Zero-Emission Vehicles Sonification Strategy Based on Shepard-Risset Glissando

International audienceIn this paper we present a sonification strategy developed for electric vehicles aiming to synthetize a new engine sound to enhance the driver's dynamic perception of his vehicle. We chose to mimic the internal combustion engine (ICE) noise by informing the driver through pitch variations. However, ICE noise pitch variations are correlated to the engine's rotations per minute (RPM) and its dynamics is covered within a limited vehicle speed range. In order to inform the driver with a significant pitch variation throughout the full vehicle speed range, we based our sonification strategy on the Shepard-Risset glissando. These illusory infinite ascending/descending sounds enable to represent accelerations with significant pitch variations for an unlimited range of speeds. In a way, we stay within the metaphor of ICE noise with unheard gearshifts. We tested this sonification strategy in a perceptual test in a driving simulator and showed that the mapping of this acoustical feedback affects the drivers' perception of vehicle dynamics

Towards a methodology for assessing electric vehicle exterior sounds

Laws mandate that electric vehicles emit sounds to ensure pedestrians' safety by alerting pedestrians of the vehicles' approach. Additionally, manufacturers want these sounds to promote positive impressions of the vehicle brand. A reliable and valid methodology is needed to evaluate electric vehicles' exterior sounds. To help develop such a methodology, this paper examines automotive exterior sound evaluation methods in the context of experimental design and cognitive psychology. Currently, such evaluations are usually conducted on road or inside a laboratory; however, a virtual environment provides advantages of both these methods but none of their limitations. The stimuli selected for evaluations must satisfy legislative guidelines. Methods for presenting and measuring the stimuli can affect study outcomes. A methodology is proposed for conducting evaluations of an electric vehicle's exterior sounds, testing its detectability and emotional evaluation. An experiment tested the methodology. Thirty-one participants evaluated an electric car in a virtual environment of a town's T-junction with 15 exterior sounds as stimuli. The car's arrival time, direction of approach, and, thus, distance to pedestrian varied across conditions. Detection time of the sound and pleasantness and powerfulness evaluations of the car were recorded. The vehicle's arrival time and approach direction affected its detectability and emotional evaluation; thus, these are important elements to vary and control in studies. Overall, the proposed methodology increases the realistic context and experimental control than in existing listening evaluations. It benefits by combining two competing elements necessary for assessing electric vehicle exterior sounds, namely, pedestrians' safety and impressions of the vehicle brand

Making Appearances:How Robots Should Approach People

To prepare for a future in which robots are more commonplace, it is important to know what robot behaviors people find socially normative. Previous work suggests that for robots to be accepted by people, the robot should adhere to the prevalent social norms, such as those related to approaching people. However, we do not expect that socially normative approach behaviors for robots can be translated on a one-on-one basis from people to robots, because currently robots have unique and different features to humans, including (but not limited to) wheels, sounds, and shapes. The two studies presented in this article go beyond the state-of-the-art and focus on socially normative approach behaviors for robots. In the first study, we compared people's responses to violations of personal space done by robots compared to people. In the second study, we explored what features (sound, size, speed) of a robot approaching people have an effect on acceptance. Findings indicate that people are more lenient toward violations of a social norm by a robot as compared to a person. Also, we found that robots can use their unique features to mitigate the negative effects of norm violations by communicating intent.</p

Audiovisual Integration of Time-to-Contact Information for Approaching Objects

Abstract Previous studies of time-to-collision (TTC) judgments of approaching objects focused on effectiveness of visual TTC information in the optical expansion pattern (e.g., visual tau, disparity). Fewer studies examined effectiveness of auditory TTC information in the pattern of increasing intensity (auditory tau), or measured integration of auditory and visual TTC information. Here, participants judged TTC of an approaching object presented in the visual or auditory modality, or both concurrently. TTC information provided by the modalities was jittered slightly against each other, so that auditory and visual TTC were not perfectly correlated. A psychophysical reverse correlation approach was used to estimate the influence of auditory and visual cues on TTC estimates. TTC estimates were shorter in the auditory than the visual condition. On average, TTC judgments in the audiovisual condition were not significantly different from judgments in the visual condition. However, multiple regression analyses showed that TTC estimates were based on both auditory and visual information. Although heuristic cues (final sound pressure level, final optical size) and more reliable information (relative rate of change in acoustic intensity, optical expansion) contributed to auditory and visual judgments, the effect of heuristics was greater in the auditory condition. Although auditory and visual information influenced judgments, concurrent presentation of both did not result in lower response variability compared to presentation of either one alone; there was no multimodal advantage. The relative weightings of heuristics and more reliable information differed between auditory and visual TTC judgments, and when both were available, visual information was weighted more heavily

Understanding and improving methods for exterior sound quality evaluation of hybrid and electric vehicles

Electric and Hybrid Electric Vehicles [(H)EVs] are harder for pedestrians to hear when moving at speeds below 20 kph. Laws require (H)EVs to emit additional exterior sounds to alert pedestrians of the vehicles’ approach to prevent potential collisions. These sounds will also influence pedestrians’ impression of the vehicle brand. Current methods for evaluating (H)EV exterior sounds focus on “pedestrians’ safety” but overlook its influence on “vehicle brand”, and do not balance experimental control, correct context along with external and ecological validity. This research addresses the question: “How should (H)EV exterior sounds be evaluated?” The research proposes an experimental methodology for evaluating (H)EV exterior sounds that assesses pedestrians’ safety and influence on the vehicle brand by measuring a listener’s detection rate and sound quality evaluation of the (H)EV in a Virtual Environment (VE). This methodology was tested, improved and validated through three experimental studies based on their findings. Study 1 examined the fidelity of the VE setup used for experiments. The VE was immersive with sufficient degree of involvement/control, naturalness, resolution, and interface quality. It also explored a new interactive way of evaluating (H)EV sounds where participants freely navigate the VE and interact with vehicles more naturally. This interactivity increased the experiments’ ecological validity but reduced reliability and quadrupled the experiment duration compared to using a predefined scenario (non-interactive mode). Thus, a predefined scenario is preferred. Study 2 tested the non-interactive mode of the proposed methodology. Manipulating the target vehicle’s manoeuvre by varying factors, namely the vehicle’s “arrival time”, “approach direction” and “distance of travel”, across the experiment conditions increased ecological validity. This allowed participants to think, respond and pay similar attention as a real world pedestrian. These factors are neglected by existing methodologies, but were found to affect the participants’ detection rate and impression of the vehicle brand. Participants detected the vehicle more than once due to confusion with real world ambient sounds. In the real world, pedestrians continuously detect a vehicle in presence of non-vehicular ambient sounds. Therefore, recommendations to improve the representation of the real-world processes in the vehicle detection during listening experiments include an option to re-detect a vehicle and subjective evaluation of ‘detectability’ of the vehicle sounds. The improved methodology adds ‘detectability’ and ‘recognisability’ of (H)EV sounds as measures and (H)EV’s arrival time as an independent variable. External validity of VEs is a highly debated yet unanswered topic. Study 3 tested external validity of the improved methodology. The methodology accurately predicted participants’ real world evaluations of the detectability of (H)EV sounds, ranked order of the recognisability of (H)EV sounds and their impressions about the vehicle brand. The vehicle’s arrival time affected participants’ detection rate and was reaffirmed as a key element in the methodologies for vehicle sounds’ detection. The final methodological guidelines can help transportation researchers, automotive engineers and legislators determine how pedestrians will respond to the new (H)EV sounds