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CHI 2020 Late-Breaking Work CHI 2020, April 25–30, 2020, Honolulu, HI, USA Initial Evaluation of Different Types of Virtual Reality Locomotion Towards a Pedestrian Simulator for Urban and Transportation Planning Julian Kreimeier Daniela Ullmann Abstract Nuremberg Institute of Nuremberg Institute of The simulation of human behaviour in today’s travel demand Technology Technology models is usually based on the assumption of a rational be- Nuremberg, D-90408 Nuremberg, D-90408 haviour of its participants. Since travel demand models have Germany Germany julian.kreimeier@ohm- daniela.ullmann@ohm- been applied in particular for motorized traffic, only little is university.eu university.eu 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 en- courage cycling and walking, we propose a VR (Virtual Re- Harald Kipke Timo Götzelmann ality) pedestrian simulator which involves walk-in-place loco- Nuremberg Institute of Nuremberg Institute of motion. Thus, identical conditions are obtained for all sub- Technology Technology jects which is not feasible in real world field research with Nuremberg, D-90408 Nuremberg, D-90408 naturally varying environmental influences. As a first step, Germany Germany our qualitative and quantitative user study revealed that walk- harald.kipke@ohm- timo.goetzelmann@ohm- university.eu university.eu ing 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. Author Keywords Virtual Reality, Walk-in-Place Locomotion, Urban Space Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation CCS Concepts on the first page. Copyrights for third-party components of this work must be honored. •Human-centered computing ! User studies; Virtual re- For all other uses, contact the owner/author(s). CHI ’20 Extended Abstracts, April 25–30, 2020, Honolulu, HI, USA. ality; •Computing methodologies ! Interactive simula- © 2020 Copyright is held by the author/owner(s). tion; ACM ISBN 978-1-4503-6819-3/20/04. http://dx.doi.org/10.1145/3334480.3382958 LBW068, Page 1 CHI 2020 Late-Breaking Work CHI 2020, April 25–30, 2020, Honolulu, HI, USA Introduction Related Work Although human beings have traveled exclusively on foot for The idea to simulate road usage to obtain information about millions of years, walking is the least explored mean to real- traffic jams, capacities and waiting times of different types of ize mobility. In a world mostly shaped by motorized transport urban infrastructures isn’t entirely new, since the late 2000s systems, walking is oftentimes considered as an anachronis- research even apply VR technology (e.g., [4]). A very de- tic way of getting around and most often receives only little tailed and up-to-date overview in this regard can be found Importance of Bipedalism in attention in public perception and research. Besides cycling, at [3]. One of the most established approaches for a mi- Urban Spaces walking appears as the second to none most energy-efficient croscopic traffic simulation are computer programs like VIS- A 2019 study of the German and unrestricted form of mobility and promises an positive SIM or SUMO (Simulation of Urban MObility) [7]. These Institute for Applied Social Sci- impact on the health of an urban society. And there is an- tools help to visualize measures and assess the effect of ences [10] showed that 83% of other important aspect of walking: Its significance in every- planning concepts to draw conclusions concerning the traf- participants over the age of 14 day life (e.g., walking from the car or bicycle to the apartment fic quality. The focus of these simulations is not on quali- perceive walking as the most or to the bus stop). Each chain of paths begins and ends with tative parameters and human behavior, but on the calcula- pleasant way to get around and by foot, and yet we know only little about influencing factors tion of quantitative data to answer which measure provides 41% walk almost every day, and behavior parameters of walking. However, in traditional the most efficient parameters like delay, travel time, stops, which is more than cycling or us- traffic engineering, the focus on walking as an independent queues, speeds and density [6], both for motorized and non- ing public transportation. type of travel mode is interpreted from a technically centered motorized road users. However, the pedestrian movement Mostly, the "last mile" of any kind point of view. But it is especially interesting and relevant to in- is based on the ’Social Force Model’ [8] with forces in anal- of urban movement is done by vestigate how and why walking in urban spaces is subject to ogy to Newtonian mechanics. These forces are repulsive foot. Thus, an intuitive and real- sensitive stimuli here. These influence both the acceptance from obstacles [16] and have a considerable influence on istic VR pedestrian simulator is and the choice of route and destination. To the authors’ best the pedestrians’ destination and route choice. This approach a promising opportunity to bet- knowledge, there are up to now no findings on physiological- can be implemented with ’cellular automata’ [15] which di- ter understand this sustainable quantitative correlations which affect the pedestrians’ ambi- vide the simulated area into single, individually connected and effective, but yet underrep- ent awareness and the endogenous expenses valuation. So cells that can be occupied by pedestrians. This method is resented way of moving around far, only empirically measured observations led to qualitative used for simulations of crowds, such as the evacuation of in urban areas. By using innova- and very general presumptions of causality (e.g., [18, 19]). events or waiting lines on train stations [9, 5]. But visual tive VR research in pedestrian At this point, VR technology can be meaningfully applied to or acoustic aspects of urban spaces are often not consid- research, this field can be given investigate possible correlations in a (virtual) environment, ered. There is only one field study from 1993 which analyzed more attention. which is identical to all subjects and can be analyzed more the effect of an attractive or unattractive urban environment precisely than in field work. To achieve this, we propose the on the behavior of pedestrians [12]. It was found that peo- use of a walk-in-place approach, which, in combination with ple in an attractive environment are more willing to walk and a HMD (Head mounted display) and headphones, enables thus accept a longer access route to the public transport sta- audiovisually walking in a (virtual) urban space. At the begin- tion. Correspondingly, attractive environments are described ning of this development, we initially evaluated different types as ’car-free’ but any further parameters or precise recom- of walk-in-place locomotion with 15 subjects on the basis of mendations for urban environments are not provided. How- a route to be covered via a virtual crossroads, see Fig.1. ever, it’s unknown to what extent simulations like VISSIM or LBW068, Page 2 CHI 2020 Late-Breaking Work CHI 2020, April 25–30, 2020, Honolulu, HI, USA SUMO correspond to reality. Beside VR bicycle simulators Question and level of measurement (e.g., [11]), there are also advanced implementations of vir- How safe did you feel when using this type of locomotion? tual car-driving [3], even with animated traffic [7] or the so- 1 (low) - 10 (high) cial interaction between a car driver and a pedestrian while How precise were you able to walk in VR? crossing an intersection [14]. These models explore vehicle 1 (low) - 10 (high) and road safety data of electric or autonomous vehicles [3], How intuitive were your movements? but pedestrians are neglected. 1 (low) - 10 (high) In order to better understand the perception of an urban space, How do you rate the simulated walking speed? there are first results which measured emotions like stress of 1 (too low) - 10 (too fast) Walk-in-Place Locomotion pedestrians and cyclists in public spaces. A ’smartband’ was How did your energy expenditure match up with real walking? Using a so-called ’walk-in-place’ used to monitor physiological changes in real-world condi- 1 (too low) - 10 (too high) approach, virtual environments tions [17], but none of these were carried out in a laboratory What is your bottom line of this type of locomotion? can be mapped to the limited with identical conditions and different types of participants Qualitative feedback size of real spaces in order (e.g., regarding age, transport use). Thus, it is difficult to to be walkable. In correlation generalize and compare findings of these field research re- Table 1: The questionnaire used in our experiment. with today’s technical possibili- sults. In order to tackle this problem, we propose a novel VR ties, there are many interesting based pedestrian simulator including walk-in-place locomo- rience. After a detailed briefing and explanation, each par- and sophisticated implementa- tion, as we will present in the following. ticipant learned how to use each hardware implementation, tions, e.g. [1, 2]. Our Experiment walked along the previously discussed route and filled our questionnaire afterwards. This questionnaire asked for the The first step to achieve a precise and intuitive walking simu- subjects’ feeling of safety, precision and intuitiveness as well lation in a virtual urban space is the physiological calibration, as realistic speed and energy expenditure and one’s indi- environmental influences can be evaluated later.

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