基于DEVS的交叉路口建模与仿真

考虑有信号控制的交叉路口内车辆之间、车辆与行人之间的冲突，在离散事件仿真规范（DEVS）框架下构建了交叉路口微观交通仿真模型.以某市典型交叉路口观察数据标定仿真参数，将仿真结果与按《城市道路设计规范》计算得到的通行能力进行比较，验证了模型.在此基础上，首先，仿真分析了不同左转比例对交叉路口通行能力的影响；然后，基于各方向等待通过交叉路口的车辆数目设计了智能绿信比控制策略.仿真试验表明：通行能力随着左转车比例的增加先上升后下降；智能绿信比控制能显著提升交叉路口通行能力，明显降低平均引道延误时间.由此证明仿真模型能真实地模拟交叉路口各因素间的相互作用，且易于扩充，通用性强，能够用于其它智能交通问题的研究.     

基于数值仿真的人车碰撞事故再现研究

对于对未留制动印迹的人车碰撞事故采用数值仿真方法进行再现研究,提出了通过调整碰撞车速使得仿真结果(人体抛距、人体损伤情况等)逼近真实事故结果的方法估计碰撞车速,并应用于一起真实事故的再现研究,初步验证了模型和方法的可行性.采用上述经过验证的数值模型研究人车碰撞初始条件对仿真结果的影响发现:人车相对接触位置接近汽车前部一侧时对人体抛距值的影响较大,因此单纯根据人体抛距估计碰撞车速可能会造成再现结果的失真.     

AA‐FVDM: An accident‐avoidance full velocity difference model for animating realistic street‐level traffic in rural scenes

Most of existing traffic simulation efforts focus on urban regions with a coarse two‐dimensional representation; relatively few studies have been conducted to simulate realistic three‐dimensional traffic flows on a large, complex road web in rural scenes. In this paper, we present a novel agent‐based approach called accident‐avoidance full velocity difference model (abbreviated as AA‐FVDM) to simulate realistic street‐level rural traffics, on top of the existing FVDM. The main distinction between FVDM and AA‐FVDM is that FVDM cannot handle a critical real‐world traffic problem while AA‐FVDM settles this problem and retains the essence of FVDM. We also design a novel scheme to animate the lane‐changing maneuvering process (in particular, the execution course). Through numerous simulations, we demonstrate that besides addressing a previously unaddressed real‐world traffic problem, our AA‐FVDM method efficiently (in real time) simulates large‐scale traffic flows (tens of thousands of vehicles) with realistic, smooth effects. Furthermore, we validate our method using real‐world traffic data, and the validation results show that our method measurably outperforms state‐of‐the‐art traffic simulation methods.Copyright © 2013 John Wiley & Sons, Ltd.     

Modeling and simulation of overtaking behavior involving environment

Overtaking is a complex driving behavior for intelligent vehicles. Current research on modeling overtaking behavior pays little attention on the effect of environment. This paper focuses on the modeling and simulation of the overtaking behavior in virtual reality traffic simulation system involving environment information, such as road geometry and wind. First, an intelligent vehicle model is proposed to better understand environment information and traffic situation. Then, overtaking behavior model is introduced in detail, the lane changing feasibility is analyzed and the fuzzy vehicle controllers considering the road and wind effect are researched. Virtual reality traffic simulation system is designed to realize the simulation of overtaking behavior, with realistic road geometry features. Finally, simulation results show the correctness and the effectiveness of our approach.     

Crowd Simulation and Its Applications: Recent Advances

This article surveys the state-of-the-art crowd simulation techniques and their selected applications, with its focus on our recent research advances in this rapidly growing research field. We first give a categorized overview on the mainstream methodologies of crowd simulation. Then, we describe our recent research advances on crowd evacuation,pedestrian crowds, crowd formation, traffic simulation, and swarm simulation. Finally, we offer our viewpoints on open crowd simulation research challenges and point out potential future directions in this field.     

Cognition-Driven Traffic Simulation for Unstructured Road Networks

Dynamic changes of traffic features in unstructured road networks challenge the scene-cognitive abilities of drivers, which brings various heterogeneous traffic behaviors. Modeling traffic with these heterogeneous behaviors would have significant impact on realistic traffic simulation. Most existing traffic methods generate traffic behaviors by adjusting parameters and cannot describe those heterogeneous traffic flows in detail. In this paper, a cognition-driven trafficsimulation method inspired by the theory of cognitive psychology is introduced. We first present a visual-filtering model and a perceptual-information fusion model to describe drivers’ heterogeneous cognitive processes. Then, logistic regression is used to model drivers’ heuristic decision-making processes based on the above cognitive results. Lastly, we apply the high-level cognitive decision-making results to low-level traffic simulation. The experimental results show that our method can provide realistic simulations for the traffic with those heterogeneous behaviors in unstructured road networks and has nearly the same efficiency as that of existing methods.

     

Calibrating a social force based model for simulating personal mobility vehicles and pedestrian mixed traffic

Personal mobility vehicles (PMVs), such as the Segway, have recently gained remarkable popularity as an alternative transport mode for short-distance trips in indoor and outdoor settings. Before allowing them on shared sidewalks, where the pedestrian and cyclist demand is high, interactions between PMV riders and other shared space users should be properly understood. Further, the designs of shared sidewalks and implementation policies should also be evaluated. Calibrated microscopic simulation tools could facilitate such purposes. This study aims to explore the applicability of a social force based microscopic simulation model, which was originally used to simulate pedestrian movements and interactions, for Segway and pedestrian mixed traffic. The parameters of the model are calibrated with data collected through controlled experiments under different Segway–pedestrian interaction scenarios. Lateral and longitudinal avoidance distances measured from trajectory data collected in a different controlled experiment was used to validate the model for a Segway rider avoiding a pedestrian. The findings of this study suggest that, with proper calibration, the social force model can potentially be used to simulate Segway-like PMVs and pedestrian mixed traffic.     

A conflict–congestion model for pedestrian–vehicle mixed evacuation based on discrete particle swarm optimization algorithm

A simulation model based on temporal–spatial conflict and congestion for pedestrian–vehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub-group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrian–vehicle conflict levels.     

Detailed traffic animation for urban road networks

We present a new agent-based system for detailed traffic animation on urban arterial networks with diverse junctions like signalized crossing, merging and weaving areas. To control the motion of traffic for visualization and animation purposes, we utilize the popular follow-the-leader method to simulate various vehicle types and intelligent driving styles. We also introduce a continuous lane-changing model to imitate the vehicle’s decision-making process and dynamic interactions with neighboring vehicles. By applying our approach in several typical urban traffic scenarios, we demonstrate that our system can well visualize vehicles’ behaviors in a realistic manner on complex road networks and generate immersive traffic flow animations with smooth accelerating strategies and flexible lane changes.     

A methodology for determining equivalent factors in heterogeneous pedestrian flows

Similar to vehicle traffic, pedestrian flow can also be classified as heterogeneous. This paper introduces the concept of equivalent factors for converting heterogeneous pedestrian flow into equivalent base flow derived from vehicle traffic methodologies. The methodology computes equivalent mixed traffic flow and uniform flow for the same performance measure. To account for both temporal and spatial variations in pedestrian characteristics, time–space (TS) occupancy is the performance measure employed. This measure can deal with diversities in both walking speeds and body sizes, which are the two factors identified to test the methodology for the proof of concept. A micro-simulation approach is used to generate input data for computation of the equivalent factors in lieu of collected data. Inputs for the micro-simulation models are derived from literature for comparison between simulation and empirical results. Results show the robustness of the methodology in taking into account pedestrian walking speed and body size differences. An application of the equivalent factors illustrates the importance of considering heterogeneity in pedestrian walkway design. This methodology can be adopted to compute local pedestrian equivalent factors from field collected data.     

面向智能驾驶测试的仿真场景构建技术综述

随着汽车智能化程度的不断提高,智能汽车通过环境传感器与周边行驶环境的信息交互与互联更为密切,需应对的行驶环境状况也越来越复杂,包括行驶道路、周边交通和气象条件等诸多因素,具有较强的不确定性、难以重复、不可预测和不可穷尽。限于研发周期和成本、工况复杂多样性,特别是安全因素的考虑,传统的开放道路测试试验或基于封闭试验场的测试难以满足智能驾驶系统可靠性与鲁棒性的测试要求。因此,借助数字虚拟技术的仿真测试成为智能驾驶测试验证一种新的手段,仿真场景的构建作为模拟仿真的重要组成部分,是实现智能驾驶测试中大样本、极限边界小概率样本测试验证的关键技术,这对提升智能驾驶系统的压力和加速测评水平显得尤为重要。面向智能驾驶测试的仿真场景构建技术已成为当前汽车智能化新的研究课题和世界性的研究热点,作为一种新兴技术仍面临许多挑战。本文提出了面向智能驾驶测试的仿真场景构建方法,系统阐述了国内外研究工作的进展与现状,包括场景自动构建方法和交通仿真建模方法,重点分析一些值得深入研究的问题并围绕场景构建技术的发展趋势进行了讨论分析,最后介绍了团队相关研究在2020中国智能驾驶挑战赛仿真赛和世界智能驾驶挑战赛的仿真场景应用情况。     

Analysis of a cellular automaton model for car traffic with a slow-to-stop rule

We propose a modification of the widely known Benjamin–Johnson–Hui (BJH) cellular automaton model for single-lane traffic simulation. In particular, our model includes a ‘slow-to-stop’ rule that exhibits more realistic microscopic driver behaviour than the BJH model. We present some statistics related to fuel economy and pollution generation and show that our model differs greatly in these measures. We give concise results based on extensive simulations using our system.     

Developing a software toolkit for urban traffic modeling

ATLAS is a modeling language that permits a static view of a city section to be defined for simulating traffic in closed areas. We propose a methodology that is focused on the user while being able to improve the software development activities. The models are formally specified, avoiding a high number of errors in the application, thus reducing the problem solving time. Streets are characterized by their traffic direction, number of lanes, etc. Once the urban section is outlined, the traffic flow is automatically set up. Specialized behavior is included to model traffic lights, trucks, traffic signs, railways, etc. The basic idea is to provide a mapping into DEVS and Cell‐DEVS models that can be easily executed with a simulation tool. As the modelers can focus on the problem to solve, development times for the simulators can be dramatically reduced. A front‐end system allows the user to draw city sections (and then parse the drawing to create a valid ATLAS file), and an output subsystem permitting cars to be shown with realistic 3D graphics. Copyright © 2007 John Wiley & Sons, Ltd.     

Modeling vehicle–pedestrian interactions outside of crosswalks

Pedestrian and driver behaviors as well as their interactions, are essential in planning, designing and operating highway facilities. Pedestrian crossing outside of a marked or unmarked crosswalk (i.e. jaywalking), is one of those pedestrian behaviors that may highly affect safety and operations. Unlike permissible crossings at crosswalks, jaywalking events are not often anticipated by drivers, which may result in less driver reaction time and different vehicle operation dynamics. It is important to understand pedestrian crossing behavior outside of crosswalks, as well as driver yielding behavior towards them. To date, limited quantitative and behavioral research has been conducted to investigate this interaction or simulate it microscopically. This paper aims to explore both pedestrian jaywalking behavior (gap acceptance and speeds) and the corresponding driver reactions (yielding behavior) for modeling the vehicle–pedestrian interactions (VPI) outside the crosswalks in a micro-simulation environment. The study also quantifies the differences between vehicle–jaywalker and vehicle-permissible crossing. An observational study and an instrumented vehicle study were conducted on the campus of the University of Florida to collect data from pedestrian and driver perspectives, respectively.Crossing speed, yield acceptance and delay of jaywalking crossings and permissible crossings were observed in the study and these attributed can be used for replicating pedestrian operations in simulators. Moreover, behaviors of driver approaching jaywalkers versus pedestrians crossing at designated crosswalks were compared on the basis of yield rates, and vehicle speed profiles. Vehicle yield dynamics were analyzed to model the driver reactions towards jaywalkers. Lastly, it was found that the locations of jaywalking events are highly concentrated and influenced by the crossing environment, such as pedestrian and vehicular volume, bus stops presence and crossing distance.This paper establishes several quantitative relationships describing interactions between pedestrians crossing outside of crosswalks and approaching drivers, which provide the basis and assumptions for modeling such interactions in a micro-simulation environment for traffic operational analyses.     

Learnt Real‐time Meshless Simulation

We present a new real‐time approach to simulate deformable objects using a learnt statistical model to achieve a high degree of realism. Our approach improves upon state‐of‐the‐art interactive shape‐matching meshless simulation methods by not only capturing important nuances of an object's kinematics but also of its dynamic texture variation. We are able to achieve this in an automated pipeline from data capture to simulation. Our system allows for the capture of idiosyncratic characteristics of an object's dynamics which for many simulations (e.g. facial animation) is essential. We allow for the plausible simulation of mechanically complex objects without knowledge of their inner workings. The main idea of our approach is to use a flexible statistical model to achieve a geometrically‐driven simulation that allows for arbitrarily complex yet easily learned deformations while at the same time preserving the desirable properties (stability, speed and memory efficiency) of current shape‐matching simulation systems. The principal advantage of our approach is the ease with which a pseudo‐mechanical model can be learned from 3D scanner data to yield realistic animation. We present examples of non‐trivial biomechanical objects simulated on a desktop machine in real‐time, demonstrating superior realism over current geometrically motivated simulation techniques.     

An agent-based model of the influence of neighbourhood design on daily trip patterns

Post-war suburban neighbourhoods are often criticised for promoting automobile use and leading to problems such as traffic congestion, air pollution, automobile reliance, limited transit access and reduced social interactions. Newer designs, such as the neo-traditional and fused grid designs, aim to ameliorate these problems. But neighbourhood trip and traffic patterns are the collective outcome of individual decisions. Such phenomena often cannot be adequately explained by traditional aggregated methods. With consideration of personal characteristics, preferences and feedbacks between pedestrian and automobile traffic, an agent-based trip and traffic simulation model was developed and calibrated based on data from Ottawa, Ontario. Experiments show that the neo-traditional and fused grid designs generally provide more pedestrian benefits such as fewer crossings, shorter facility-access distance, less emission exposure and more social interaction opportunities, but these benefits also depend on the implementation such as the location of pedestrian-only routes. The influences are often complex. For example, elimination of pedestrian-only routes may lead to more social opportunities, but also much higher emission exposure. The study shows the importance of complex system based study of urban and neighbourhood designs, and the promise of a meso-level approach to urban and transportation simulation that can improve planning outcomes.     

无信号人行横道交通流特性的研究

考虑到行人穿越人行横道特点和心理因素,构建人行横道处机动车和行人相互干扰行为的元胞自动机模型。模型中重新制定行人和机动车的冲突干扰规则,引入临界安全间隙和临界决策间隙概念计算行人的通过概率,根据行人过街等待时间阈值定义了行人的冒险概率。模拟结果显示,临界决策间隙、行人忍耐时间阈值和行人的临界跟随间隙对机动车与行人流量均有不同程度的影响,其中行人的临界跟随间隙对交通流影响最大。     

基于多智能体的信号交叉口微观仿真

交通系统是一个典型的多智能体系统（Multi-Agent System,MAS）。应用多智能体技术建立了信号交叉口微观仿真模型,给出了机动车Agent的三层结构,详细分析了机动车在信号交叉口中的基于期望间隙和期望速度的运动决策逻辑,探讨了机动车加速度模型。针对国内交通仿真软件缺少行人与非机动车模拟的不足,以元胞自动机模型为基础引入了行人及非机动车实体,使得仿真系统更具实用性。给出了该仿真系统的实现结果和结论。     

Interactive thin elastic materials

Despite great strides in past years are being made to generate motions of elastic materials such as cloth and biological skin in virtual world, unfortunately, the computational cost of realistic high‐resolution simulations currently precludes their use in interactive applications. Thin elastic materials such as cloth and biological skin often exhibit complex nonlinear elastic behaviors. However, modeling elastic nonlinearity can be computationally expensive and numerically unstable, imposing significant challenges for their use in interactive applications. This paper presents a novel simulation framework for simulating realistic material behaviors with interactive frame rate. Central to the framework is the use of a constraint‐based multi‐resolution solver for efficient and robust modeling of the material nonlinearity. We extend a strain‐limiting method to work on deformation gradients of triangulated surface models in three‐dimensional space with a novel data structure. The simulation framework utilizes an iterative nonlinear Gauss–Seidel procedure and a multilevel hierarchy structure to achieve computational speedups. As material nonlinearity are generated by enforcing strain‐limiting constraints at a multilevel hierarchy, our simulation system can rapidly accelerate the convergence of the large constraint system with simultaneous enforcement of boundary conditions. The simplicity and efficiency of the framework makes simulations of highly realistic thin elastic materials substantially fast and is applicable of simulations for interactive applications. Copyright © 2015 John Wiley & Sons, Ltd.     

An expert fuzzy system for predicting object collisions. Its application for avoiding pedestrian accidents

Collision among moving objects in space is one of the most common risks in daily life. In this context, we have developed an abstract model that allows to detect the presence of risk of future collisions among objects from the video content analysis. Our proposal carries out several stages. First, a camera calibration process calculates the real location of object in scene. Then, we estimate the object speed and their future trajectory in order to predict possible collisions. All the information of the objects is described in an ontology. Using the properties of objects (such as location, speed, trajectories), we have defined a fuzzy rule that permits to identify whether an object is in danger because another could hit him. The use of fuzzy logic results in two points: the collision detection is gradual and the model can be adjusted through membership functions to fuzzy concepts. Furthermore, the proposed model is easily adaptable to any situation and can be applied on various fields. With the aim of testing our proposal, we have focused on pedestrian accidents, a case of special interest since a lot of pedestrians die or are injured in traffic accidents daily. We have developed an application based on our model that is able to predict, in real time, the traffic accidents where a vehicle could run over a pedestrian. The obtained results in the experimental stage show a high performance of the system.