In VR locomotion, walking performance can vary significantly depending on the locomotion method. In our study, participants completed in total 12 walking trials in virtual environments using either arm-swing or joystick method. Arm-swing interface maintains stable trajectory control from the outset, while joystick locomotion shows significant improvement with repeated trials, indicating a strong learning effect across different scenes. These findings suggest that physical locomotion method may be preferable for tasks requiring immediate stability, whereas artificial locomotion may excel in scenarios allowing for practice and demanding high precision.

Research on cycling safety has recently gained the attention of the HCI community. While there have been multiple proposals for automated driving features on bikes, we are unaware of a project that systematically aims to translate and evaluate driver assistance systems from the automotive to the bike domain to promote cycling safety in traffic. Thus, we implemented an adaptive cruise control and a lane-keeping/centering system with hard- and software on a motion-based bicycle simulator and investigated their potential in a virtual reality experiment. Based on performance measurements and subjective ratings, results showed significant improvements in technology acceptance, subjective workload, and driving performance regarding the cruise control. In contrast, the lane-centering and lane-keeping features were rated significantly worse than the baseline without such assistance. The paper concludes with a critical reflection on automated driving features for bicycles.

With the increasing development of Virtual Reality, locomotion has become an essential component of interaction in VR. Currently, various locomotion technologies have been developed to provide users with a natural walking experience in virtual environments. However, the multiple walking techniques impact users’ walking experience in different ways. Simulator sickness is a common issue in VR experiences. Since different walking methods may influence simulator sickness differently, we conducted a user study to evaluate simulator sickness in walking with three relevant walking methods: real walking, arm-swing, and omnidirectional treadmill, and the results indicated that these three walking methods caused different levels of simulator sickness, and people perceived stronger sickness when they walked on the omnidirectional treadmill.

Research on cyclists‘ safety and comfort is a growing topic. Existing works address support systems with novel interaction concepts such as augmented reality but also the design and evaluation of high-fidelity bicycle simulators. Since the field is still in its exploratory phase, there have been few attempts to systematically provide guidance for conducting experiments. For example, there is no consensus on the choice of representative driving scenarios, the proper choice of different bicycle simulators, and measurement standards to systematically compare the results of different studies. With this workshop, we want the community to gather and discuss a roadmap for the future of HCI bicycle research so that these issues can be overcome.