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Keywords = traffic microsimulation tool

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26 pages, 11962 KB  
Article
A Microsimulation-Based Methodology for Evaluating Efficiency and Safety in Roundabout Corridors: Case Studies of Pisa (Italy) and Avignon (France)
by Lorenzo Brocchini, Antonio Pratelli, Didier Josselin and Massimo Losa
Infrastructures 2025, 10(7), 186; https://doi.org/10.3390/infrastructures10070186 - 17 Jul 2025
Viewed by 743
Abstract
This research is part of a broader investigation into innovative simulation-based approaches for improving traffic efficiency and road safety in roundabout corridors. These corridors, composed of successive roundabouts along arterials, present systemic challenges due to the dynamic interactions between adjacent intersections. While previous [...] Read more.
This research is part of a broader investigation into innovative simulation-based approaches for improving traffic efficiency and road safety in roundabout corridors. These corridors, composed of successive roundabouts along arterials, present systemic challenges due to the dynamic interactions between adjacent intersections. While previous studies have addressed localized inefficiencies or proposed isolated interventions, this paper introduces possible replicable methodology based on a microsimulation and surrogate safety analysis to evaluate roundabout corridors as integrated systems. In this context, efficiency refers to the ability of a road corridor to maintain stable traffic conditions under a given demand scenario, with low delay times corresponding to acceptable levels of service. Safety is interpreted as the minimization of vehicle conflicts and critical interactions, evaluated through surrogate measures derived from simulated vehicle trajectories. The proposed approach—implemented through Aimsun Next and the SSAM tool—is tested on two real-world corridors: Via Aurelia Nord in Pisa (Italy) and Route de Marseille in Avignon (France), assessing multiple intersection configurations that combine roundabouts and signal-controlled junctions. Results show how certain layouts can produce unexpected performance outcomes, underlining the importance of system-wide evaluations. The proposed framework aims to support engineers and planners in identifying optimal corridor configurations under realistic operating conditions. Full article
(This article belongs to the Special Issue Sustainable Road Design and Traffic Management)
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23 pages, 59897 KB  
Article
Method to Use Transport Microsimulation Models to Create Synthetic Distributed Acoustic Sensing Datasets
by Ignacio Robles-Urquijo, Juan Benavente, Javier Blanco García, Pelayo Diego Gonzalez, Alayn Loayssa, Mikel Sagues, Luis Rodriguez-Cobo and Adolfo Cobo
Appl. Sci. 2025, 15(9), 5203; https://doi.org/10.3390/app15095203 - 7 May 2025
Cited by 1 | Viewed by 1060
Abstract
This research introduces a new method for creating synthetic Distributed Acoustic Sensing (DAS) datasets from transport microsimulation models. The process involves modeling detailed vehicle interactions, trajectories, and characteristics from the PTV VISSIM transport microsimulation tool. It then applies the Flamant–Boussinesq approximation to simulate [...] Read more.
This research introduces a new method for creating synthetic Distributed Acoustic Sensing (DAS) datasets from transport microsimulation models. The process involves modeling detailed vehicle interactions, trajectories, and characteristics from the PTV VISSIM transport microsimulation tool. It then applies the Flamant–Boussinesq approximation to simulate the resulting ground deformation detected by virtual fiber-optic cables. These synthetic DAS signals serve as large-scale, scenario-controlled, labeled datasets on training machine learning models for various transport applications. We demonstrate this by training several U-Net convolutional neural networks to enhance spatial resolution (reducing it to half the original gauge length), filtering traffic signals by vehicle direction, and simulating the effects of alternative cable layouts. The methodology is tested using simulations of real road scenarios, featuring a fiber-optic cable buried along the westbound shoulder with sections deviating from the roadside. The U-Net models, trained solely on synthetic data, showed promising performance (e.g., validation MSE down to 0.0015 for directional filtering) and improved the detectability of faint signals, like bicycles among heavy vehicles, when applied to real DAS measurements from the test site. This framework uniquely integrates detailed traffic modeling with DAS physics, providing a novel tool to develop and evaluate DAS signal processing techniques, optimize cable layout deployments, and advance DAS applications in complex transportation monitoring scenarios. Creating such a procedure offers significant potential for advancing the application of DAS in transportation monitoring and smart city initiatives. Full article
(This article belongs to the Special Issue Recent Research on Intelligent Sensors)
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23 pages, 11258 KB  
Article
Creating and Validating Hybrid Large-Scale, Multi-Modal Traffic Simulations for Efficient Transport Planning
by Fabian Schuhmann, Ngoc An Nguyen, Jörg Schweizer, Wei-Chieh Huang and Markus Lienkamp
Smart Cities 2025, 8(1), 2; https://doi.org/10.3390/smartcities8010002 - 24 Dec 2024
Cited by 3 | Viewed by 2809
Abstract
Mobility digital twins (MDTs), which utilize multi-modal microscopic (micro) traffic simulations and an activity-based demand generation, are envisioned as flexible and reliable planning tools for addressing today’s increasingly complex and diverse transport scenarios. Hybrid models may become a resource-efficient solution for building MDTs [...] Read more.
Mobility digital twins (MDTs), which utilize multi-modal microscopic (micro) traffic simulations and an activity-based demand generation, are envisioned as flexible and reliable planning tools for addressing today’s increasingly complex and diverse transport scenarios. Hybrid models may become a resource-efficient solution for building MDTs by creating large-scale, mesoscopic (meso) traffic simulations, using simplified, queue-based network-link models, in combination with more detailed local micro-traffic simulations focused on areas of interest. The overall objective of this paper is to develop an efficient toolchain capable of automatically generating, calibrating, and validating hybrid scenarios, with the following specific goals: (i) an automated and seamless merge of the meso- and micro-networks and demand; (ii) a validation procedure that incorporates real-world data into the hybrid model, enabling the meso- and micro-sub-models to be validated separately and compared to determine which simulation, micro- or meso-, more accurately reflects reality. The developed toolchain is implemented and applied to a case study of Munich, Germany, with the micro-simulation focusing on the city quarter of Schwabing, using real-word traffic flow and floating car data for validation. When validating the simulated flows with the detected flows, the regression curve shows acceptable values. The speed validation with floating car data reveals significant differences; however, it demonstrates that the micro-simulation achieves considerably better agreement with real speeds compared to the meso-model, as expected. Full article
(This article belongs to the Special Issue Cost-Effective Transportation Planning for Smart Cities)
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23 pages, 928 KB  
Review
Artificial Intelligence-Based Adaptive Traffic Signal Control System: A Comprehensive Review
by Anurag Agrahari, Meera M. Dhabu, Parag S. Deshpande, Ashish Tiwari, Mogal Aftab Baig and Ankush D. Sawarkar
Electronics 2024, 13(19), 3875; https://doi.org/10.3390/electronics13193875 - 30 Sep 2024
Cited by 25 | Viewed by 18870
Abstract
The exponential increase in vehicles, quick urbanization, and rising demand for transportation are straining the world’s road infrastructure today. To have a sustainable transportation system with dynamic traffic volume, an Adaptive Traffic Signal Control system (ATSC) should be contemplated to reduce urban traffic [...] Read more.
The exponential increase in vehicles, quick urbanization, and rising demand for transportation are straining the world’s road infrastructure today. To have a sustainable transportation system with dynamic traffic volume, an Adaptive Traffic Signal Control system (ATSC) should be contemplated to reduce urban traffic congestion and, thus, help reduce the carbon footprints/emissions of greenhouse gases. With dynamic cleave, the ATSC system can adapt the signal timing settings in real-time according to seasonal and short-term variations in traffic demand, enhancing the effectiveness of traffic operations on urban road networks. This paper provides a comprehensive study on the insights, technical lineaments, and status of various research work in ATSC. In this paper, the ATSC is categorized based on several road intersections (RIs), viz., single-intersection (SI) and multiple-intersection (MI) techniques, viz., Fuzzy Logic (FL), Metaheuristic (MH), Dynamic Programming (DP), Reinforcement Learning (RL), Deep Reinforcement Learning (DRL), and hybrids used for developing Traffic Signal Control (TSC) systems. The findings from this review demonstrate that modern ATSC systems designed using various techniques offer substantial improvements in managing the dynamic density of the traffic flow. There is still a lot of scope to research by increasing the number of RIs while designing the ATSC system to suit real-life applications. Full article
(This article belongs to the Section Artificial Intelligence)
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24 pages, 11862 KB  
Article
Comparative Assessment of Expected Safety Performance of Freeway Automated Vehicle Managed Lanes
by Jana McLean Sarran and Yasser Hassan
World Electr. Veh. J. 2024, 15(10), 447; https://doi.org/10.3390/wevj15100447 - 29 Sep 2024
Viewed by 1536
Abstract
The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature [...] Read more.
The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts. Full article
(This article belongs to the Special Issue Vehicle Safe Motion in Mixed Vehicle Technologies Environment)
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20 pages, 1958 KB  
Article
Integrating LiDAR Sensor Data into Microsimulation Model Calibration for Proactive Safety Analysis
by Morris Igene, Qiyang Luo, Keshav Jimee, Mohammad Soltanirad, Tamer Bataineh and Hongchao Liu
Sensors 2024, 24(13), 4393; https://doi.org/10.3390/s24134393 - 6 Jul 2024
Cited by 4 | Viewed by 3173
Abstract
Studies have shown that vehicle trajectory data are effective for calibrating microsimulation models. Light Detection and Ranging (LiDAR) technology offers high-resolution 3D data, allowing for detailed mapping of the surrounding environment, including road geometry, roadside infrastructures, and moving objects such as vehicles, cyclists, [...] Read more.
Studies have shown that vehicle trajectory data are effective for calibrating microsimulation models. Light Detection and Ranging (LiDAR) technology offers high-resolution 3D data, allowing for detailed mapping of the surrounding environment, including road geometry, roadside infrastructures, and moving objects such as vehicles, cyclists, and pedestrians. Unlike other traditional methods of trajectory data collection, LiDAR’s high-speed data processing, fine angular resolution, high measurement accuracy, and high performance in adverse weather and low-light conditions make it well suited for applications requiring real-time response, such as autonomous vehicles. This research presents a comprehensive framework for integrating LiDAR sensor data into simulation models and their accurate calibration strategies for proactive safety analysis. Vehicle trajectory data were extracted from LiDAR point clouds collected at six urban signalized intersections in Lubbock, Texas, in the USA. Each study intersection was modeled with PTV VISSIM and calibrated to replicate the observed field scenarios. The Directed Brute Force method was used to calibrate two car-following and two lane-change parameters of the Wiedemann 1999 model in VISSIM, resulting in an average accuracy of 92.7%. Rear-end conflicts extracted from the calibrated models combined with a ten-year historical crash dataset were fitted into a Negative Binomial (NB) model to estimate the model’s parameters. In all the six intersections, rear-end conflict count is a statistically significant predictor (p-value < 0.05) of observed rear-end crash frequency. The outcome of this study provides a framework for the combined use of LiDAR-based vehicle trajectory data, microsimulation, and surrogate safety assessment tools to transportation professionals. This integration allows for more accurate and proactive safety evaluations, which are essential for designing safer transportation systems, effective traffic control strategies, and predicting future congestion problems. Full article
(This article belongs to the Special Issue Vehicle Sensing and Dynamic Control)
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24 pages, 8773 KB  
Article
Investigation of Analyzable Solutions for Left-Turn-Centered Congestion Problems in Urban Grid Networks
by Taraneh Ardalan, Denis Sarazhinsky, Nemanja Dobrota and Aleksandar Stevanovic
Sustainability 2024, 16(11), 4777; https://doi.org/10.3390/su16114777 - 4 Jun 2024
Cited by 3 | Viewed by 1662
Abstract
Traffic congestion caused by left-turning vehicles in a coordinated corridor is a multifaceted problem requiring tailored solutions. This study explores the impact of shared left-turn lanes within one-way couplets, particularly during peak hours, where high left-turn volumes, limited side street storage, and the [...] Read more.
Traffic congestion caused by left-turning vehicles in a coordinated corridor is a multifaceted problem requiring tailored solutions. This study explores the impact of shared left-turn lanes within one-way couplets, particularly during peak hours, where high left-turn volumes, limited side street storage, and the overlapped green time between pedestrians and left-turners contribute to queue spillbacks, coordination interruption, and network congestion. The focus of this paper is on the solutions that can be easily analyzed by practitioners, here called “analyzable solutions”. This approach stands in contrast to solutions derived from “non-transparent” optimization tools, which do not allow for a clear assessment of the solution’s adequacy or the ability to predict its impact in real-world applications. This paper investigates the effects of employing two analyzable signal timing strategies: Lagging Pedestrian (LagPed) phasing and Left-Turn Progression (LTP) offsets. Using high-fidelity microsimulation, the authors evaluated different scenarios, assessing pedestrian delays, queue lengths, travel time index, area average travel time index, and environmental impacts such as Fuel Consumption (FC) and CO2 emissions. The effectiveness of the proposed strategies was comprehensively evaluated against the base case scenario, demonstrating considerable improvements in various performance measures, including approximately a 5% reduction in FC and CO2 emissions. Implementation of the LTP strategy alone yields substantial reductions in delays, the number of stops, the queue length for left-turning vehicles, travel times for all road users, and ultimately FC and CO2 emissions. This study offers innovative approach to addressing the complex and multifaceted problem of left-turn-centered congestion in urban grid networks using efficient and down-to-earth analyzable solutions. Full article
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18 pages, 6428 KB  
Article
Connected Automated and Human-Driven Vehicle Mixed Traffic in Urban Freeway Interchanges: Safety Analysis and Design Assumptions
by Anna Granà, Salvatore Curto, Andrea Petralia and Tullio Giuffrè
Vehicles 2024, 6(2), 693-710; https://doi.org/10.3390/vehicles6020032 - 11 Apr 2024
Cited by 6 | Viewed by 3435
Abstract
The introduction of connected automated vehicles (CAVs) on freeways raises significant challenges, particularly in interactions with human-driven vehicles, impacting traffic flow and safety. This study employs traffic microsimulation and surrogate safety assessment measures software to delve into CAV–human driver interactions, estimating potential conflicts. [...] Read more.
The introduction of connected automated vehicles (CAVs) on freeways raises significant challenges, particularly in interactions with human-driven vehicles, impacting traffic flow and safety. This study employs traffic microsimulation and surrogate safety assessment measures software to delve into CAV–human driver interactions, estimating potential conflicts. While previous research acknowledges that human drivers adjust their behavior when sharing the road with CAVs, the underlying reasons and the extent of associated risks are not fully understood yet. The study focuses on how CAV presence can diminish conflicts, employing surrogate safety measures and real-world mixed traffic data, and assesses the safety and performance of freeway interchange configurations in Italy and the US across diverse urban contexts. This research proposes tools for optimizing urban layouts to minimize conflicts in mixed traffic environments. Results reveal that adding auxiliary lanes enhances safety, particularly for CAVs and rear-end collisions. Along interchange ramps, an exclusive CAV stream performs similarly to human-driven ones in terms of longitudinal conflicts, but mixed traffic flows, consisting of both CAVs and human-driven vehicles, may result in more conflicts. Notably, when CAVs follow human-driven vehicles in near-identical conditions, more conflicts arise, emphasizing the complexity of CAV integration and the need for careful safety measures and roadway design considerations. Full article
(This article belongs to the Special Issue Emerging Transportation Safety and Operations: Practical Perspectives)
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14 pages, 3268 KB  
Article
Assessing the Operation of a Multimodal Hub: A Traffic Impact Microsimulation Analysis
by Georgia Charalampidou, Aristomenis Kopsacheilis and Ioannis Politis
Infrastructures 2024, 9(3), 55; https://doi.org/10.3390/infrastructures9030055 - 9 Mar 2024
Viewed by 3481
Abstract
Creating new multimodal infrastructure in an existing transport network of an urban city is a challenging process. The responsible transport authorities have to pay special attention to the details regarding the accessibility and effectiveness of the new development, to avoid travelers’ confusion and [...] Read more.
Creating new multimodal infrastructure in an existing transport network of an urban city is a challenging process. The responsible transport authorities have to pay special attention to the details regarding the accessibility and effectiveness of the new development, to avoid travelers’ confusion and network congestion. The subject of this paper is the assessment and optimization of the traffic network in the surroundings of the new multimodal depot of Thessaloniki’s future metro system with the use of the microsimulation software PTV VISSIM (version 2022). Five different scenarios were developed in collaboration with the city’s transport authority and evaluated into two stages, beginning with the whole traffic network, and then continuing with the analyzed intersections separately. The evaluation is based on Key Performance Indicators (KPIs), which were extracted by the software. According to the results of the base case scenario, the network functions satisfactorily, with slight delays. Regarding the future network, the operation of the new hub will strongly increase the traffic demand, while the proposed traffic network adjustments by the local authorities seem to cause significant delay problems. This paper aims to highlight the importance of using modeling tools during the design phase of a new infrastructure to create efficient, accessible, and sustainable infrastructures that enhance the public transport system. Full article
(This article belongs to the Special Issue Sustainable Infrastructures for Urban Mobility)
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24 pages, 10193 KB  
Article
The Role of Intersection Geometry in Urban Air Pollution Management
by Ammar Šarić, Suada Sulejmanović, Sanjin Albinović, Mirza Pozder and Žanesa Ljevo
Sustainability 2023, 15(6), 5234; https://doi.org/10.3390/su15065234 - 15 Mar 2023
Cited by 14 | Viewed by 3533
Abstract
Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents [...] Read more.
Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents the influence of intersection geometry on pollutant emissions levels. In addition, the influence of various traffic policies promoting greater use of public transport and zero-emission vehicles is also examined. The research combines the field part of recording existing intersections in Sarajevo, Bosnia and Herzegovina with traffic microsimulation. Detailed data on vehicles’ movements were obtained by advanced video processing using the DataFromSky tool, while the PTV Vissim 2022 and Bosch ESTM (2022) software were used to simulate traffic and estimate emissions at geometrically different intersections. The results showed that, in saturated traffic conditions, signalized intersections cause up to 50% lower emissions compared with two-lane and turbo roundabouts and that the impact of the geometric change is more significant than the impact of zero-emission vehicles. In unsaturated conditions, the differences in emissions at different intersections are negligible, with the highest reductions in pollution achieved by using zero-emission vehicles. Full article
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26 pages, 1542 KB  
Article
Expected Waiting Times at an Intersection with a Green Extension Strategy for Freight Vehicles: An Analytical Analysis
by Sara Sasaninejad, Joris Van Malderen, Joris Walraevens and Sabine Wittevrongel
Mathematics 2023, 11(3), 721; https://doi.org/10.3390/math11030721 - 1 Feb 2023
Cited by 3 | Viewed by 2123
Abstract
The need for transporting commodities has led to more and more freight vehicles on urban roads. Specific operational constraints of such vehicles could induce non-homogeneities in the smooth movement of traffic, especially at intersections where acceleration/deceleration events occur frequently. This leads to unnecessary [...] Read more.
The need for transporting commodities has led to more and more freight vehicles on urban roads. Specific operational constraints of such vehicles could induce non-homogeneities in the smooth movement of traffic, especially at intersections where acceleration/deceleration events occur frequently. This leads to unnecessary wasted time for all vehicles, even in low to moderate traffic conditions. Hence, the literature reports different proposals to enhance the continuity of traffic at intersections. Among them, the green extension strategy has attracted researchers’ attention, owing to its simplicity, flexibility and practicality. In this paper, we propose a new approximate probabilistic model for the expected waiting/wasted time of all vehicles at an intersection with green time extension in low to moderate traffic conditions. Accordingly, the optimal green extension interval that minimizes the total expected waiting time can then be determined in different conditions. The proposed analysis needs few pieces of information (as opposed to microsimulation models conventionally employed to analyze such systems) and is therefore, suitable for quickly deciding on the optimal strategy based on the current situation in a dynamic environment. We have validated our approximate analysis with simulations in the VISSIM simulation tool. Full article
(This article belongs to the Special Issue Queue and Stochastic Models for Operations Research II)
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11 pages, 2926 KB  
Article
Modeling the Assessment of Intersections with Traffic Lights and the Significance Level of the Number of Pedestrians in Microsimulation Models Based on the PTV Vissim Tool
by Monika Ziemska-Osuch and Dawid Osuch
Sustainability 2022, 14(14), 8945; https://doi.org/10.3390/su14148945 - 21 Jul 2022
Cited by 20 | Viewed by 6196
Abstract
The present article contains a microsimulation analysis of the impact of the number of pedestrians on pedestrian crossings controlled by traffic lights. To analyze the level of freedom of movement using the HCM 2010 method based on the level of service (LOS) implemented [...] Read more.
The present article contains a microsimulation analysis of the impact of the number of pedestrians on pedestrian crossings controlled by traffic lights. To analyze the level of freedom of movement using the HCM 2010 method based on the level of service (LOS) implemented in the PTV VISSIM tool, a simulation of two interconnected intersections is performed. These crossings differ in the number of inlets as well as in the intensity of vehicles at each of the inlets. The microsimulation model was based on real data on the intensity of vehicles from an intelligent traffic control system as well as real traffic light programs. Eleven different variants of the same initial conditions were tested in which the number of pedestrians at pedestrian crossings was increased every 50 and the time of the right turn and the LOS of the right turn were compared. The result shows the impact of the number of pedestrians on the assessment of LOS traffic conditions at the entire intersection. The results consider the ranges in which the number of pedestrians has a significant impact and change the assessment of the entire intersection to the next worse level of freedom of movement. The article shows how it can be a mistake to overlook adding the exact number of pedestrians at traffic light intersections with PTV Viswalk in the microsimulation model. Full article
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16 pages, 2731 KB  
Article
Managed Lane as Strategy for Traffic Flow and Safety: A Case Study of Catania Ring Road
by Salvatore Cafiso, Alessandro Di Graziano, Tullio Giuffrè, Giuseppina Pappalardo and Alessandro Severino
Sustainability 2022, 14(5), 2915; https://doi.org/10.3390/su14052915 - 2 Mar 2022
Cited by 13 | Viewed by 3735
Abstract
According to international traffic statistics, the quantity of daily traveling vehicles amounts to one billion, and it is estimated that in 2050 that amount will reach four billion. Urban population is growing especially in large metropolitan areas. This increase has different outgrowths concerning [...] Read more.
According to international traffic statistics, the quantity of daily traveling vehicles amounts to one billion, and it is estimated that in 2050 that amount will reach four billion. Urban population is growing especially in large metropolitan areas. This increase has different outgrowths concerning regular circulation, safety, and climatic perspectives. Therefore, the present and further increase of traffic flow is affecting the operational and safety performance of several roadway categories. Urban ring roads belong to a roadway category that is particularly subjected to congestion phenomena, but in many cases, public administrations are unable to afford required expenses to upgrade or build new roadways. Therefore, an intervention is needed that increases the capacity of existing infrastructures with limited cost results to be fundamental. In such a framework, the dynamic use of hard shoulder running (HSR) would represent a valid solution that both exploits existing infrastructures and facilitates traffic outflow by implementation of smart digital roads, with limited interventions on the physical infrastructure. Despite the expected improvements in traffic capacity, the HSR poses safety issues particularly in specific locations (e.g., interchanges) and for the operation of the transition phase for opening and closing the HSR. In this paper, the applicability and usefulness of microsimulation were tested with the Catania (Italy) ring road, as a case study, through the application of VISSIM traffic microsimulation software and SSAM traffic conflict tool, implementing different scenarios for the activation of the HSR. Full article
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28 pages, 7057 KB  
Article
Getting Real: The Challenge of Building and Validating a Large-Scale Digital Twin of Barcelona’s Traffic with Empirical Data
by Javier Argota Sánchez-Vaquerizo
ISPRS Int. J. Geo-Inf. 2022, 11(1), 24; https://doi.org/10.3390/ijgi11010024 - 30 Dec 2021
Cited by 59 | Viewed by 7997
Abstract
Large-scale microsimulations are increasingly resourceful tools for analysing in detail citywide effects and alternative scenarios of our policy decisions, approximating the ideal of ‘urban digital twins’. Yet, these models are costly and impractical, and there are surprisingly few published examples robustly validated with [...] Read more.
Large-scale microsimulations are increasingly resourceful tools for analysing in detail citywide effects and alternative scenarios of our policy decisions, approximating the ideal of ‘urban digital twins’. Yet, these models are costly and impractical, and there are surprisingly few published examples robustly validated with empirical data. This paper, therefore, presents a new large-scale agent-based traffic microsimulation for the Barcelona urban area using SUMO to show the possibilities and challenges of building these scenarios based on novel fine-grained empirical big data. It combines novel mobility data from real cell phone records with conventional surveys to calibrate the model comparing two different dynamic assignment methods for getting an operationally realistic and efficient simulation. Including through traffic and the use of a stochastic adaptive routing approach results in a larger 24-hour model closer to reality. Based on an extensive multi-scalar evaluation including traffic counts, hourly distribution of trips, and macroscopic metrics, this model expands and outperforms previous large-scale scenarios, which provides new operational opportunities in city co-creation and policy. The novelty of this work relies on the effective modelling approach using newly available data and the realistic robust evaluation. This allows the identification of the fundamental challenges of simulation to accurately capture real-world dynamical systems and to their predictive power at a large scale, even when fed by big data, as envisioned by the digital twin concept applied to smart cities. Full article
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28 pages, 1274 KB  
Article
Longitudinal Control for Connected and Automated Vehicles in Contested Environments
by Shirin Noei, Mohammadreza Parvizimosaed and Mohammadreza Noei
Electronics 2021, 10(16), 1994; https://doi.org/10.3390/electronics10161994 - 18 Aug 2021
Cited by 13 | Viewed by 3744
Abstract
The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 to Level 5. Automated driving systems perform entire dynamic driving tasks for Levels 3–5 automated vehicles. Delegating dynamic driving tasks from driver to automated driving systems can [...] Read more.
The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 to Level 5. Automated driving systems perform entire dynamic driving tasks for Levels 3–5 automated vehicles. Delegating dynamic driving tasks from driver to automated driving systems can eliminate crashes attributed to driver errors. Sharing status, sharing intent, seeking agreement, or sharing prescriptive information between road users and vehicles dedicated to automated driving systems can further enhance dynamic driving task performance, safety, and traffic operations. Extensive simulation is required to reduce operating costs and achieve an acceptable risk level before testing cooperative automated driving systems in laboratory environments, test tracks, or public roads. Cooperative automated driving systems can be simulated using a vehicle dynamics simulation tool (e.g., CarMaker and CarSim) or a traffic microsimulation tool (e.g., Vissim and Aimsun). Vehicle dynamics simulation tools are mainly used for verification and validation purposes on a small scale, while traffic microsimulation tools are mainly used for verification purposes on a large scale. Vehicle dynamics simulation tools can simulate longitudinal, lateral, and vertical dynamics for only a few vehicles in each scenario (e.g., up to ten vehicles in CarMaker and up to twenty vehicles in CarSim). Conventional traffic microsimulation tools can simulate vehicle-following, lane-changing, and gap-acceptance behaviors for many vehicles in each scenario without simulating vehicle powertrain. Vehicle dynamics simulation tools are more compute-intensive but more accurate than traffic microsimulation tools. Due to software architecture or computing power limitations, simplifying assumptions underlying convectional traffic microsimulation tools may have been a necessary compromise long ago. There is, therefore, a need for a simulation tool to optimize computational complexity and accuracy to simulate many vehicles in each scenario with reasonable accuracy. This research proposes a traffic microsimulation tool that employs a simplified vehicle powertrain model and a model-based fault detection method to simulate many vehicles with reasonable accuracy at each simulation time step under noise and unknown inputs. Our traffic microsimulation tool considers driver characteristics, vehicle model, grade, pavement conditions, operating mode, vehicle-to-vehicle communication vulnerabilities, and traffic conditions to estimate longitudinal control variables with reasonable accuracy at each simulation time step for many conventional vehicles, vehicles dedicated to automated driving systems, and vehicles equipped with cooperative automated driving systems. Proposed vehicle-following model and longitudinal control functions are verified for fourteen vehicle models, operating in manual, automated, and cooperative automated modes over two driving schedules under three malicious fault magnitudes on transmitted accelerations. Full article
(This article belongs to the Special Issue Security of Cyber-Physical Systems)
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