Julian Kreimeier
ABSTRACT
The simulation of human behaviour in today's travel demand models is usually based on the assumption of a rational behaviour of its participants. Since travel demand models have been applied in particular for motorized traffic, only little is known about the influence of variables that affect both the choice of trip destination and the route decision in pedestrian and cycling models. In order to create urban spaces that encourage cycling and walking, we propose a VR (Virtual Reality) pedestrian simulator which involves walk-in-place locomotion. Thus, identical conditions are obtained for all subjects which is not feasible in real world field research with naturally varying environmental influences. As a first step, our qualitative and quantitative user study revealed that walking in a VR treadmill felt safest and most intuitive, although walking in it took in return more energy than walking-in-place with VR trackers only.
Supplemental Material
- Costas Boletsis. 2017. The new era of virtual reality locomotion: A systematic literature review of techniques and a proposed typology. Multimodal Technologies and Interaction 1, 4 (2017), 24.Google Scholar
Cross Ref
- Fabio Buttussi and Luca Chittaro. 2019. Locomotion in Place in Virtual Reality: A Comparative Evaluation of Joystick, Teleport, and Leaning. IEEE transactions on visualization and computer graphics (2019).Google Scholar
- Qianwen Chao, Huikun Bi, Weizi Li, Tianlu Mao, Zhaoqi Wang, Ming C Lin, and Zhigang Deng. 2019. A survey on visual traffic simulation: models, evaluations, and applications in autonomous driving. In Computer Graphics Forum. Wiley Online Library.Google Scholar
- Wang Chun, Chen Ge, Liu Yanyan, and Margaret Horne. 2008. Virtual-reality based integrated traffic simulation for urban planning. In 2008 International Conference on Computer Science and Software Engineering, Vol. 2. IEEE, 1137--1140.Google ScholarDigital Library
- Patrick Dickinson, Kathrin Gerling, Kieran Hicks, John Murray, John Shearer, and Jacob Greenwood. 2019. Virtual reality crowd simulation: effects of agent density on user experience and behaviour. Virtual Reality 23, 1 (2019), 19--32.Google ScholarDigital Library
- Martin Fellendorf and Peter Vortisch. 2010. Microscopic traffic flow simulator VISSIM. In Fundamentals of traffic simulation. Springer, 63--93.Google Scholar
- Deepeka Garg, Maria Chli, and George Vogiatzis. 2019. Traffic3D: A New Traffic Simulation Paradigm. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 2354--2356.Google Scholar
- Dirk Helbing and Peter Molnar. 1995. Social force model for pedestrian dynamics. Physical review E 51, 5 (1995), 4282.Google Scholar
- Jun Hu, Xiaoling Gao, Juan Wei, Yongyong Guo, Mei Li, and Jierui Wang. 2019. The cellular automata evacuation model based on Er/M/1 distribution. Physica Scripta (2019).Google Scholar
- infas Institute for Applied Social Science. 2019. Mobility in Germany - Analyses of bicycle traffic and foot traffic. (2019). http://www.mobilitaet-in-deutschland.de/pdf/MiD2017_Analyse_zum_Rad_und_Fussverkehr.pdfGoogle Scholar
- Heather Kaths, Andreas Keler, Jakob Kaths, and Fritz Busch. 2019. Analyzing the behavior of bicyclists using a bicycle simulator with a coupled SUMO and DYNA4 simulated environment. EPiC Series in Computing 62 (2019), 199--205.Google ScholarCross Ref
- Hermann Knoflacher. 1993. Does the Development of Mobility in Traffic Follow a Pattern. History and Technology 15 (1993), 125--140.Google Scholar
- Julian Kreimeier and Timo Götzelmann. 2019. First Steps Towards Walk-In-Place Locomotion and Haptic Feedback in Virtual Reality for Visually Impaired. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, LBW2214.Google Scholar
- Christian Lehsing, Tobias Benz, and Klaus Bengler. 2016. Insights into interaction-effects of human-human interaction in pedestrian crossing situations using a linked simulator environment. IFAC-PapersOnLine 49, 19 (2016), 138--143.Google ScholarCross Ref
- Yang Li, Maoyin Chen, Xiaoping Zheng, Zhan Dou, and Yuan Cheng. 2020. Relationship between behavior aggressiveness and pedestrian dynamics using behavior-based cellular automata model. Appl. Math. Comput. 371 (2020), 124941.Google Scholar
- Ramin Mehran, Alexis Oyama, and Mubarak Shah. 2009. Abnormal crowd behavior detection using social force model. In 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 935--942.Google ScholarCross Ref
- Javier Nuñez, Inaian Teixeira, Antônio Silva, Peter Zeile, Luc Dekoninck, and Dick Botteldooren. 2018. The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists. Sustainability 10, 7 (2018), 2379.Google ScholarCross Ref
- LSC Pun-Cheng and CWY So. 2019. A comparative analysis of perceived and actual walking behaviour in varying land use and time. Journal of Location Based Services 13, 1 (2019), 53--72.Google ScholarCross Ref
- Charles W Schmidt. 2019. The why and where of active travel: modeling bike and foot traffic across the United States. Environmental health perspectives 127, 3 (2019), 034002.Google Scholar
Index Terms
- Initial Evaluation of Different Types of Virtual Reality Locomotion Towards a Pedestrian Simulator for Urban and Transportation Planning
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