We have successfully designed and implemented a multi-player, multi-modal virtual reality (VR) co-simulator that integrates both pedestrians and cyclists within the same VR environment. This co-simulator is designed to support multi-player, multi-modal VR experiments aimed at comprehensive data collection in transportation research. It features advanced functionalities including body tracking for pedestrians and cyclists, high-quality digital human representations, and comprehensive data collection technologies such as eye gazing data. A VR experiment was conducted to evaluate the effectiveness of the VR co-simulator and investigate the interactions between vulnerable road users (VRUs) and automated vehicles (AVs) in shared spaces. The assessment demonstrated the co-simulator's capabilities and feasibility in terms of simulator sickness, presence, realism, and usability. The experiment also confirmed the impact of VRU combinations and initial relative positions on the interactions between VRUs and AVs in shared space.

his research explores user feedback on proposed mobility solutions in the Merwe-Vierhavens (M4H) area of Rotterdam to inform the development of Community Mobility Hubs (CMHs). Conducted in two phases, the study began with socio-demographic analysis, followed by Virtual Reality (VR) simulations. The initial phase involved desk research to understand the demographic composition and travel patterns in neighborhoods around M4H. Findings revealed a diverse community with a young population (27-39 years old), including European, Turkish, Moroccan migrants, and Dutch non-migrants, primarily in low-income single or family-with children households. Mobility patterns showed varied travel purposes, such as
shopping, commuting, and recreational activities, with walking, cycling, passenger cars, and public transport being the most common modes of transportation. The second phase used VR to provide an immersive experience of the proposed CMH, engaging participants and gathering detailed feedback. Key findings indicated a strong preference for amenities like cafes, co-working spaces, postal services, and refurbishing centers, especially among first- and second-generation migrants. Significant concerns about affordability, reliability, and availability of mobility solutions were also highlighted. Despite limitations such as potential biases in self-reported data and the fixed nature of the VR simulation, the study’s innovative use of VR provided valuable insights. Recommendations for the CMH include creating solutions for diverse demographics, focusing on families, people of migrant backgrounds, and low-income groups, ensuring accessible, affordable, acceptable, and available transport options. The CMH should incorporate practical features to accommodate various activities, address concerns about affordability, availability, and reliability through ongoing community
dialogue, and emphasize convenience, good maintenance, and diverse pricing schemes. Affordable transportation solutions should be offered, targeting user groups most likely to adopt the solutions, such as females and people of migrant backgrounds. Comprehensive services and family-friendly amenities should be included, and community ownership and management encouraged. Both digital and non-digital access points should be provided, and continuous community engagement maintained. Future research should expand the sample size for better representation and include longitudinal studies to track evolving mobility preferences. Enhancing VR simulation quality and addressing potential biases from tech-savvy participants will provide more balanced insights. This research underscores the importance of understanding diverse mobility needs and innovative citizen participation utilizing VR to create inclusive and effective urban mobility solutions for the M4H community.

Introduction:

As technology advances, autonomous vehicles (AVs), with their advanced sensors and algorithms, are expected to reduce human driving errors and lower traffic accident rates, while also providing convenient mobility for groups such as the elderly and disabled. Meanwhile, electric vehicles (EVs), as new energy vehicles, use electricity instead of fossil fuels, effectively reducing emissions and mitigating environmental issues. However, the low noise of EVs also presents safety risks, especially in urban environments where other road users may not notice them in time. To address this, the European Union has mandated the installation of Acoustic Vehicle Alerting Systems (AVAS) in electric vehicles.

Autonomous vehicles face challenges in communicating with other road users. The application of external Human-Machine Interfaces (eHMI) has significantly improved this interaction, allowing pedestrians and cyclists to better understand vehicle behavior. Studies show that AVs equipped with eHMI increase the sense of safety and trust among road users.

Cyclists, as a vulnerable group, face greater safety risks due to their higher speeds and the interference of wind noise, which can make it difficult to detect auditory signals. Although research on eHMI and AVAS has made progress, there is currently no study on whether autonomous electric vehicles need to be equipped with both systems simultaneously, which warrants further investigation.

Research question:

How does an additional auditory alert system in autonomous electric vehicle equipped with visual eHMI affect the objective and subjective safety of bicycle users?

Research method:

To explore whether the added auditory warning could effectively interrupt cyclists' attention and influence their recognition and judgment of environmental changes, as well as their sense of safety, we conducted a simulation experiment using virtual reality (VR) technology. In a virtual environment, the interaction between autonomous electric vehicles and cyclists was studied to investigate how these warning systems could enhance cyclists' perception of approaching vehicles and improve cycling safety. The experiment was built using Unreal Engine to create realistic virtual city streets, vehicles, buildings, and environmental sound effects. Audio files included idle sounds of electric and traditional fuel vehicles, urban background noise, and warning signal sounds, aiming to replicate a sound environment close to reality.

The experiment took place in the MXR lab, equipped with high-performance computers, a simulated bicycle setup, and high-end VR headsets to provide an immersive experience for participants. Participants rode in multiple simulated scenarios, and data such as real-time trajectories, cycling paths, and speed adjustments were collected. This data was used to assess the impact of auditory warning systems on cyclists' perception of vehicles and their sense of safety.

We recruited 41 participants with varying ages, genders, and cycling experiences to ensure the generalizability of the results. After completing the experiment, each participant filled out a questionnaire to gather their subjective preferences regarding the auditory warning systems, their feelings of safety, and their acceptance of this system for potential future use in autonomous electric vehicles. This qualitative data helped to better understand the potential impact of auditory warning systems in real-world applications and public acceptance.

Result:

First, regarding safety, our experimental data clearly demonstrate that the auditory alert system significantly shortens cyclists' reaction times. When facing potential hazards, hearing an auditory signal allows cyclists to complete avoidance maneuvers earlier, particularly in situations where the low noise levels of electric vehicles make them harder to detect. This is especially crucial in noisy, complex urban environments. The participants' feedback also supports this finding, with over 60% of them stating that relying solely on visual signals is insufficient to ensure complete safety, particularly in urban traffic scenarios.

In terms of comfort, the auditory alert system not only improves the detectability of the vehicle but also helps cyclists perform evasive maneuvers more smoothly and naturally, reducing the psychological stress caused by sudden reactions. Our data show that auditory alerts reduce cyclists' maximum deceleration, allowing them to respond more calmly and avoid panic or discomfort. The survey feedback corroborates this, with participants expressing that the auditory alerts made them feel more at ease, significantly enhancing their overall cycling experience.

However, it’s important to recognize the limitations of this study. First, we only used a simple buzzer as the auditory signal. Future research could incorporate a variety of sounds with different frequencies and volumes to better assess which types of auditory alerts are most effective. Additionally, the participant sample was predominantly younger individuals who were highly familiar with virtual reality, which may limit the generalizability of the results to other demographic groups. The experiment was conducted in a virtual reality environment, which, while controlled, may not fully replicate the complexities of real-world traffic conditions. Therefore, future studies should aim to validate these findings in more diverse environments and with a broader participant base.

Overall, our study suggests that auditory alert systems play a crucial role in enhancing the safety and comfort of interactions between autonomous electric vehicles and cyclists.

Electric vehicles (EVs) are required according to the EU legislation from 2014 to install Acoustic Vehicle Alerting Systems (AVAS) to convey information about the EVs through sound signals to other road users, ensuring their safety. Meanwhile,autonomous vehicles (AVs) are also recommended to be equipped with an External Human-Machine Interface (eHMI) system, enabling better interaction with other road users. . However, for the special group of autonomous electric vehicles (AEVs), considering that equipping both eHMI and AVAS, given their overlapping functionality in conveying information, might result in a waste of resources, it remains unclear whether it's feasible to use only eHMI for communication with road users as a cost-saving measure, thereby omitting AVAS or perhaps adding only a simple sound signal to replace AVAS. This study aims to explore whether autonomous electric vehicles need to add extra noise to provide more information to other vulnerable road users, such as cyclists and pedestrians. In this study, we will use Virtual Reality (VR) technology for simulation experiments. Utilizing VR, as opposed to real-world experiments, allows for precise control over the variables in each experiment, ensuring that experiments can be conducted under the same conditions multiple times, thus enhancing reliability. On the other hand, VR can ensure the safety of experiment participants while providing them with an immersive experience, especially in experiments related to traffic safety research.

In this experiment, we will utilize the Unreal Engine to create a simulated testing environment, focusing on observing participants' (acting as cyclists) reactions to a series of variables. These include different environmental noises, the warning distance of sound signals emitted by autonomous vehicles, and the autonomous vehicles themselves. The sound signal warning distance specifically refers to a mechanism where, when pedestrians or cyclists enter a predefined range of the vehicle, it automatically emits a warning signal. This signal is to alert the approaching individuals that the vehicle is in a ready state and may proceed to the next action, thereby enhancing safety interaction and awareness on the road.

The data collected from this experiment will be divided into two parts: first, the participants' reaction times, speed adjustments, and distances obtained from VR devices; second, their perceptions of the trust, perceived safety, and comfort of interactions with autonomous electric vehicles gathered through post-experiment surveys.

The results of this experiment will assist policymakers in refining relevant laws and regulations, as the existing legislation concerning electric vehicles and AVAS do not take autonomous vehicles into account. It will also provide theoretical support for car manufacturers in the design of autonomous electric vehicles.