform to provide a geospatial context for traffic simulations to be performed at the level of individual vehicles in a manner that takes into consideration the geospatial context. Presently, most road networks are modeled based on a link-node structure, in which road segments are modeled as links that start, end, and connect to each other at nodes; detailed information regarding lane and lane connectivity at intersections is lost. To overcome this gap between the link-node-based and the lane-based network representations, both open source and commercial simulation packages had created specific data structures and formats, making it difficult to extend them to convert link-node representations into lane-based network representations and facilitate the sharing of resulting lane models. This paper presents an effective approach to automatically derive generic lane-based network representation models from link-node-based network representation models using the concept of two-dimensional (2D) arrangements to realize the automatic extraction of link and lane topologies. The method was prototyped and tested on a Manhattan and a Miami road network. The algorithms and tools created in this study greatly facilitate the development of mesoscopic and microscopic traffic simulation models to address a wide array of infrastructure engineering problems.

Border crossing delay prediction using transient multi-server queueing models

As a result of the continued increase in travel demand coupled with the need for tighter security and inspection procedures after September 11, border crossing delay has recently become a critical issue with tremendous economic and social costs. The current paper develops multi-server queuing models to estimate border crossing delay in support of a predictive traveler information system for the crossings. Two classes of multi-server models are considered: (1) models with exponential inter-arrival times and Erlang service times; and (2) a more generic model with a Batch Markovian Arrival Process (BMAP) and phase types (PH) services. As a case study, the models are developed based on real-time traffic volume and inspection time data collected at one of the major US–Canada border crossings, the Peace Bridge, and their transient solution is obtained using heuristic methods. For validation, the queueing models’ estimates are compared to the results from a detailed microscopic traffic simulation model of the Peace Bridge border crossing. The comparison shows that the transient queueing model, along its heuristic solution algorithm, is capable of predicting border crossing delay. Finally, a set of sensitivity analysis tests are conducted, and the developed models are incorporated within an optimization framework to help inform border crossing management strategies.

A microscopic analysis of speed deviation impacts on lane-changing behavior

Driving behavior models that capture drivers’ tactical maneuvering decisions in different traffic conditions are essential to microscopic traffic simulation systems. This paper focuses on a parameter that has a great impact on road users’ aggressive overtaking maneuvers and directly affects lane-changing models (an integral part of microscopic traffic simulation models), namely, speed deviation. The objective of this research is to investigate the impacts of speed deviation in terms of performance measures (delay time, network mean speed, and travel time duration) and the number of lane-change maneuvers using the Aimsun traffic simulator. Following calibration of the model for a section of urban highway in Tehran, this paper explores the sensitivity of lane-changing maneuvers during different speed deviations by conducting two types of test. Simulation results show that, by decreasing speed deviation, the number of lane changes reduces remarkably and so network safety increases, thus reducing travel time due to an increase in network mean speed.

Simulating the environmental effects of isolated and area-wide traffic calming schemes using traffic simulation and microscopic emission modeling

This study focuses on the development of a microscopic traffic simulation and emission modeling system which aims at quantifying the effects of different types of traffic calming measures on vehicle emissions both at a link-level and at a network-level. It also investigates the effects of isolated traffic-calming measures at a corridor level and area-wide calming schemes, using a scenario analysis. Our study is set in Montreal, Canada where a traffic simulation model for a dense urban neighborhood is extended with capabilities for microscopic emission estimation. The results indicate that on average, isolated calming measures increase carbon dioxide (CO2), carbon monoxide (CO), and nitrogen oxides (NOx) emissions by 1.5, 0.3, and 1.5 %, respectively across the entire network. Area-wide schemes result in a percentage increase of 3.8 % for CO2, 1.2 % for CO, and 2.2 % for NOx across the entire network. Along specific corridors where traffic calming measures were simulated, increases in emissions of up to 83 % were observed. We also account for the effect of different measures on traffic volumes and observe moderate decreases in areas that have undergone traffic calming. In spite of traffic flow reductions, total emissions do increase.