Review Article Review of Virtual Traffic Simulation and Its Applications

e increasing number of vehicles in cities brings new challenges to urban traffic management. Analyzing and modeling traffic is of great practical significance to urban intelligent traffic management. In this paper, the existing traffic simulation research is reviewed and summarized. Firstly, the crowd modeling and crowd animation are analyzed by referring to the idea of crowd simulation. Secondly, it compares and analyzes various existing car following technologies, and points out that animated traffic simulation is a hotspot in traffic simulation research. And then the concept of affective computing is integrated into the traffic simulation, considering the impacts of drivers’ emotion on vehicle driving and it is pointed out that the emotion-driven traffic flow is more authentic. Finally, combined with the status quo, the existing research drawbacks are analyzed, and the direction of future traffic simulation is pointed out.

[1]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[2]  Dirk Helbing,et al.  A mathematical model for the behavior of pedestrians , 1991, cond-mat/9805202.

[3]  E. Hatfield,et al.  Emotional Contagion , 1995 .

[4]  Yiannis E. Papelis,et al.  The Iowa Driving Simulator: An Immersive Research Environment , 1995, Computer.

[5]  Yiannis E. Papelis,et al.  Driving simulation: challenges for VR technology , 1996, IEEE Computer Graphics and Applications.

[6]  M. Schreckenberg,et al.  Microscopic Simulation of Urban Traffic Based on Cellular Automata , 1997 .

[7]  Peter Willemsen,et al.  Directable behavior models for virtual driving scenarios , 1997 .

[8]  Craig W. Reynolds Steering Behaviors For Autonomous Characters , 1999 .

[9]  Zhen Liu,et al.  Behavior animation for simulation of virtual pedestrians near a road , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[10]  Yasuhisa Hasegawa,et al.  Zipping, weaving: control of vehicle group behavior in non-signalized intersection , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  James J. Kuffner,et al.  Autonomous behaviors for interactive vehicle animations , 2004, SCA '04.

[12]  Demetri Terzopoulos,et al.  Autonomous pedestrians , 2005, SCA '05.

[13]  Ivan Prebil,et al.  3D road traffic situation simulation system , 2005, Adv. Eng. Softw..

[14]  Adrien Treuille,et al.  Continuum crowds , 2006, SIGGRAPH 2006.

[15]  Karsten Schwan,et al.  Dynamic Data Driven Application Simulation of Surface Transportation Systems , 2006, International Conference on Computational Science.

[16]  Kincho H. Law,et al.  A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations , 2007, AI & SOCIETY.

[17]  Dimitris N. Metaxas,et al.  Eurographics/ Acm Siggraph Symposium on Computer Animation (2007) Group Behavior from Video: a Data-driven Approach to Crowd Simulation , 2022 .

[18]  Ge Hong-Xia,et al.  A modified coupled map car-following model based on application of intelligent transportation system and control of traffic congestion , 2007 .

[19]  Charlie C. L. Wang,et al.  Interactive Control of Large-Crowd Navigation in Virtual Environments Using Vector Fields , 2008, IEEE Computer Graphics and Applications.

[20]  H. Bruch,et al.  The positive group affect spiral: a dynamic model of the emergence of positive affective similarity in work groups , 2008 .

[21]  Ana Paiva,et al.  A model for emotional contagion based on the emotional contagion scale , 2009, 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops.

[22]  Christopher E. Peters,et al.  Modeling Groups of Plausible Virtual Pedestrians , 2009, IEEE Computer Graphics and Applications.

[23]  Daniel Thalmann,et al.  YaQ: An Architecture for Real-Time Navigation and Rendering of Varied Crowds , 2009, IEEE Computer Graphics and Applications.

[24]  Ming C. Lin,et al.  Continuum Traffic Simulation , 2010, Comput. Graph. Forum.

[25]  Georgios Ch. Sirakoulis,et al.  An FPGA implemented cellular automaton crowd evacuation model inspired by the electrostatic-induced potential fields , 2010, Microprocess. Microsystems.

[26]  Jehee Lee,et al.  Morphable crowds , 2010, SIGGRAPH 2010.

[27]  Nadir Farhi Piecewise linear car-following modeling , 2011 .

[28]  Julien Pettré,et al.  Imperceptible relaxation of collision avoidance constraints in virtual crowds , 2011, ACM Trans. Graph..

[29]  Norman I. Badler,et al.  How the Ocean Personality Model Affects the Perception of Crowds , 2011, IEEE Computer Graphics and Applications.

[30]  Soyoung Ahn,et al.  A behavioural car-following model that captures traffic oscillations , 2012 .

[31]  Dinesh Manocha,et al.  A statistical similarity measure for aggregate crowd dynamics , 2012, ACM Trans. Graph..

[32]  Ludovic Hoyet,et al.  Push it real , 2012, ACM Trans. Graph..

[33]  Laheeb Ibrahim,et al.  Traffic Simulation System based on Fuzzy Logic , 2012, Complex Adaptive Systems.

[34]  Haneen Farah,et al.  Latent class model for car following behavior , 2012 .

[35]  Ko Nishino,et al.  Tracking Pedestrians Using Local Spatio-Temporal Motion Patterns in Extremely Crowded Scenes , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  Xiaogang Jin,et al.  Detailed traffic animation for urban road networks , 2012, Graph. Model..

[37]  Michel C. A. Klein,et al.  Modelling collective decision making in groups and crowds: Integrating social contagion and interacting emotions, beliefs and intentions , 2013, Autonomous Agents and Multi-Agent Systems.

[38]  Siome Goldenstein,et al.  Crowd simulation: applying mobile grids to the social force model , 2012, The Visual Computer.

[39]  Wenzhi Chen,et al.  Adaptive-AR Model with Drivers' Prediction for Traffic Simulation , 2013, Int. J. Comput. Games Technol..

[40]  Xiaogang Jin,et al.  Video-based personalized traffic learning , 2013, Graph. Model..

[41]  Shriniwas S Arkatkar,et al.  Estimating capacity for eight-lane divided urban expressway under mixed-traffic conditions using computer simulation , 2013 .

[42]  Jin Wei,et al.  An Emotion Contagion Simulation Model for Crowd Events , 2013 .

[43]  Su Hu Microscopic Traffic Model in Virtual Environment , 2013 .

[44]  Dihua Sun,et al.  On the stability analysis of microscopic traffic car-following model: a case study , 2013 .

[45]  Zhigang Deng,et al.  A personality model for animating heterogeneous traffic behaviors , 2014, Comput. Animat. Virtual Worlds.

[46]  Mingliang Xu,et al.  Collective motion in a minimal continuous model , 2014 .

[47]  Tong Li,et al.  A new car-following model with two delays , 2014 .

[48]  Haris N. Koutsopoulos,et al.  Do cooperative systems make drivers' car-following behavior safer? , 2014 .

[49]  Zhigang Deng,et al.  Crowd Simulation and Its Applications: Recent Advances , 2014, Journal of Computer Science and Technology.

[50]  Dinesh Manocha,et al.  Velocity-based modeling of physical interactions in dense crowds , 2015, The Visual Computer.

[51]  Yi-Cheng Chen,et al.  Interactive Visual Analysis for Vehicle Detector Data , 2015, Comput. Graph. Forum.

[52]  Hua Wang,et al.  An efficient lane model for complex traffic simulation , 2015, Comput. Animat. Virtual Worlds.

[53]  Emilio Luque,et al.  Crowd Evacuations SaaS: An ABM Approach , 2015, ICCS.

[54]  Zhigang Deng,et al.  Collective Crowd Formation Transform with Mutual Information–Based Runtime Feedback , 2015, Comput. Graph. Forum.

[55]  Pei Lv,et al.  miSFM: On combination of Mutual Information and Social Force Model towards simulating crowd evacuation , 2015, Neurocomputing.

[56]  Zhigang Deng,et al.  Vehicle–pedestrian interaction for mixed traffic simulation , 2015, Comput. Animat. Virtual Worlds.

[57]  Sai-Keung Wong,et al.  Generating Believable Mixed-Traffic Animation , 2016, IEEE Transactions on Intelligent Transportation Systems.

[58]  Y. Ge,et al.  Expressing Anger Is More Dangerous than Feeling Angry when Driving , 2016, PloS one.

[59]  Xin Yang,et al.  Real‐virtual fusion model for traffic animation , 2017, Comput. Animat. Virtual Worlds.

[60]  Qunsheng Peng,et al.  Group Modeling: A Unified Velocity‐Based Approach , 2017, Comput. Graph. Forum.

[61]  Hua Wang,et al.  Shadow traffic: A unified model for abnormal traffic behavior simulation , 2018, Comput. Graph..

[62]  Zhigang Deng,et al.  Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis , 2018, IEEE Transactions on Visualization and Computer Graphics.

[63]  Xiaogang Jin,et al.  Force-based Heterogeneous Traffic Simulation for Autonomous Vehicle Testing , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[64]  Bing Zhou,et al.  Crowd Behavior Evolution With Emotional Contagion in Political Rallies , 2019, IEEE Transactions on Computational Social Systems.

[65]  Mingliang Xu,et al.  Crowd queuing simulation with an improved emotional contagion model , 2019, Science China Information Sciences.

[66]  Yong Gan,et al.  Traffic Simulation and Visual Verification in Smog , 2019, ACM Trans. Intell. Syst. Technol..

[67]  Zhigang Deng,et al.  Dictionary-based Fidelity Measure for Virtual Traffic , 2020, IEEE Transactions on Visualization and Computer Graphics.

[68]  Dinesh Manocha,et al.  Heter-Sim: Heterogeneous Multi-Agent Systems Simulation by Interactive Data-Driven Optimization , 2018, IEEE Transactions on Visualization and Computer Graphics.

[69]  Hua Wang,et al.  Crowd Behavior Simulation With Emotional Contagion in Unexpected Multihazard Situations , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.