Showing papers on "Traffic simulation published in 2023"
TL;DR: In this article , a force-based approach is proposed to simulate the complex behaviors of all potential road users in a realistic urban environment, which can accurately replicate the sophisticated behaviors of various road users and their interactions in a simple and unified manner.
Abstract: Virtual traffic benefits a variety of applications, including video games, traffic engineering, autonomous driving, and virtual reality. To date, traffic visualization via different simulation models can reconstruct detailed traffic flows. However, each specific behavior of vehicles is always described by establishing an independent control model. Moreover, mutual interactions between vehicles and other road users are rarely modeled in existing simulators. An all-in-one simulator that considers the complex behaviors of all potential road users in a realistic urban environment is urgently needed. In this work, we propose a novel, extensible, and microscopic method to build heterogeneous traffic simulation using the force-based concept. This force-based approach can accurately replicate the sophisticated behaviors of various road users and their interactions in a simple and unified manner. We calibrate the model parameters using real-world traffic trajectory data. The effectiveness of this approach is demonstrated through many simulation experiments, as well as comparisons to real-world traffic data and popular microscopic simulators for traffic animation.
6 citations
19 Apr 2023
TL;DR: In this paper , an overview of the selected work on the topic of emission modelling and vehicle traffic simulation models is presented, as well as development trends in the field and the fact of proper calibration of vehicle traffic simulators in order to obtain the most reliable vehicle emissions results.
Abstract: Accurate estimation of vehicle emissions is essential and can be helpful in the decision-making process. Thanks to calculation methods, it is possible to accurately estimate the emissions that result from driving a car and to determine their impact on, for example, the health of pedestrians who are on the pavement near an arterial road. Recent years have seen an increase in the use and importance of emission models, as well as vehicle traffic simulation models. Increasingly, emission models are being combined with traffic simulation models, as it is not practical to actually measure the on-road emissions of an entire fleet of vehicles over a given stretch of road. This paper provides an overview of the selected work on the topic of emission modelling and vehicle traffic simulation models. The models are distinguished according to their respective scales of accuracy, i.e., micro, meso, and macro. Selected work combining emission and traffic simulation models is also presented, as well as development trends in the field. In particular, the paper also highlights the fact of proper calibration of vehicle traffic simulation models in order to obtain the most reliable vehicle emissions results from computational models. The review of the works carried out may be helpful for future projects concerning the use of simulation tools for transport and environmental decision-makers in the area of arterial roads.
1 citations
TL;DR: In this article , the authors investigated the impacts of the AVs emergence on traffic performance for the city of Budapest in three future traffic scenarios with different AV market replacement rates for the year 2030.
Abstract: Traffic and transport researchers, policymakers, and vehicle manufacturers are interested in investigating the implications and the influence of autonomous vehicles (AV) because a gradual deployment of such new technologies is expected to take place in the future. This research investigates the impacts of the AVs emergence on traffic performance for the city of Budapest in three future traffic scenarios with different AV market replacement rates for the year 2030. The network was modeled using simulation-based dynamic traffic assignment in PTV Visum software. Four traffic performance parameters were analyzed to explore the impacts of AV's emergence on the network. The results showed noticeable improvements among the four investigated traffic performance parameters.
1 citations
TL;DR: In this paper , the authors reviewed literature that is closely related to crash analysis based on crash reports and to simulation of mixed traffic when CAVs and human-driven vehicles co-exist, for studying traffic safety.
1 citations
TL;DR: In this paper , the authors evaluated the operational performance of Transit Signal Priority (TSP) using a microscopic simulation approach, based on a 10-mile study corridor in South Florida.
Abstract: This study evaluated the operational performance of Transit Signal Priority (TSP) using a microscopic simulation approach. The analysis was based on a 10-mile study corridor in South Florida. Two microscopic VISSIM simulation models were developed: a Base model, calibrated and validated to represent field conditions, and a TSP model. With TSP, the study corridor experienced up to 8 % reduction in travel times and up to 13.3 % reduction in average vehicle delay time, for both buses and all other vehicles. To better quantify the mobility benefits of the TSP strategy, Mobility Enhancement Factors (MEFs) were developed, unlike previous studies. A MEF is a multiplicative factor to estimate the expected mobility level after implementing TSP at a specific site. A MEF < 1 implies that the TSP yields mobility benefits. TSP’s impact on cross-streets were also estimated. The study results indicate TSP strategy has enhanced mobility for buses and all other vehicles.
1 citations
TL;DR: In this paper , the authors compared the differences in driving behaviors of CVs depending on whether V2V-based forward collision warning information was provided, and a methodology was proposed to simulate the driving behaviors in VISSIM environments.
Abstract: Vehicle-to-vehicle (V2V)-based forward collision warning is a core connected vehicle (CV) service for preventing traffic crashes. Since the driver’s reaction affects the surrounding traffic conditions, an analysis of the effects of the CV application is required in terms of traffic stream performance. This study compared the differences in driving behaviors of CVs depending on whether V2V-based forward collision warning information was provided. The driving characteristics of CVs based on the analysis of probe vehicle data (PVD) were defined, and a methodology was proposed to simulate the driving behaviors of CVs in VISSIM environments. Additionally, the effectiveness of improving mobility and traffic safety by various market penetration rates (MPRs) of CVs in an accident situation was identified by evaluating the average travel speed and time-to-collision (TTC)-based crash risk. The simulation results for the two-lane blocking accident scenario indicated that the average speed increased by 23.18% with an MPR of 100%, and the TTC-based crash risk decreased by 18.34% compared with an MPR of 0%. It has been demonstrated that V2V-based warning information is useful for not only safety benefits but also mobility improvement. The results of this study could be employed as fundamentals to establish various policies to expedite the implementation of CV systems in practice. In addition, it is suggested that the outcome of this study will be useful for developing traffic flow management strategies technology to improve traffic safety.
TL;DR: In this article , the authors investigated the impacts of AV implementation on the performance of a signalized intersection considering a mixed traffic environment comprising regular vehicles (RVs) and AVs through microscopic traffic simulations.
Abstract: Autonomous driving can overcome the limitations of stochastic human driving behavior. Therefore, implementing autonomous vehicles (AVs) could improve the efficiency of road networks. This study investigates the impacts of AV implementation on the performance of a signalized intersection considering a mixed traffic environment comprising regular vehicles (RVs) and AVs through microscopic traffic simulations. Accordingly, 24 scenarios with different AV implementation rates, AV driving models, and traffic volume conditions, were developed and evaluated using the Vissim simulation software. The results indicated that even partial AV implementation could improve the operational efficiency of a signalized intersection compared to full RV traffic. AV implementation reduced the vehicle delay, stopped delay, and queue length. The expected improvements are primarily based on the implementation rate, and are higher at higher rates (≥50%). The improvements are highest at moderate traffic volumes. Compared to the moderate level, partially replacing RVs with AVs at free-flow conditions does not significantly impact the performance of the intersection. Under congested conditions, the expected improvements from AV implementation are mitigated by the high traffic volumes. Considering the different AV models employed herein, the connected autonomous vehicle (CAV) model exhibited the best performance.
13 Jun 2023
TL;DR: The Flexible Interface for X-in-the-loop Simulation (FIXS) as mentioned in this paper supports the co-simulation of microsimulation, CAV control algorithm, and vehicle dynamics model in Simulink.
Abstract: Connected and automated vehicles (CAVs) have the potential to improve many aspects of the current transportation systems such as safety, mobility, and energy efficiency. In order to evaluate the benefits and impacts of a CAV, the CAV control algorithm is typically implemented on vehicles simulated in a traffic microsimulation environment. However, traffic microsimulation usually lacks detailed vehicle and powertrain dynamics, making it challenging to fully understand how a CAV control algorithm will perform and respond on an actual vehicle. Whether the same benefits measured in the simulation will also be observed in real-world remains an open question. One potential approach to fill in this gap is to conduct a co-simulation of traffic microsimulation with detailed vehicle and powertrain dynamics models, often developed in MATLAB Simulink. However, current microsimulation tools such as VISSIM and SUMO do not have a ready-to-use interface for co-simulation with vehicle dynamics and Simulink. Also, even if such an interface exists, it will be tool-specific, making it challenging to shift from one tool to another or test CAV controls in different tools. There are needs for tool-agnostic co-simulation as different microsimulation tools have their pros and cons, and researchers often need to use different tools based on the purposes of the simulation, project needs, and applications. In this work, Flexible Interface for X-in-the-loop Simulation (FIXS) is developed that can support the co-simulation of microsimulation, CAV control algorithm, and vehicle dynamics model in Simulink. Enabled by the FIXS, the benefit and performance of a CAV control algorithm can be better understood with the consideration of vehicle responses and dynamics. The connection to VISSIM and SUMO is handled internally by the interface, and users can easily switch tools by changing a configuration file. The co-simulation capability is demonstrated for a VISSIM eco-approach and departure CAV scenario and a SUMO cooperative merging scenario for both a passenger CAV and a class 8 heavy-duty connected and automated trucks.
TL;DR: In this article , the authors present a traffic model to simulate network-level traffic evolution under the impact of controlled autonomous vehicles acting as moving bottlenecks and calculate the cumulative number of vehicles passing each moving bottleneck.
Abstract: In this work we present a traffic model to simulate network-level traffic evolution under the impact of controlled autonomous vehicles acting as moving bottlenecks. We first extend the Newell-Daganzo method to track the trajectories of moving bottlenecks and calculate the cumulative number of vehicles passing each moving bottleneck. By integrating the solutions to the cumulative number of vehicles passing moving bottlenecks and link nodes as boundary conditions in the link-transmission model, we can incorporate the impact of moving bottlenecks into the flow of traffic at a network scale. We present numerical simulation results that illustrate the effectiveness of the developed model to track the trajectories of the moving bottlenecks and simulate their impact on freeway traffic. Lastly, we present control applications of the developed model to trajectory optimization. The reduced fuel consumption associated with the careful control of AV trajectories in the moving bottleneck framework indicates the potential to considerably improve the flow of traffic by controlling the AVs in a mixed human and autonomous environment.
TL;DR: WorkZoneQ-Pro as discussed by the authors is developed with a new signal timing method that considers the above-mentioned factors and can handle multiple hours of analysis with two- or three-phase signal operations.
Abstract: Work zones on two-lane highways with one lane closed require sharing the open lane with traffic from the closed directions. In such work zones, traffic control resembles operating a two-phase traffic signal and, in rare cases, a three-phase traffic signal. Temporary traffic signals (or flaggers) allow the open lane to be used in an alternating manner. Signal timing (green times and cycle length) of the temporary traffic lights directly affects the delay and queue in the work zones. Delay and queue computations must consider queue build up that often happens in oversaturated conditions. Another influential variable is the average operating speed of the work zone. The operating speed is affected by the work zone speed limit, work intensity, speed control technique, lane and shoulder widths, acceleration capability of vehicles, and work zone length. WorkZoneQ-Pro (WZQ-Pro) is developed with a new signal timing method that considers the above-mentioned factors. The procedure can handle multiple hours of analysis with two- or three-phase signal operations. Test scenarios are real-world work zone examples from three different U.S. states that were used to compute signal time variables and use them to compute queue and delay. These values were also computed using Highway Capacity Manual (HCM) 2016 procedures and are compared. In addition, the computed values were input into Vissim simulation software, and the results were compared. It showed that the WZQ-Pro results are reasonably close to Vissim simulation results, and that further validated that an acceptable agreement existed between the analytical and simulation results.
TL;DR: In this article , the VISSIM traffic model was selected for calibration and field measurements were carried out on two roundabouts in a local urban transport network, where the applicability of neural networks in the process of calibrating the microsimulation models was confirmed by comparison of the modelled and measured data of traffic indicators in real traffic conditions.
Abstract: The efficacy of the application of traffic models depends on a successful process of model calibration. Microsimulation models have a significant number of input parameters that can be optimized in the calibration process. This paper presents the optimization of input parameters that are difficult to measure or unmeasurable in real traffic conditions and includes parameters of the driver’s behavior and parameters of Wiedemann’s psychophysical car-following model. Using neural networks, models were generated for predicting travel time and queue parameters and were used in the model calibration procedure. This paper presents the results of a comparison of five different applications of neural networks in calibrating the microsimulation model. The VISSIM microsimulation traffic model was selected for calibration and field measurements were carried out on two roundabouts in a local urban transport network. The applicability of neural networks in the process of calibrating the microsimulation models was confirmed by comparison of the modelled and measured data of traffic indicators in real traffic conditions. Methods of calibration were validated with two sets of new measured data at the same intersection where the calibration of the model was carried out. The third validation was made at the intersection in a different location. The selection of the optimal calibration methodology is based on the model accuracy between the simulated and measured data of traveling time, as well as queue parameters. The microsimulation model provides access to the raw data of observed traffic parameters for each vehicle in the simulation. The dataset of the calibrated model simulation results of all travel times of the selected traffic flow was compared with the dataset of the measured field data to determine whether the data are statistically significantly different or not.
TL;DR: In this paper , the authors benchmark three European microscopic simulation software's ability to reproduce congested patterns at merges and diverges by comparing their macroscopic outputs to validated analytical formulations.
Abstract: Abstract Purpose We benchmark three European microscopic simulation software’s ability to reproduce congested patterns at merges and diverges by comparing their macroscopic outputs to validated analytical formulations. The capacity drop and, in the specific case of merges, the priority ratio are assessed. At the microscopic scale, the spatial distribution of lane changes at merges is examined. Method A single reference state is built for all three simulation tools. A point-based diverge and an extended merge are reproduced in the simulation tools. Under traffic conditions ranging from free-flow to congestion, vehicles counts and vehicles trajectories are collected to compute the selected indicators, which help to conclude for the considered reference state. Results The considered simulation tools correctly reproduce the merges and diverges elementary behaviors. However, their default configuration does not, entirely or partially, reproduce the traffic conditions induced by insertions and desertions as predicted by the analytical models. Discussion The study could be enriched by including the benchmark of other simulation tools. In addition, the networks studied are elementary and may not reflect completely the traffic situations encountered on the highways.
TL;DR: In this paper , a simulation of vehicle traffic was carried out for three options on the section of the public road of national importance M-06, and it was proved that transport modeling can be used to analyze various options for developing traffic management measures, in particular, solving the issue of congestion on a particular section of a road.
Abstract: Introduction. The destruction of the road network has been going on for more than a year. In this regard, there is a need to restore traffic conditions both in settlements and on the public road network. The solution to this problem should be based on the definition of the criterion for the formation of safe and continuous traffic conditions based on the use of modern traffic flow models. Problems. Improving traffic management using transport modeling in the PTV VISSIM software environment. Taking into account such criteria as throughput and delay. Purpose. Development of a model for the distribution of traffic flows on the road network. Research methods. Analytical and experimental with the use of computer simulation modeling. Results. A simulation of vehicle traffic was carried out for three options on the section of the public road of national importance M-06. The first option took into account the existing traffic conditions on the road section, the second option - in case of an obstacle to traffic in the existing conditions, and the third option - with the implementation of the proposed measures. As a result of the modeling, it was found that under existing conditions, the average speed is 50 km/h, the average delay time is 20.46 seconds, but if an obstacle to traffic appears, the average delay time increases and is 156 seconds, and the average speed, respectively, decreases and is 37 km/h. With the implementation of measures, namely the introduction of the distribution of traffic flows along different routes (bypassing the obstacle), the average delay time decreased compared to option two and is 54.67 s, and the average speed increased by 11.64 km/h. Conclusions. As a result of the work performed, it was proved that transport modeling can be used to analyze various options for developing traffic management measures, in particular, solving the issue of congestion on a particular section of the road. Transportation modeling allows simulating the division of traffic flows into alternative routes and evaluating them according to established criteria. As a result, traffic delays and waiting times are reduced, which significantly affects traffic capacity, road safety, and has a positive socio-economic effect.
TL;DR: In this article , an innovative method based on shockwave theory and the volume delay function adapted from the Highway Capacity Manual (7th edition) is proposed to measure demand directly with vehicle sensors, as the queue grows beyond the sensor, and flow measurements at a given point cannot exceed the capacity of the section.
Abstract: Measuring demand directly with vehicle sensors is not possible when demand is larger than capacity for an extended period, as the queue grows beyond the sensor, and the flow measurements at a given point cannot exceed the capacity of the section. The main objective of this study is to develop methods that could be implemented in practice based on readily available data. To this end, two methods are proposed: an innovative method based on shockwave theory and the volume delay function adapted from the Highway Capacity Manual (7th edition). Both methods primarily rely on probe vehicle speeds (e.g., from INRIX) as the input data and the capacity of the segment or bottleneck being analyzed. Probe vehicle data are used to determine the critical times when the queue reaches the end or beginning of a road segment. From these critical times, the shockwave speed for the boundary between congested (high density) traffic and arriving (low density) traffic is estimated. The proposed methods are tested with simulation data generated in VISSIM and validated based on volume data from the field. The field data are collected from a congested arterial in Virginia Beach, VA, and include the ground truth volumes and INRIX speed data aggregated at one-minute intervals. The results show that both methods are effective for estimating the demand volume and produce less than 4% error when tested with field data.
TL;DR: Kimarite as discussed by the authors is an automated vehicle model for microscopic traffic simulation tools, which is developed with the open-source traffic simulation software Simulation of Urban Mobility (SUMO) and evaluated in common traffic interaction scenarios with bicyclists.
Abstract: With the undeniable advance of automated vehicles and their gradual integration in day-today urban traffic, many new technologies have been developed that offer great potential for this emerging field of research. However, testing automated vehicle technologies in real road traffic with vulnerable road users (VRUs) is still a complicated and time consuming procedure. The virtual development and evaluation of automated vehicles using simulation tools offers a good opportunity to test new functions efficiently. However, existing models prove to be insufficient in modeling the interaction between autonomous vehicles and vulnerable road users such as bicyclists and pedestrians. In this paper, an automated vehicle model for microscopic traffic simulation tools is developed with the open-source traffic simulation software Simulation of Urban Mobility (SUMO) and evaluated in common traffic interaction scenarios with bicyclists. A controller model is proposed using different path-finding algorithms from the field of robotic and automated vehicle research, which covers all important control levels of a self-driving vehicle. Finally, its performance is compared to existing car-following and lane-changing models. Results showcase that the autonomous vehicle model achieves either comparable results or has a much steadier and more realistic driving behavior when compared to existing driving models while interacting with bicyclists. The whole source code developed over the course of this work is freely accessible at: https://github.com/FlixFix/Kimarite.
03 May 2023
TL;DR: In this paper , a microscopic simulation approach was used to estimate the mobility and safety benefits of TSP, and the importance and benefits of calibration of VISSIM model with TSP integration were also studied.
Abstract: The continuous growth of automobile traffic on urban and suburban arterials in recent years has created a substantial problem for transit, especially when it operates in mixed traffic conditions. As a result, there has been a growing interest in deploying Transit Signal Priority (TSP) to improve the operational performance of arterial corridors. TSP is an operational strategy that facilitates the movement of transit vehicles (e.g., buses) through signalized intersections that helps transit service be more reliable, faster, and more cost-effective. The goal of this research was to quantify the mobility and safety benefits of TSP. A microscopic simulation approach was used to estimate the mobility benefits of TSP. Microscopic simulation models were developed in VISSIM and calibrated to represent field conditions. Implementing TSP provided significant savings in travel time and average vehicle delay. Under the TSP scenario, the study corridor also experienced significant reduction in travel time and average vehicle delay for buses and all other vehicles. The importance and benefits of calibration of VISSIM model with TSP integration were also studied as a part of the mobility benefits. Besides quantifying the mobility benefits, the potential safety benefits of the TSP strategy were also quantified.
TL;DR: In this paper , the authors present a built-in model integrated into the GAMA open-source modeling and simulation platform, allowing the modeler to easily define traffic simulations with a detailed representation of the driver's operational behaviors.
Abstract: Continuous improvement in computing power allowed for an increase of the scales micro-traffic models can be used at. Among them, agent-based frameworks are now appropriate for studying ordinary traffic conditions at city-scale, but remain difficult to adapt, especially for non-computer scientists, to more specific application contexts (e.g., car accidents, evacuation following a natural disaster), that require integrating particular behaviors for the agents. In this paper, we present a built-in model integrated into the GAMA open-source modeling and simulation platform, allowing the modeler to easily define traffic simulations with a detailed representation of the driver’s operational behaviors. In particular, it allows modelling road infrastructures and traffic signals, change of lanes by driver agents and less normative traffic mixing car and motorbike as in some South East Asian countries. Moreover, the model allows to carry out city-level simulations with tens of thousands of driver agents. An experiment carried out shows that the model can accurately reproduce the traffic in Hanoi, Vietnam.
01 Jan 2023
TL;DR: In this article , the authors presented a large-scale simulation scenario depicting a full day of motorized private traffic for the City of Berlin, with the traffic demand extracted from an existing MATSim scenario and transferred to SUMO using iterative traffic assignment.
Abstract: Research on novel concepts in the field of smart mobility and ITS requires employing traffic simulations in combination with communication and application simulations. With Eclipse MOSAIC we developed a co-simulation simulation framework to setup holistic system simulations in that very field, by coupling best-in-class simulators from various research domains. One important task here is modeling road traffic, which is non-trivial on a large scale. Traffic for a city-wide area can be modeled on a macroscopic or microscopic level, however, only the later provides realistic vehicle movements which is a requirement for communication and application simulation. Currently, there are only a handful of scenarios that model enough traffic to reliably test smart mobility applications. In this paper, we describe how we created a large-scale simulation scenario depicting a full day of motorized private traffic for the City of Berlin. To achieve this, we created a scenario for the microscopic traffic simulator SUMO, with the traffic demand extracted from an existing MATSim scenario and transferred to SUMO using iterative traffic assignment. Comparing the simulated counts with real data emphasizes that this scenario can model traffic in Berlin close to reality. With more than 2.2 million trips within an area of 800 km2 this is the largest traffic scenario we are currently aware of, and we will provide it for other researchers under an open-source license.
TL;DR: In this article , the authors identify the optimal queue detector locations on all approaches at two selected roundabouts in Amman, Jordan, using micro-simulation (VISSIM) supported by programming (Python) software, and validate the simulated models with the best LOS.
Abstract: The growing number of vehicles in Jordan has contributed to traffic congestion, particularly at roundabouts. Roundabouts deflect high volumes of traffic flow. To improve the performance of roundabouts, it is necessary to consider the impact of all components on traffic conditions, especially delay, queue length, and level of service (LOS), to reduce congestion and enhance efficiency and sustainability, etc. This study aims to (a) identify the optimal queue detector locations on all approaches at two selected roundabouts in Amman, Jordan, using micro-simulation (VISSIM) supported by programming (Python) software, and (b) validate the simulated models with the best LOS. Traffic and geometric data of roundabouts (Prince Faisal Bin al-Hussein, fifth; and Prince Rashid Bin Hassan, sixth roundabouts) were used for simulation purposes. The queue detector (across 15 distinct scenarios at various distances) and standard (base scenario, 50 m from the stop line) locations were assessed for optimal placement. The model validation was made based on all scenarios including signalized and non-signalized roundabouts. The best-case scenario for queue detector location was determined based on the highway capacity manual (HCM) criteria for measurement of effectiveness (MOE) at roundabouts. The optimal location was measured based on the duration of traffic delay (seconds), average queue length (m), and LOS. The optimal queue detector’s location was observed to be 97 m from the roundabout stop line. It can reduce the traffic delay (or speed up the traffic flow) by 85.25%. The average queue length can be reduced up to 76.76%. The LOS F status on the selected roundabouts can be improved to LOS D. Overall, the application of adaptive signal and queue detectors in appropriate locations at all roundabout approaches is crucial to improve imbalanced traffic flow while reducing delays.
TL;DR: In this article , the authors evaluated the feasibility of implementing an ANN-based gap acceptance model in SUMO, using its application programming interface, and concluded that the advantage of the ANNbased model lies not only in the accuracy of the selected output variables in comparison to the observed field values, but also in the realistic vehicle crossings at uncontrolled intersections in the simulation model.
Abstract: The impact of various operational and design alternatives at roundabouts and traffic circles can be evaluated using microscopic simulation tools. Most microscopic simulation software utilizes default underlying models for this purpose, which may not be generalized to specific facilities. Since the effectiveness of traffic operations at traffic circles and roundabouts is highly affected by the gap rejection–acceptance behavior of drivers, it is essential to accurately model drivers’ gap acceptance behavior using location-specific data. The objective of this paper was to evaluate the feasibility of implementing an artificial neural network (ANN)-based gap acceptance model in SUMO, using its application programming interface. A traffic circle in New Jersey was chosen as a case study. Separate ANN models for one stop-controlled and two yield-controlled intersections were trained based on the collected ground truth data. The output of the ANN-based model was then compared with that of the SUMO model, which was calibrated by modifying the default gap acceptance parameters to match the field data. Based on the results of the analyses it was concluded that the advantage of the ANN-based model lies not only in the accuracy of the selected output variables in comparison to the observed field values, but also in the realistic vehicle crossings at the uncontrolled intersections in the simulation model.
TL;DR: In this paper , the authors present the possibility of utilizing an open-sourced real-time web-based platform linking simulation results to dashboards, where traffic flow at intersections and location information of individual vehicles are stored in the cloud from VISSIM at analysis intervals.
08 May 2023-Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
TL;DR: In this paper , the authors consider whether further reduction in delay could be gained by applying this predictive model to dynamically reroute some portion of vehicles willing to share their destinations along less congested paths.
Abstract: Roadway congestion leads to wasted time and money and environmental damage. Since adding more roadway capacity is often not possible in urban environments, it is becoming more important to use existing road networks more efficiently. Toward this goal, recent research in real-time, schedule-driven intersection control has shown an ability to significantly reduce the delays incurred at signalized intersections. Such approaches operate by building a predictive model of when locally sensed approaching traffic is expected to arrive at a given intersection, and then using the model to generate a signal timing plan (a phase schedule) that minimizes the cumulative delay of this traffic as it moves through the intersection. In this paper, we consider whether further reduction in delay could be gained by applying this predictive model to dynamically reroute some portion of vehicles willing to share their destinations along less congested paths. We developed an algorithm that simulates the current traffic state forward at each vehicle decision point, based on knowledge of other vehicles’ current routes and traffic signals’ control algorithms, and evaluated it using the SUMO microscopic simulator on different road networks (one as a simple synthetic example and the other taken from the real world) using different traffic signal control algorithms (fixed-timing plans and schedule-driven intersection control). Experiments carried out on combinations of networks and traffic signal control algorithms show that our rerouting protocol reduces delay for both vehicles participating in route guidance (adopters) and those that do not (non-adopters) and that the reduction in delay generally increases as the proportion of adopters does.
TL;DR: In this paper , the authors compared field data with simulation data to evaluate traffic performance by comparing simulation results with direct observations in the field, and the results obtained from using VISSIM can be reliable and helpful in designing and optimizing urban transportation systems in the future.
Abstract: This research aims to calibrate and validate the VISSIM simulation model tool by comparing field data with simulation data. The ultimate goal is to evaluate traffic performance by comparing simulation results with direct observations in the field. This study uses modeling to determine a road segment's maximum flow volume. This study was conducted in Makassar, South Sulawesi, Indonesia, on Jalan Veteran Selatan. The method uses two main inputs: urban road primary capacity data from the Indonesian Highway Capacity Manual (IHCM 1997) and roadside activity data from PTV VISSIM. The GEH and MAPE have commonly used metrics for measuring the accuracy of simulation models and calibration measurements using driving behavior parameters. The research results obtained for validation measurements have met the requirements. Namely, the obtained MEPE value (7.38%) is 10% smaller than the obtained GEH value (2.032 and 3.961), which is still more than 5.00. The calibration measurements obtained the suitability of the vehicle location and intervehicle spacing in the simulation model (VISSIM) with the actual field conditions. The results obtained from using VISSIM can be reliable and helpful in designing and optimizing urban transportation systems in the future. It is essential to remember that traffic simulation with VISSIM is only a transportation decision-making and planning tool and must be combined with field observations and accurate data for adequate and efficient transportation solutions.
TL;DR: In this article , a co-simulation platform for studying driving behavior with multiple participants was presented, where different driving scenarios could be simulated and driver behavior could be recorded and analyzed.
Abstract: This paper presents the system development of a co-simulation platform aimed at studying driving behavior with multiple participants. The objective of this study was to create an immersive and interactive environment where different driving scenarios could be simulated and driver behavior could be recorded and analyzed. The platform integrated the Unity game engine with the VISSIM microscopic traffic simulator to create a hybrid simulation environment that combined the advantages of both tools. A virtual reality massive multiplayer online (VRMMO) module was developed to capture the interactions of the participants during the simulation experiments. The external control devices of this co-simulation platform were calibrated using the empirical data of a Controller Area Network (CAN-BUS) from actual driving behaviors. The main contributions of this study are the demonstration of the Unity–VISSIM co-simulation platform in simulating interactive driver behavior and the potential for its use in various research areas, such as intelligent transportation systems, human factors, driving education, and traffic safety analyses. The platform could be a valuable tool for evaluating the effectiveness of collective intelligence countermeasures in improving traffic systems, with relatively lower costs and risks.
TL;DR: In this article , different aspects of simulating bicycle traffic in SUMO are examined and an overview of the results of the workshop discussions is given. And some suggestions for the future development of SUMO emerging from this workshop, are presented as a conclusion.
Abstract: Microscopic traffic simulation tools provide ever-increasing value in the design and implementation of motor vehicle transport systems. Research and development of automated and intelligent technologies have highlighted the usefulness of simulation tools and development efforts have accelerated in recent years. However, the majority of traffic simulation software is developed with a focus on motor vehicle traffic and has limited capabilities in the simulation of bicycles and other micro-mobility modes. Bicycles, e-bikes and cargo bikes represent a non-negligible modal share in many urban areas and their impact on the operation, efficiency and safety of traffic systems must be considered in any comprehensive study. The Differentiation between different types of micro-mobility modes, including microcars, e-kick scooters, different types of bicycles and other personal mobility devices, has not yet attracted enough attention in the development of simulation software which creates difficulties in including these modes in simulation-based studies. On November 25th, 2022, members of the SUMO team at DLR organized a workshop to assess the state of bicycle simulation in SUMO, identify shortcomings and missing capabilities and prioritize the order in which bicycle traffic related features should be modified or implemented in the future. In this paper, different aspects of simulating bicycle traffic in SUMO are examined and an overview of the results of the workshop discussions is given. Some suggestions for the future development of SUMO emerging from this workshop, are presented as a conclusion.
TL;DR: In this article , a Variable Speed Limit (VSL) system that utilizes fuzzy logic is presented, which adjusts the speed limits that connected vehicles must comply with by leveraging traffic data such as vehicle flow, occupancy and speed obtained from loop detectors installed along the road.
Abstract: This paper handles the problem of controlling speed limits on freeways in a connected traffic environment to reduce traffic congestion and improve both the operational and environmental performance of the road network. In order to achieve this objective, we present a Variable Speed Limit (VSL) system that utilizes fuzzy logic, which adjusts the speed limits that connected vehicles must comply with by leveraging traffic data such as vehicle flow, occupancy, and speed obtained from loop detectors installed along the road. To evaluate the effectiveness of the proposed Fuzzy-based VSL system and its potential benefits compared to the conventional rule-based VSL system in terms of traffic congestion and environmental impact, we conducted a simulation analysis using the microscopic traffic simulator, VISSIM. Specifically, three simulation scenarios are taken into account: i) no VSL, where the VSL system is not enabled; ii) Rule-based VSL system, where a typical a decision tree-based system is considered; iii) Fuzzy-based VSL system, where the herein proposed approach is appraised. The results demonstrate that the proposed approach enhances road efficiency by decreasing speed variation, increasing average speed and vehicle volume, and reducing fuel consumption.
TL;DR: In this paper , a sensitivity analysis was used to find the most sensitive driver behavior parameters and the optimum driver behavior parameter values for these identified most sensitive drivers behavior parameters were determined using the multiobjective GA optimization tool in the MATLAB software's optimization toolbox.
Abstract: Modeling effective vehicular traffic is a highly contested topic, especially in developing countries like Sri Lanka, which has a wide range of driving conditions. VISSIM microsimulation software is currently used by Road Development Authority (RDA) and relevant authorities to perform traffic management solutions in Sri Lanka. However, it is required to do modifications to the existing driver behavior parameter values to effectively reflect the realistic traffic conditions observed in the real-world in the simulated model. The main purpose of this study is to calibrate the VISSIM driver behavior parameter values using a genetic algorithm (GA). The methodology and results of the VISSIM model’s sensitivity analysis and calibration, which was developed for the Malabe three-legged signalized intersection, are presented in this study. A sensitivity analysis was used to find the most sensitive driver behavior parameters. Using the multi-objective GA optimization tool in the MATLAB software's optimization toolbox, the optimum driver behavior parameter values for these identified most sensitive driver behavior parameters were determined. The findings revealed that GA optimization is effective in reducing the difference between observed and simulated results.
31 May 2023
TL;DR: In this paper , the authors investigate existing simulation environments, identify use case scenarios, and create a cosimulation environment to satisfy the simulation requirements for autonomous driving function development using the Carla simulator.
Abstract: Increasing the implemented SAE level of autonomy in road vehicles requires extensive simulations and verifications in a realistic simulation environment before proving ground and public road testing. The level of detail in the simulation environment helps ensure the safety of a real-world implementation and reduces algorithm development cost by allowing developers to complete most of the validation in the simulation environment. Considering sensors like camera, LIDAR, radar, and V2X used in autonomous vehicles, it is essential to create a simulation environment that can provide these sensor simulations as realistically as possible. While sensor simulations are of crucial importance for perception algorithm development, the simulation environment will be incomplete for the simulation of holistic AV operation without being complemented by a realistic vehicle dynamic model and traffic cosimulation. Therefore, this paper investigates existing simulation environments, identifies use case scenarios, and creates a cosimulation environment to satisfy the simulation requirements for autonomous driving function development using the Carla simulator based on the Unreal game engine for the environment, Sumo or Vissim for traffic co-simulation, Carsim or Matlab, Simulink for vehicle dynamics co-simulation and Autoware or the author or user routines for autonomous driving algorithm co-simulation. As a result of this work, a model-based vehicle dynamics simulation with realistic sensor simulation and traffic simulation is presented. A sensor fusion methodology is implemented in the created simulation environment as a use case scenario. The results of this work will be a valuable resource for researchers who need a comprehensive co-simulation environment to develop connected and autonomous driving algorithms.
TL;DR: In this article , the authors describe a scenario in which a large number of people are living in a large environment, such as the US, Japan, China, and India, and the US.
Abstract: 北海道の地方都市では，深刻な人口減少に伴い，公共交通の利用者数が急速に減少しつつある．この課題に対し，公共交通サービスの向上を目的として，MaaS実証実験が各地で行われている．本研究では，北海道室蘭市を対象に，各種のオープンデータを活用したマクロ交通シミュレーションを構築し，将来的に維持すべきバス路線と将来的にオンデマンド交通を導入すべきエリアの抽出を行った．また，オンデマンド交通の導入が検討される室蘭市のオールドニュータウンである白鳥台地区において，令和3年度に実施されたオンデマンド交通導入実証実験のモニターアンケートデータと利用者の移動データを用いてシミュレーション分析を行うことで，住民が求めるサービスレベルとそれに応じたオンデマンド交通の必要運用台数を明らかにした．