The Influence of Fixed and Moving NPC on Pedestrians’ Avoidance Behaviors: VR-Based Experiments


  • Weisong Liu University of Science and Technology of China, Hefei, China
  • Jun Zhang University of Science and Technology of China, Hefei, China
  • Weiguo Song University of Science and Technology of China, Hefei, China



Pedestrians’ avoidance behavior, Virtual Reality, Movement NPC, Fixed NPC


Pedestrians have to take actions when crossing other pedestrians to avoid collisions. In this work, we focus on the differences of avoidance behaviors when a pedestrian crosses a moving and fixed intruder (NPC) in the virtual environment. The avoidance process is divided into three stages using the start avoidance point and maximum lateral deviation point. In moving NPC experiments, the distance from start avoidance point to the potential collision point (CP) first decreases and then increases as the intrusion angle increases. In standing NPC experiments, pedestrians start avoidance closer to the CP (average distance: 3.73m). In moving NPC experiments, the average maximum lateral offset distance (MLD) for the pedestrians to detour decreases with the intrusion angles decreases (Behind MLD ∈[1.09 m, 1.94 m], Front MLD ∈[1.13 m, 1.56 m]). In standing NPC experiments, the average MLD is 1.01m (left: 1.04m, right: 0.98m), which is the closest to the MLD of pedestrians at 180° intrusion angles. What’s more, at 30°, 60°, 90° and 120° intrusion angles, pedestrians avoiding behind the NPC require higher MLD than others avoiding in front of the NPC. Thus, more subjects prefer to avoid in front of the NPC under these conditions (88%, 86%, 78%, 69% of all). But the preference weakens and disappears at 150° and 180° intrusion angles due to the decrease of MLD. In standing NPC experiments, significant left-right preference is not found in pedestrians’ avoidance strategies (right: 46%, left: 54%). This article quantitatively analyses the difference between the influence of fixed and movement NPC on pedestrians’ avoidance strategies. The mechanism of pedestrian’s avoidance behavior is obtained by analyzing characteristic parameters, which is helpful to adjust pedestrian avoidance prediction models and design humanoid robots.


W. Lv, W.G. Song, J. Ma, Z.M. Fang: A Two-Dimensional Optimal Velocity Model for Unidirectional Pedestrian Flow Based on Pedestrian's Visual Hindrance Field. Ieee Transactions on Intelligent Transportation Systems 14, 1753-1763 (2013), doi:10.1109/tits.2013.2266340

S.M. Bourgaize, B.J. McFadyen, M.E. Cinelli: Collision avoidance behaviours when circumventing people of different sizes in various positions and locations. Journal of Motor Behavior 53, 166-175 (2021), doi:10.1080/00222895.2020.1742083

A.G. Knorr, L. Willacker, J. Hermsdörfer, S. Glasauer, M. Krüger:Influence of person- and situation-specific characteristics on collision avoidance behavior in human locomotion. Journal of Experimental Psychology: Human Perception and Performance 42, 1332-1343 (2016), doi:10.1037/xhp0000223

M. Lappe, M. Huber, Y.-H. Su, M. Krüger, K. Faschian, S. Glasauer, J. Hermsdörfer: Adjustments of Speed and Path when Avoiding Collisions with Another Pedestrian. PLoS ONE 9(2013), doi:10.1371/journal.pone.0089589

D.R. Parisi, P.A. Negri, L. Bruno: Experimental characterization of collision avoidance in pedestrian dynamics.Physical Review E 94(2016), doi:10.1103/PhysRevE.94.022318

X. Shan, J. Ye, X. Chen: Critical walking space requirement for collision avoidance of pedestrians: an experimental study. In: CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems, 2369-2380 (2014), doi:10.1061/9780784413623.227

W. Daamen, S. Hoogendoorn, M. Campanella, D. Versluis: Interaction Behavior Between Individual Pedestrians. In:Springer International Publishing, Cham, 1305-1313 (2014), doi:10.1007/978-3-319-02447-9$_$107

Z. Feng, V.A. Gonzalez, M. Trotter, M. Spearpoint, J. Thomas, D. Ellis, R. Lovreglio: How people make decisions during earthquakes and post-earthquake evacuation: Using Verbal Protocol Analysis in Immersive Virtual Reality. Safety Science 129(2020), doi:10.1016/j.ssci.2020.104837

M. Kinateder, B. Comunale, W.H. Warren: Exit choice in an emergency evacuation scenario is influenced by exit familiarity and neighbor behavior. Safety Science 106,170-175(2016), doi:10.1016/j.ssci.2018.03.015

B.A. Baxter, W.H. Warren: Route selection in barrier avoidance.Gait $&$ Posture 80,192-198(2020), doi:10.1016/j.gaitpost.2020.04.009

J. Bruneau, A.-H. Olivier, J. Pettre: Going through, going around: A study on individual avoidance of groups.Ieee Transactions on Visualization and Computer Graphics 21,520-528(2015), doi:10.1109/tvcg.2015.2391862

S.D. Lynch, R. Kulpa, L.A. Meerhoff, J. Pettre, A. Cretual, A.-H. Olivier,Collision Avoidance Behavior between Walkers: Global and Local Motion Cues.IEEE Transactions on Visualization and Computer Graphics 24, 2078-2088(2018), doi:10.1109/tvcg.2017.2718514

X. Wei, W. Lv, W. Song, X. Li: Survey study and experimental investigation on the local behavior of pedestrian groups.Complexity 20,87-97(2015), doi:10.1002/cplx.21633




How to Cite

Liu, W., Zhang, J., & Song, W. (2022). The Influence of Fixed and Moving NPC on Pedestrians’ Avoidance Behaviors: VR-Based Experiments. Collective Dynamics, 6, 1–15.



Pedestrian and Evacuation Dynamics 2021