Microscopic Traffic Simulation Tool Research Articles

Maximum Green Time Settings for Traffic-Actuated Signal Control at Isolated Intersections Using Fuzzy Logic

Traffic Actuated Control (TAC) is widely used for signal control in isolated intersections. TAC is a responsible method for online traffic data. In TAC, green durations are dynamically determined based on online traffic data. These determinations are subject to predefined static parameters which do not respond to sudden traffic flow changes. One type of these parameters in TAC is maximum green time. In this paper, maximum green times are dynamically determined by means of fuzzy control. At first, it monitors the whole intersection traffic conditions and then dynamically adjusts maximum green times. The main advantage of the proposed approach is its capability to adjust maximum green times which are responsive to real time traffic condition in isolated intersections. The efficiency of the proposed method has been evaluated by AIMSUN 7 microscopic traffic simulation tool. The evaluation results show the efficiency and the robustness of the proposed method compared to maximum green times provided by SYNCHRO8.

Modelling acceleration decisions in traffic streams with weak lane discipline: A latent leader approach

Acceleration is an important driving manoeuvre that has been modelled for decades as a critical element of the microscopic traffic simulation tools. The state-of-the art acceleration models have however primarily focused on lane based traffic. In lane based traffic, every driver has a single distinct lead vehicle in the front and the acceleration of the driver is typically modelled as a function of the relative speed, position and/or type of the corresponding leader. On the contrary, in a traffic stream with weak lane discipline, the subject driver may have multiple vehicles in the front. The subject driver is therefore subjected to multiple sources of stimulus for acceleration and reacts to the stimulus from the governing leader. However, only the applied accelerations are observed in the trajectory data, and the governing leader is unobserved or latent. The state-of-the-art models therefore cannot be directly applied to traffic streams with weak lane discipline.This prompts the current research where we present a latent leader acceleration model. The model has two components: a random utility based dynamic class membership model (latent leader component) and a class-specific acceleration model (acceleration component). The parameters of the model have been calibrated using detailed trajectory data collected from Dhaka, Bangladesh. Results indicate that the probability of a given front vehicle of being the governing leader can depend on the type of the lead vehicle and the extent of lateral overlap with the subject driver. The estimation results are compared against a simpler acceleration model (where the leader is determined deterministically) and a significant improvement in the goodness-of-fit is observed. The proposed models, when implemented in microscopic traffic simulation tools, are expected to result more realistic representation of traffic streams with weak lane discipline.

A binary decision model for discretionary lane changing move based on fuzzy inference system

This paper presents a Fuzzy Inference System (FIS) which models a driver’s binary decision to or not to execute a discretionary lane changing move on freeways. It answers the following question “Is it time to begin to move into the target lane?” after the driver has decided to change lane and have selected the target lane. The system uses four input variables: the gap between the subject vehicle and the preceding vehicle in the original lane, the gap between the subject vehicle and the preceding vehicle in the target lane, the gap between the subject vehicle and the following vehicle in the target lane, and the distance between the preceding and following vehicles in the target lanes. The input variables were selected based on the outcomes of a drivers survey, and can be measured by sensors instrumented in the subject vehicle. The FIS was trained with Next Generation SIMulation (NGSIM) vehicle trajectory data collected at the I-80 Freeway in Emeryville, California, and then tested with data collected at the U.S. Highway 101 in Los Angeles, California. The results of the test have shown that the system made lane change recommendations of “yes, change lane” with 82.2% accuracy, and “no, do not change lane” with 99.5% accuracy. These accuracies are better than the same performance measures given by the TRANSMODELER’s gap acceptance model for discretionary lane change on freeways, which is also calibrated with NGSIM data. The developed FIS has a potential to be implemented in lane change advisory systems, in autonomous vehicles, as well as microscopic traffic simulation tools.

Improving Traffic Flow at Long-term Roadworks

Improving Traffic Flow at Long-term Roadworks

Modeling Traffic Control Agency Decision Behavior for Multimodal Manual Signal Control Under Event Occurrences

Traffic control agencies (TCAs), including police officers, firefighters, or other traffic law enforcement officers, can override automatic traffic signal control and manually control the traffic at an intersection. TCA-based traffic signal control is crucial to mitigate nonrecurrent traffic congestion caused by planned and unplanned events. Understanding and predicting TCA behaviors is significant to optimize event traffic management and operations. In this paper, we propose a pressure-based human behavior model to mimic TCA's decision-making behavior. The model calculates TCA's pressure based on two attributes: vehicle and pedestrian queue dynamics and the red time duration for each phase. When TCA's pressure on each phase meet certain criteria and the minimal green is satisfied, TCA will terminate the current phase and switch to another phase. In order to study TCA behavior systematically, we first build a manual signal control simulator based on a microscopic traffic simulation tool. Supported by the manual control simulator, a series of human subject experiments have been conducted with real-world TCAs. Experiment data are divided into training data and test data. The proposed behavior model is then calibrated by training data, and the model is validated by both offline segment-based phase and duration prediction and online VISSIM-based simulation. Further, we test the model with videotaped TCA behavior data at a real-world intersection. Both validation results support the effectiveness of proposed behavior model.

AM-Band: An Asymmetrical Multi-Band model for arterial traffic signal coordination

MAXBAND and MULTIBAND are two well-recognized methods for arterial signal control. In this paper, an Asymmetrical Multi-BAND (AM-BAND) model is developed by relaxing the symmetrical progression band requirement in MULTIBAND. Such a relaxation allows the AM-BAND model to better utilize the available green times in each direction and to provide additional opportunities for vehicular progression. Similar to MULTIBAND, the proposed AM-BAND model is formulated as a mixed-integer linear program. However, in AM-BAND the green bands in each directional section of the arterials do not have to be symmetrical with respect to the progression line. The performance of the AM-BAND model is evaluated for two arterial network data using the AIMSUN microscopic traffic simulation tool. The optimal signal coordination plans are computed by the IBM CPLEX Optimization Studio and compared with signal timing plans generated by AM-BAND, MULTIBAND, and MAXBAND. Simulation results indicate that the traffic signal coordination plans generated by AM-BAND can provide significant benefits compared to those generated by MAXBAND and MULTIBAND.

Comparison of SimTraffic and VISSIM Microscopic Traffic Simulation Tools in Modeling Roundabouts

SimTraffic and VISSIM are two microscopic traffic simulation tools that are capable of modeling arterial roads with signalized intersections and roundabouts. This study compares the performance of the two simulation tools in modeling dual lane and triple lane roundabouts under different scenarios such as traffic volume, proportion of left turning movement, and proportion of trucks in the traffic flow. The two simulation tools did not show statistically significant difference in general. However; in the case of high traffic volumes, VISSIM showed higher average delays than those from SimTraffic compared to nearly identical results in the case of low traffic volumes.

Impact of Minimum Driveway Spacing Policies on Safety Performance: An Integrated Traffic Micro-Simulation and Automated Conflict Analysis

A key strategy for successful access management is the adoption of driveway spacing guidelines that consider both safety and operations. The goal is to provide sufficient distance from one driveway to the next so that drivers can perceive and react to the conditions at each potential conflict point in succession. State DOTs across the country have adopted different driveway spacing standards that vary according to the access class and characteristics of the adjacent roadway, such as type of roadway, posted speed limit, and traffic volume. Utilizing the VISSIM microscopic traffic simulation tool and FHWA's Surrogate Safety Assessment Model (SSAM), this research examined safety implications of four different driveway spacing policies representing 13 states. The analysis involved calibrating the VISSIM model for an arterial roadway corridor in West Columbia, SC, and then using the calibrated model to simulate various operational changes to the corridor, including speed limits, traffic volumes, and the associated minimum driveway spacing criteria for the four different policies. SSAM was used to analyze vehicle trajectories derived from VISSIM to determine the number of conflict points. Experimental results indicate that posted speed limit and traffic volume are the primary impact factors for driveway safety, and thus, these parameters should be considered in establishing minimum driveway spacing. Findings from this study indicate that there are significant differences in safety impacts between the different driveway spacing policies adopted by various state DOTs.

Dynamic Simulation of Traffic Noise by Applying Ray Tracing Method based on Indoor Space Partitioning

This study presents a revised 3D ray tracing method by combining it with indoor space partitioning. This method divides an entire indoor space into limited convex polyhedron subspaces, and thus reduces the number of surfaces intersected with rays, and omits the validity test of the collision point on the reflecting surfaces. Combining it with a microscopic traffic simulation tool and a vehicle noise emission model, and taking the influence of diffraction into account, the method can be utilized in simulating dynamically the process of traffic noise diffusing inside the building through windows. Meanwhile, this study selects two different types of indoor architectural layouts in order to demonstrate the efficiency of this method, the influence of diffraction and of the state of windows, and the differences in indoor noise on different floors. A comparison study on before-and-after indoor space partitioning shows that the method is efficient.

Modular Simulation-Based Physical and Emotional Assessment of Ambient Intelligence in Traffic

In this letter, we detail a modular approach for measuring the secondary physical and emotional effects of ambient intelligence (AmI) technology in traffic. Using the case of merges on to a highway, we assess the results of a system that advises the driver to change early to a lane on the left to create space for merging cars downstream (tested using a cellular automata simulation). The indirect impact of the system downstream, namely how the remaining lane changes from the merge lane to the innermost lane proceed, is then evaluated using a time-discrete, space-continuous microscopic traffic simulation tool. This yields detailed results concerning driver interactions that can also be used to derive an estimate of driver anger in the situation. We have used real geographic, traffic and psychological data to test the system, and different models are used to accomplish various tasks. The approach yields (surprisingly) negative results concerning the indirect emotional impact of this AmI intervention which may be due to the nature of the lane changing model used and the chosen parameters. We argue that such an approach is also applicable to similar types of systems, where different data and model types are suited to different scenario elements.

Assessment of Level of Service on Freeways by Microscopic Traffic Simulation

Analytical methods for the assessment of traffic flow quality on freeways are valid for standard types of basic, merge, diverge, and weaving segments. For more complex freeway facilities, microscopic traffic flow simulation is widely used. In this case, the definition and the computation of the level of service must be compatible with the analytical methods. For the forthcoming edition of the German Highway Capacity Manual, standards and user guidance for the application of microscopic traffic flow simulation tools for quality of service assessment on freeways were developed. For typical freeway segments, standard parameter sets for the simulation tools VISSIM, AIMSUN, PARAMICS, BABSIM, and Simulation of Urban Mobility were developed. This study applied these simulation tools for a diverge with a two-lane exit ramp. The results show that the simulation results represent the manual's design capacities well.

Review of Microscopic Lane-Changing Models and Future Research Opportunities

Driver behaviors, particularly lane-changing behaviors, have an important effect on the safety and throughput of the roadway-vehicle-based transportation system. Lane-changing models are a vital component of various microscopic traffic simulation tools, which are extensively used and playing an increasingly important role in Intelligent Transportation Systems studies. The authors conducted a detailed review and systematic comparison of existing microscopic lane-changing models that are related to roadway traffic simulation to provide a better understanding of respective properties, including strengths and weaknesses of the lane-changing models, and to identify potential for model improvement using existing and emerging data collection technologies. Many models have been developed in the last few decades to capture the uncertainty in lane change modeling; however, lane-changing behavior in the real world is very complex due to driver distraction (e.g., texting and cellphone or smartphone use) and environmental (e.g., pavement and lighting conditions) and geometric (e.g., horizontal and vertical curves) factors of the roadway, which have not been adequately considered in existing models. Therefore, large and detailed microscopic vehicle trajectory data sets are needed to develop new lane changing models that address these issues, and to calibrate and validate lane-changing models for representing the real world reliably. Possible measures to improve the accuracy and reliability of lane-changing models are also discussed in this paper.

Modelling driving decisions: a latent plan approach

Microscopic traffic simulation tools are becoming increasingly popular in evaluating transport options. Driving behaviour models (e.g. route choice models, lane-changing models, etc.) are essential components of these tools. The state-of-the-art driving behaviour models assume that drivers make instantaneous decisions. However, in reality, many of the driving decisions are based on a specific plan. The plan is however unobserved or latent and only the manifestations of the plan through actions are observed. Examples include selection of a target lane before execution of the lane change, choice of a merging tactic before execution of the merge. Ignoring the effect of plans in the decision framework can lead to incorrect representation of congestion in traffic simulation tools. In this article, we present a modelling methodology to address the effects of unobserved plans in the decisions of the drivers. The actions of the driver are conditional on the current plan and can be influenced by anticipation of downstream traffic conditions. The heterogeneity in decision making and planning capabilities of drivers are explicitly addressed. The methodology has been applied in developing lane-changing behaviour models with disaggregate trajectory data extracted from video recordings of an urban road using the maximum likelihood technique. Estimation results show that the latent plan models have a significantly better goodness-of-fit compared to the ‘reduced form’ models where the latent plans are ignored. The latent plan models were also found to outperform the reduced form models in validation case studies within the microscopic traffic simulator MITSIMLab.

Mobility and Safety Evaluation Methodology for the Locations of Hi-PASS Lanes Using a Microscopic Traffic Simulation Tool

The number of Hi-Pass lanes became 793 lanes at 316 expressway tollgates in 2011 due to the increase in the Hi-Pass use. In spite of the increase in the number of Hi-Pass lanes, there have been increased potential risks in tollgates where vehicles using a Hi-Pass lane must weave with other vehicles using a TCS lane. Therefore, there is a need for study on the safety in tollgates. To this end, this study aims at developing a methodology to evaluate the performance measures of diverse location countermeasures of Hi-Pass lanes in an efficient and systematic way. This study measured the mobility, safety and the convenience of installation and operation of Hi-Pass lanes using a microscopic traffic simulation tool, the surrogate safety assessment model and survey. In addition, this study aggregated the above three performance indexes using weight factors estimated using the AHP technique. For the test site, Dongsuwon interchange was selected. After building the microscopic traffic simulation model for the test site, the location countermeasures of Hi-Pass lanes applicable to the test site were compared with each other in terms of the mobility, safety and installing and operating convenience. As a result, there has been no apparent difference in mobility index based on delays. However, the countermeasures where Hi-Pass lanes are located in inside lanes generally showed better safety performance based on the number of conflicts. In addition, countermeasures with neighboring Hi-Pass lanes were favorable in terms of the safety and the convenience of installation and operation. The methodology proposed in this study was found to be useful to support decision makings by providing critical and quantitative information regarding the mobility, safety and the convenience of installation and operation.

Mobility and Safety Evaluation Methodology for the Locations of Hi-PASS Lanes Using a Microscopic Traffic Simulation Tool

Mobility and Safety Evaluation Methodology for the Locations of Hi-PASS Lanes Using a Microscopic Traffic Simulation Tool

Modeling pedestrian crossing activities in an urban environment using microscopic traffic simulation

Microscopic traffic simulation tools are increasingly being employed as an integral part of modeling vehicular traffic and pedestrian activity. However, the complexity of pedestrians’ behaviors and their interactions with the various components of the traffic network is commonly under-represented in simulation models, resulting in potentially misleading analyses. This paper explores modeling pedestrians at the microscopic level, attempting to replicate observed pedestrian behavior at a crosswalk in Midtown Atlanta, GA. The VISSIM® simulation tool, with pedestrian movement based on the Social Force Model by Helbing and Molnár (Social Force Model for pedestrian dynamics. Phys Rev E 1995; 51: 4282-4286), is utilized. Comparative results of field observations and the microscopic modeling of the same vehicle and pedestrian activity are presented. A primary observation is that, for the intersection studied, only a small percentage of pedestrians appear to comply with the pedestrian signal indication, with the vast majority of pedestrians exhibiting gap-seeking behavior, crossing when a gap is available, regardless of the signal indication. This results in potentially significant over-estimates of wait time if high pedestrian signal compliance rates are assumed. A second notable observation is that the pedestrian crossing behavior is strongly related to the cross-street traffic queue clearance time and subsequent traffic flow. Capturing this interaction significantly enhances the models’ ability to reflect the observed field performance.

Analysis of Real-World Lead Vehicle Operation for Modal Emissions and Traffic Simulation Models

New models and data are needed in microscopic traffic simulation tools to allow effective use with newer modal tailpipe emissions models. Traffic simulation models offer the ability to simulate large, second-by-second vehicle operation data sets as input for emissions models. However, more data are needed to improve simulation of second-by-second vehicle speed. This research analyzes and models the vehicle dynamics of unconstrained drivers in real-world driving situations based on road geometry. Vehicle dynamics data were collected by using an instrumented vehicle driven by 22 volunteers over a 17-mi predetermined test route. The objective of this research was to analyze and model the nonrandom speed variations in unconstrained lead drivers. The results of this study suggest that horizontal and vertical curvatures have a significant impact on the second-by-second operation of an unconstrained lead vehicle. Furthermore, these nonrandom changes in speed are important considerations since they can produce considerable variations in the level of tailpipe emissions.

Simulation-Based Investigation on High-Occupancy Toll Lane Operations for Washington State Route 167

High-occupancy toll (HOT) lane operation has been implemented in several urban areas in the United States and is regarded as one of the most effective management strategies against freeway congestion. By allowing single occupancy vehicles (SOVs) to pay a toll for using high-occupancy vehicle (HOV) lanes, the excess capacities of HOV lanes can be used and the overall traffic mobility of the roadway section can be improved. However, research on HOT lane operations is still in its early stage. A series of theoretical and practical issues on optimizing HOT lane system performance particularly require immediate attention for better practice. Simulation-based investigation on HOT lane operations provides a cost-effective, risk-free, and prospective means of exploring and addressing these issues. A microscopic traffic simulation tool, VISSIM, is exploited in this study. By overcoming functional constraints with the VISSIM built-in modules and taking advantage of its component object model interface, we develop a new external module to enable HOT lane simulation. This HOT lane module provides additional flexibility to satisfy any specific demands from particular researchers and practitioners. Based on this external module, HOT lane operations can be simulated and evaluated as demonstrated using the Washington State Route (SR) 167 HOT Lane Pilot Project. The SR-167 simulation results not only quantitatively evaluate the overall system performance but also identify potential problems. Significantly different operational performance was illustrated between HOV lane and HOT lane systems using the developed simulation models. The simulation platform used in this study has the potential to be a cost-effective evaluation tool for HOT lane operations.

Modelling drivers' compliance and route choice behaviour in response to travel information

This paper addresses commuters' route choice behaviour in response to traveller information systems. The data used in this study was obtained from a field behavioural survey of drivers that was conducted on a congested commuting corridor in Brisbane, Australia. Agent-based neural network models (Neugents) were used to analyse the impacts of socio-economic, context and information variables on individual behaviour and propensity to change route and adjust travel patterns. The results from these models clearly indicate that prescriptive, predictive and quantitative real-time delay information provided for both the usual and best alternate routes are most effective in influencing commuters to change their routes. The Neugent behavioural models describing drivers' dynamic route choice decision making were also implemented within a microscopic traffic simulation tool to evaluate the corridor-wide impacts of providing drivers with real-time traffic information. The simulation results support the notions that commuters' decisions to divert to alternate routes are influenced by their socio-economic characteristics; the degree of familiarity with network conditions and the expectation of an improvement in travel time that exceeds a certain delay threshold associated with each commuter. An evaluation of the benefits of the Neugent model over static route choice algorithms which do not consider dynamic driver behaviour and compliance with travel advice showed improvements of 4–7% in network speeds; 5–8% in network delays; 7–11% in stop time per vehicle and 1–3% in network travel times.

Comparative Evaluation of Microscopic Car-Following Behavior

Microscopic traffic-simulation tools are increasingly being applied to evaluate the impacts of a wide variety of intelligent transport systems (ITS) applications and other dynamic problems that are difficult to solve using traditional analytical models. The accuracy of a traffic-simulation system depends highly on the quality of the traffic-flow model at its core, with the two main critical components being the car-following and lane-changing models. This paper presents findings from a comparative evaluation of car-following in a number of traffic simulators [advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN), parallel microscopic simulation (PARAMICS), and Verkehr in Stadten-simulation (VISSIM)]. The car-following algorithms used in these simulators have been developed from a variety of theoretical backgrounds and are reported to have been calibrated on a number of different data sets. Very few independent studies have attempted to evaluate the performance of the underlying algorithms based on the same data set. The results reported in this study are based on a car-following experiment that used instrumented vehicles to record the speed and relative distance between follower and leader vehicles on a one-lane road. The experiment was replicated in each tool and the simulated car-following was compared to the field data using a number of error tests. The results showed lower error values for the Gipps-based models implemented in AIMSUN and similar error values for the psychophysical spacing models used in VISSIM and PARAMICS. A qualitative drift and goal-seeking behavior test, which essentially shows how the distance headway between leader and follower vehicles should oscillate around a stable distance, also confirmed the findings.