Microscopic Simulation Research Articles

Safety Impact of Introducing Automated Road Debris Removal System in South Korea

Road debris should be removed quickly because it can cause road damage and traffic accidents. An automated road debris removal system—called ROBOS—was developed in South Korea to remove road debris automatically and quickly. It can be mounted and used on vehicles over 3.5 tons. The effects of ROBOS on the traffic flow need to be studied before it can be used on actual roads. In this study, these effects were investigated by performing driving and microscopic traffic simulations. The former can be used to analyze drivers’ reactions to new road equipment and driving behavior when detecting road debris. Driving behavior results that met the research purpose were employed in the microscopic traffic simulation to imitate reality. Finally, the number of conflicts and the conflict rate were compared between manual and ROBOS vehicle road debris removal scenarios to analyze traffic safety. The results showed that the overall traffic safety was low when road debris was present in curved sections, where it was generally difficult for the driver to easily detect it, and in the first lane and third lane, where lane changes were limited. Assuming that a ROBOS vehicle was used in these sections, the number of conflicts and the conflict rate can be significantly reduced. This study evaluated traffic safety after the use of a ROBOS vehicle input and obtained basic information needed for decision-making in future road debris removal work, such as the priority of input when choosing between manual removal and removal by a ROBOS vehicle.

Introduction and application of a new approach for model-based optical bidirectional measurements

Accurate measurements of micro- and nanoscale features in optical microscopy demand comprehensive modelling approaches. In this study, we introduce an enhanced evaluation method, utilizing rigorous simulations based on a finite element method algorithm within an advanced Bayesian optimization framework. We provide an in-depth explanation of the measurement process, including the dimension reduction techniques applied to the acquired measurement data. Additionally, we employ Hopkins’ approximation or also referred to as local Hopkins’ methods for an efficient microscopic image simulation, resulting in a significant reduction of the computing time. We applied this method to measure the linewidths of six different chrome lines, nominally 300 nm–1000 nm wide, on a glass substrate. Our results show an excellent agreement with previous investigations conducted using various measurement systems, including atomic force microscopy, scanning electron microscopy, and optical microscopy in combination with different measurement evaluation techniques.

The Environmental Benefits of an Automatic Idling Control System of Connected and Autonomous Vehicles (CAVs)

The transportation sector is regarded as the main culprit in greenhouse gas emission in the urban network, particularly idling vehicles waiting at signalized intersections. Although autonomous vehicles can be a promising technology to tackle vehicle idling, their environmental benefits receive little attention compared with their safety and mobility issues. This study investigated the environmental benefits of autonomous vehicles equipped with an automatic idling control function based on the queue discharge time and traffic signal information transmitted from the traffic signal controller via V2I communication using microscopic mobility and emission simulation models, VISSIM and MOVES, in Haeundae-gu in Busan, Korea. This study found that the function contributes to a significant reduction in CO2 emissions by 23.6% for all-inclusive emission and 94.3% for idling emission, respectively. Moreover, total reduced idling time accounts for 47.6% of the total travel time and 94.3% of the total idling time, respectively. Consequently, the autonomous vehicles equipped with automatic vehicle idling control function under C-ITS can play an important role in reducing greenhouse gas emissions and fuel consumption as well in the urban network.

Design of advanced steels by integrated computational materials engineering

AbstractThe integrated computational materials engineering (ICME) has achieved great success in accelerating the rational design and deployment of new materials. It is a new route of designing new materials and processes and highlighted by Materials Genome Initiative/Engineering that stresses the high‐throughput computation in addition to high‐throughput experimentation and materials informatics. This article presents a brief review on the basic theories and multi‐scale computational tools of ICME to design advanced steel grades, including the first‐principles calculations, the CALPHAD method (i.e., computational thermodynamics) fueled by dedicated databases, diffusion and phase‐field simulations, as well as finite analysis methods and machine learning. In the ICME scheme to deal with steels, the CALPHAD method is considered as the core to readily consider multi‐component systems and integrated to link the microscopic simulations (such as diffusion and phase field method to predict microstructure evolutions in response to external conditions) and macroscopic finite analysis method to deal with mechanical properties. Two applications are also presented to address the new routes to carry out materials design, especially for advanced steels.

Analysis of spin-squeezing generation in cavity-coupled atomic ensembles with continuous measurements

We analyze the generation of spin-squeezed states via coupling of three-level atoms to an optical cavity and continuous quantum measurement of the transmitted cavity field in order to monitor the evolution of the atomic ensemble. Using analytical treatment and microscopic simulations of the dynamics, we show that one can achieve significant spin squeezing, favorably scaling with the number of atoms N. However, contrary to some previous literature, we clarify that it is not possible to obtain Heisenberg scaling without the continuous feedback that is proposed in optimal approaches. In fact, in the adiabatic cavity removal approximation and large N limit, we find the scaling behavior N−2/3 for spin squeezing and N−1/3 for the corresponding protocol duration. These results can be obtained only by considering the curvature of the Bloch sphere, since linearizing the collective spin operators tangentially to its equator yields inaccurate predictions. With full simulations, we characterize how spin-squeezing generation depends on the system parameters and departs from the bad cavity regime, by gradually mixing with cavity-filling dynamics until metrological advantage is lost. Finally, we discuss the relevance of this spin-squeezing protocol to state-of-the-art optical clocks.

Evaluation of Traffic Efficiency and Energy-Saving Benefits of L3 Smart Vehicles under the Urban Expressway Scenario

An L3 smart vehicle (L3 SV) could behave differently from human-driven vehicles due to its intelligent configuration and decision-making logic, and may consequently exert influences on traffic flow. In order to clarify the L3 SV’s traffic impacts and accelerate L3 SV implementation, this paper conducted an evaluation on the traffic efficiency and energy consumption influences of L3 SVs based on a microscopic traffic simulation. Taking Beijing as a case, the relevant traffic economic benefits were calculated with the help of the previously proposed traffic economic benefits model. Before modeling L3 SVs, a two-dimensional general modeling architecture for SVs was proposed. According to the architecture, the driving behavior model, as well as behavior selection models of L3 SVs, was eventually determined, based on which the intelligent driving model of L3 SVs was established. Urban expressways were selected as the simulation road type, and scenario analysis was conducted on various proportions of L3 SVs and L3 connected and autonomous vehicles (L3 CAVs), as well as the input traffic flow rates. It was found that L3 SVs can significantly reduce the travel time and energy consumption and enlarge the actual road capacity. The improvement will become particularly prominent under saturated or supersaturated traffic flow and increasing the proportion of L3 SVs and L3 CAVs can also amplify the effect of traffic optimization. The related economic benefit is considerable, which is CNY 3.104 billion a year based on Beijing’s travel and traffic conditions.

Traffic flow impact of mixed heterogeneous platoons on highways: an approach combining driving simulation and microscopic traffic simulation

The connected automated vehicle (CAV) platoons are expected to improve the operational performance of the transportation system. Existing platoon testing processes have used the format of mixed heterogeneous platoons (MHPs), where the leader vehicles are connected human-driven vehicles (CHDVs) and the follower vehicles are CAVs. The impact of this type of MHP on existing highway traffic flow is more complex due to the presence of human drivers, and this impact has yet to be analyzed and quantified. Therefore, this paper takes this type of MHP as the research object and conducts experiments by combining driving simulation and microscopic traffic simulation. The driving behavior of the driver of the MHP's leader vehicle is incorporated into the car-following model by means of a car-following model calibration, and an impact analysis is carried out in terms of multiple dimensions of stability, efficiency, and ecological aspects of the mixed traffic flow under different MHP market penetration rates (MPRs). The results show that MHPs weaken the oscillatory effect of mixed traffic flow and improve mixed traffic flow stability. The MPRs of MHPs are proportional to the road capacity and average speed and antipodal to the average travel time. Also, the MHPs help reduce fuel consumption and pollutant emissions (CO2, CO, NOx, HC, and PMx) during traffic operations. This study can provide theoretical support for the future large-scale application and management of MHPs.

MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC)

Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.

Determining Desired Speeds from Vehicle Trajectory Data

Desired speed or free speed distributions are important input parameters for microscopic traffic flow simulations. Whereas driven speeds can be measured, desired speeds are not detectable for all vehicles because of vehicles constraining each other. An established approach to estimating desired speed distributions is the modified Kaplan–Meier approach, which estimates desired speed distributions based on single vehicle data from stationary detectors. We propose a novel approach to determine desired speeds based on vehicle trajectory data. The proposed approach, as well as the modified Kaplan–Meier approach, is applied to a trajectory dataset recorded on a German freeway. With the modified Kaplan–Meier approach, we observed that the resulting desired speed distributions vary by approximately 5 km/h depending on the position of the stationary detectors. The desired speed distributions obtained from the trajectory-based approach are approximately 5 to 10 km/h higher than those estimated by the modified Kaplan–Meier approach. This difference in results is probably because the trajectory-based approach observes each vehicle over a longer distance rather than just at stationary points. Nevertheless, it can be concluded that the estimation of desired speed distributions is subject to a certain degree of inaccuracy. The analysis of the vehicle trajectory data revealed a notable intra-vehicle instability in desired speeds, with a difference of 5 to 7 km/h observed for 40% of the vehicles between different periods of free driving. These findings should be considered in the context of calibrating microscopic traffic flow simulations.

A hierarchy of the optimal velocity model with optimal path for pedestrian evacuation: From microscopic to macroscopic models

We study the evacuation process of pedestrians by adopting an optimal velocity model. The Eikonal equation is coupled to the optimal velocity model for optimal path to guide the movement directions of pedestrians. It depends on pedestrian density. We derive the corresponding mean field equation, hydrodynamic and scalar models from the scaled microscopic optimal velocity model. Several numerical experiments are performed in a corridor with two exits. We show and compare results on the microscopic as well as on the hydrodynamic and scalar models. Results from microscopic model are closed to the hydrodynamic and scalar models when a large number of particles are considered in microscopic simulation. The computation time increases as number of particles in microscopic simulation increases. The computation times of the hydrodynamic and scalar models are less than the computation time of the microscopic model with large number of particles. Hence it is beneficial to apply the hydrodynamic and scalar models over the microscopic model when a large number of particles in microscopic system are considered.

Ultrafast dephasing in solid-state high harmonic generation: macroscopic origin revealed by real-space dynamics [Invited

Using a fully real-space perspective on high harmonic generation (HHG) in solids, we examine the relationship between microscopic response, macroscopic propagation of this response to the far-field, and the extremely short dephasing times routinely used in the theoretical simulations of experimentally measured solid-state HHG spectra. We find that far-field propagation naturally reduces the contribution to the observed HHG emission from electrons that do not return to the lattice site where they have been injected into the conduction band. We then show that extremely short dephasing times routinely used in microscopic simulations suppress many electron trajectories that contribute to the far-field spectra, leading to significant distortions of the true high harmonic response. We show that a real-space based dephasing mechanism, which preferentially suppresses trajectories that veer too far away from their original lattice site, yields HHG spectra that faithfully retain those trajectories that contribute to the far-field spectra while filtering out those that do not, already at the microscopic level. Our findings emphasize the similarities between atomic and solid-state HHG by highlighting the importance of the intensity-dependent phase of HHG emission and address the longstanding issue regarding the origin of extremely short dephasing times in solid-state HHG.

Safety-oriented urban pavement design and evaluation: integrating microscopic simulation and tyre-pavement friction

ABSTRACT Tyre-pavement friction significantly impacts traffic safety performance, yet integrating these topics is often overlooked in pavement engineering. This paper addresses this gap by utilising microscopic traffic simulation and surrogate measures of safety to assess vehicular conflicts severity in diverse urban scenarios and establish friction thresholds for practical implementation. A pre-construction materials selection approach is proposed, employing a predictive model for tyre-pavement friction. Findings reveal that combinations of fine-graded mixtures and low surface texture mineral aggregates can lead to increased conflict severity in urban environments. Furthermore, a post-construction texture assessment using 3D computer vision was applied for verifying compliance with friction thresholds for asphalt pavement surfaces. This study emphasises the potential for cost-effective integration of traffic simulation and safety analysis to an enhanced urban pavement design and evaluation. By incorporating safety-based tyre-pavement friction considerations, decision-making related to materials selection and friction conditions can be improved, leading to safer urban transportation networks.

Analysis of reservoir damage and microscopic seepage simulation in low permeability oil and gas reservoirs based on pore topology structure

This paper investigates the potential factors contributing to reservoir damage in low permeability reservoirs, based on the micro-characteristics of pore throats. Through the utilization of numerical simulations, we investigate the micro-permeability behavior of fluids within these low permeability reservoirs. The simulations produce a micro-numerical field distribution of fluid within the reservoir (comprising velocity field, pressure field, and phase field), facilitating an analysis of evolving patterns and influencing mechanisms between oil and water phases during displacement processes. The simulation results indicate that with an increase in the number and diameter of plugged pores, there is a significant decrease in reservoir permeability. The permeability of pores smaller than 3.0 μm decreases to 92 % of the original value, while that of pores smaller than 3.5 μm drops to 87 %, and that of pores smaller than 5.0 μm decreases to 82 %. The rock stress sensitivity effect leads to a reduction in permeability, with a 94 % decrease when pore deformation reaches 95 %, and an 86.5 % decrease at a deformation level of 85 %. Leveraging these simulation results and considering potential formation damage that may occur during oil and gas field development processes, we propose targeted formation damage controlling measures to provide theoretical underpinning for efficient development strategies in low permeability reservoirs.

Numerical simulation of fingering in the underground hydrogen storage

Underground hydrogen storage has garnered interest in recent years owing to the considerable demand for clean energy. Hydrogen is more diffusive than air and has relatively low density and viscosity. These unique properties induce distinct hydrodynamic phenomena during hydrogen storage. Cushion gas has been proven to be a potential remedy for attenuating the adverse impacts of underground hydrogen storage. To investigate the influence of the cushion gas, a microscopic numerical simulation was performed with Fluent software using the Eulerian multi-fluid model. Carbon dioxide, nitrogen, and methane are usually used as the preferred candidates for cushion gases in underground hydrogen storage systems. In this study, nitrogen was used as the cushion gas and was injected along with hydrogen into heterogeneous porous media with volume fractions ranging from 0% to 70%. A parameterization study was then performed to elucidate the influences of the injection rate and viscosity of the fluid on the fingering pattern. Two representative types of fingering, viscous fingering and capillary fingering, were observed under different gas mixtures and boundary conditions. After the simulation, an image analysis was performed to capture the evolution of the fingering pattern. The specific fingering area, number of branches, and fractal dimensions are proposed as geometric indices to describe the shape of the fingering pattern. The results showed that there was a remarkable enhancement in saturation due to the injection of the cushion gas, depending on the concentration of the gas mixture. This study offers insight on the design of gas mixture injection in underground hydrogen storage and can be further extended to the hydrochemo–mechanical coupled numerical simulation of multiphase gas injection in porous media.

Multi-scale investigation of heat and momentum transfer in packed-bed TES systems up to 800 K

With the rising cost of energy and the advancement of corporate social responsibility, there is a growing interest in addressing the challenge of recovering and storing high-temperature waste heat. Sensible heat storage in packed beds stands out as a cost-effective and seemingly straightforward solution for high-temperature Thermal Energy Storage (TES). Engineering models developed to design low-temperature TES systems were tentatively used to design this new generation of high-temperature systems. Delving into the physics of coupled heat and mass transfer reveals a lack of validation of this approach. This study seeks to establish a comprehensive bottom-up methodology - from the particle scale up to the system level - to provide informed and validated engineering models for the design of high-temperature TES systems. To achieve this goal, we developed a multi-scale numerical model to explore the physics of heat and momentum transfer in packed-bed TES systems. At the microscopic scale (pore/particle), we consider the flow of a compressible high-temperature gas between the particles, coupled to transient heat conduction within the particles, with particular attention given to incorporating accurate temperature-dependent viscosity for the gas phase and thermal conductivity and density for both solid and gas phases. At the macroscopic scale (engineering), we propose a high-temperature extension of state-of-the-art two-equation TES models. The governing equations considered are the volume-average conservation laws for gas-mass, gas-momentum and energy of both phases. The multi-scale strategy is applied to a randomly packed bed of spherical particles generated with the discrete element method (DEM) software LIGGGHTS. Numerical models for both scales were implemented in the Porous material Analysis Toolbox based on OpenFoam (PATO), which is made available in Open Source by NASA. Microscopic scale simulations were used to infer the effective parameters needed to inform the macroscopic model, namely, permeability, Forchheimer coefficient, effective thermal conductivities, and the heat transfer coefficient. The informed macroscopic model reproduces with excellent accuracy the average temperature fields of the physics-based microscopic model. Pore-scale analysis shows highly three-dimensional flow characterized by reverse flow and strong cross-flow in the packed bed system. Moreover, it indicates the coupling between temperature and velocity fields, where a nonuniform velocity field results in uneven temperature distributions across the fluid and the solid spheres within the packed bed, subsequently affecting the macroscopic heat transfer coefficient. The overall strategy is validated by comparison to available experimental data. This bottom-up methodology contributes to the understanding and opens new perspectives for a more precise design and monitoring of high-temperature TES systems.

Comparison of probabilistic cruising-for-parking time estimation models

Models of parking search time predominantly rely on the binomial approximation, the calculation of which is dependent solely on the occupancy of the parking network. This paper sheds light on the importance of accounting for competition between parking searchers and the effects of dynamically changing occupancy. To this end, we investigate the accuracy of two probabilistic models, namely the binomial approximation and a model proposed by Cao and Menéndez (CaM). We utilize an agent-based microscopic parking simulation model as a benchmark for comparison purposes. Our findings highlight the significance of considering the competitive dynamics among drivers in the quest for parking spaces and the fluctuations in parking occupancy rates over short time intervals. We highlight the ranges of occupancies for which the binomial approximation and the CaM model provide more reliable estimations of parking search times. The CaM model provides, in general, more accurate estimations of search times since it accounts for various parking network characteristics such as competition and varying occupancy. The binomial approximation underestimates parking search times more substantially at high occupancies with a large number of searching vehicles, whereas the CaM model performs worse for lower spacing between parking spots and lower parking occupancies. Insights from this research are then used to discuss policy implications of accounting for competition and short-term occupancy variations when designing either parking models or parking-related control strategies.

A methodology of cooperative driving based on microscopic traffic prediction

We present a methodology of cooperative driving in vehicular traffic, in which for short-time traffic prediction rather than one of the statistical approaches of artificial intelligence (AI), we follow a qualitative different microscopic traffic prediction approach developed recently (Kerner and Klenov, 2022). In the microscopic traffic prediction approach used for the planning of the subject vehicle trajectory, no learning algorithms of AI are applied; instead, microscopic traffic modeling based on the physics of vehicle motion is used. The presented methodology of cooperative driving is devoted to application cases in which microscopic traffic prediction without cooperative driving cannot lead to a successful vehicle control and trajectory planning. For the understanding of the physical features of the methodology of cooperative driving, a traffic city scenario has been numerically studied, in which a subject vehicle, which requires cooperative driving, is an automated vehicle. Based on microscopic traffic prediction, in the methodology first a cooperating vehicle(s) is found; then, motion requirements for the cooperating vehicle(s) and characteristics of automated vehicle control are predicted and used for vehicle motion; to update predicted characteristics of vehicle motion, calculations of the predictions of motion requirements for the cooperating vehicle and automated vehicle control are repeated for each next time instant at which new measured data for current microscopic traffic situation are available. With the use of microscopic traffic simulations, the evaluation of the applicability of this methodology is illustrated for a simple case of unsignalized city intersection, when the automated vehicle wants to turn right from a secondary road onto the priority road.

Using Probe Counts to Provide High-Resolution Detector Data for a Microscopic Traffic Simulation

Microscopic traffic simulations have become increasingly important for research targeting connected vehicles. They are especially appreciated for enabling investigations targeting large areas, which would be practically impossible or too expensive in the real world. However, such large-scale simulation scenarios often lack validation with real-world measurements since these data are often not available. To overcome this issue, this work integrates probe counts from floating car data as reference counts to model a large-scale microscopic traffic scenario with high-resolution detector data. To integrate the frequent probe counts, a road network matching is required. Thus, a novel road network matching method based on a decision tree classifier is proposed. The classifier automatically adjusts its cosine similarity and Hausdorff distance-based similarity metrics to match the network’s requirements. The approach performs well with an F1-score of 95.6%. However, post-processing steps are required to produce a sufficiently consistent detector dataset for the subsequent traffic simulation. The finally modeled traffic shows a good agreement of 95.1%. with upscaled probe counts and no unrealistic traffic jams, teleports, or collisions in the simulation. We conclude that probe counts can lead to consistent traffic simulations and, especially with increasing and consistent penetration rates in the future, help to accurately model large-scale microscopic traffic simulations.

Soil conditioning of clay based on interface adhesion mechanism: Microscopic simulation and laboratory experiment

Clogging frequently occurs in the cutter head, excavation chamber or screw conveyor when an earth pressure balance (EPB) shield machine is tunneling in soft or silty clay ground with high clay mineral content. In this paper, montmorillonite, kaolinite, and illite were selected as research objects, and molecular dynamics simulation and laboratory experiment were adopted. At the microscopic scale, dynamic contact behavior and interfacial mechanical behavior of the interface between clay minerals and water/surfactant solution was simulated and the interfacial adhesion and conditioning mechanism between clay minerals and water/surfactant solution was revealed. Thus, sodium dodecyl benzene sulfonate surfactant was selected as the main composition of the soil conditioner. Then, the adhesion stress before and after soil conditioning and the contact angles between clay minerals and water/surfactant solution were tested and analyzed at the macroscopic scale. The result shows that the contact angle between droplet and clay mineral surface is an important parameter to characterize soil adhesion. The simulation rules of the microscopic contact angle are consistent with the experiment results. Furthermore, the adsorption energy between microscopic substances is dominated by electrostatic force, which can reflect the adhesion stress between macroscopic substances. Soil adhesion stress can be effectively decreased by adding the surfactant to the soil conditioner.

The Feasibility and Operational Performance of Implementation Median U-turn Intersections: A CRITIC Method

Currently, a growing number of cities are adopting the Median-U-Turn (MUT) intersection design to enhance road capacity and traffic efficiency. The critical question in selecting the right intersection design is how significantly the implementation of MUT can enhance intersection performance, focusing on three key aspects: intersection efficiency, capacity, and the environmental impact of the design. To address this question, an evaluation of operational performance under various prevailing conditions (roadway and control) was conducted using VISSIM, a microscopic simulation platform. This evaluation involved five scenarios: conventional intersections (with increased cycle length, grade separation with a signalized at-grade intersection, grade separation with a roundabout), MUT, and signalized crossover MUT at a dense urban arterial intersection in Amman, Jordan's capital. The performance was compared using several metrics: average control delay, number of stops, average travel speed and time, average stopped delay, Carbon Monoxide (CO) emissions, fuel consumption, and vehicle safety. The Criteria Importance Through Intercriteria Correlation (CRITIC) technique was subsequently used to select the optimal design. The findings indicate that the existing intersection configuration is the least effective, while the MUT with signals at the crossing U-turn points is the most efficient solution.