Assessing pedestrian safety across modalities via a simulated vehicle time-to-arrival task

Effect of Signal Design of Autonomous Vehicle Intention Presentation on Pedestrians' Cognition

In this study, a method is devised that allows the intentions of autonomous vehicles to be effectively communicated to pedestrians and passengers via an efficient interactive interface. Visual and auditory factors are used as variables to investigate the effects of different autonomous vehicle signal factors on the judgment of pedestrians and to determine the main factors such that the best combination can be proposed. Two visual dimensions (i.e., color and flashing) and three auditory dimensions (i.e., rhythm, frequency, and melody) are used as the experimental signal variables. In addition, deceleration and waiting-to-restart scenarios are investigated. Multiple-choice questions and a subjective cognition scale are used for evaluation. The results show that the combination of green and slow rhythm can be used for the road-user-first case, whereas the combination of red and fast rhythm can be used for the vehicle-first case. Under the same intention, factors of color, flashing, rhythm, and melody are highly similar in terms of the combination mode, except for the frequency. In the deceleration and waiting-to-restart scenarios, the frequencies of the best signal are high and low frequencies, respectively. The results of this study can be used as a reference for the signal design of autonomous vehicles in the future and provide ideas for the interactions between autonomous vehicles and pedestrians.

Overestimated time-to-collision for quiet vehicles: Evidence from a study using a novel audiovisual virtual-reality system for traffic scenarios

To avoid collision, pedestrians intending to cross a road need to estimate the time-to-collision (TTC) of an approaching vehicle. Here, we present a novel interactive audiovisual virtual-reality system for investigating how the acoustic characteristics (loudness and engine type) of vehicles influence the TTC estimation. Using acoustic recordings of real vehicles as source signals, the dynamic spatial sound fields corresponding to a vehicle approaching in an urban setting are generated based on physical modeling of the sound propagation between vehicle and pedestrian and are presented via sound field synthesis. We studied TTC estimation for vehicles with internal combustion engine and for loudness-matched electric vehicles. The vehicle sound levels were varied by 10 dB, independently of the speed, presented TTC, and vehicle type. In an auditory-only condition, the cars were not visible, and lower loudness of the cars resulted in considerably longer TTC estimates. Importantly, the loudness of the cars also had a significant effect in the same direction on the TTC estimates in an audiovisual condition, where the cars were additionally visually presented via interactive virtual-reality simulations. Thus, pedestrians use auditory information when estimating TTC, even when full visual information is available. At equal loudness, the TTC judgments for electric and conventional vehicles were virtually identical, indicating that loudness has a stronger effect than spectral differences. Because TTC overestimations can result in risky road crossing decisions, the results imply that vehicle loudness should be considered as an important factor in pedestrian safety.

The Effectiveness of Selected Devices to Reduce the Speed of Vehicles on Pedestrian Crossings

Accidents involving pedestrians often result in serious injury or death. The main goal of this conducted research is to evaluate selected devices that will help reduce the speed of vehicles on pedestrian crossings. Many devices from a group of “speed control measures” and “mid block tools” (refugee islands, speed tables, and raised pedestrian crossings) are examined to find the most effective ones. In our research, the range of reduction of a vehicle’s speed is used as a main measure of effectiveness, but a wider statistical analysis was conducted as well. One of the results of the research is the identification of three categories of devices referred to as high effectives (good), medium effectives (intermediate), and low or lack of effectives (bad). The content of the paper starts by highlighting the reasons to reduce the vehicle’s speed on pedestrian crossings (as an introduction). Next, we present the description of devices used to reduce the vehicle’s speed with a presentation of the research of their effectiveness. The studies that have been conducted are described in the following chapters: first, the characteristic of method and location, second, with discussion, the results of research and identification of the three categories of devices. The paper is then summarized by conclusions and comments. The research only covered the issues of road traffic engineering. The research was made in Poland, but the conclusions could be useful worldwide due to similar traffic rules and technical solutions.

A Systematic Review of Virtual Reality Applications for Automated Driving: 2009–2020

While virtual reality (VR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of VR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to VR technology, at present, the pool of findings is heterogeneous and non-transparent. We investigated N = 176 scientific papers of relevant journals and conferences with the goal to analyze the status quo of existing VR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of VR technology which is applicable at specific level of vehicle automation and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on designing automotive experiences in VR, safety aspects, and vulnerable road users. Trust, simulator and motion sickness, and external human-machine interfaces (eHMIs) also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Finally, we discuss a set of open challenges, and give recommendation for future research in automated driving at the VR side of the reality-virtuality continuum.