How Should an Electric Truck Sound? A User-Centered Path to Safer, Smarter AVAS Design

What is it about?

Electric trucks are quiet. That is good for reducing noise pollution, but it also creates a basic safety problem: pedestrians and cyclists may not hear them early enough, especially at low speeds in cities. This is where Acoustic Vehicle Alerting Systems, or AVAS, become important. But designing AVAS for trucks is not as simple as taking the sound from an electric car and making it louder. Trucks carry a different meaning. People expect them to sound bigger, heavier, and more powerful. The study behind this article asked a practical question: how can we design an electric truck warning sound that still feels electric, but also clearly feels like a truck? The central idea of the research is simple. A good AVAS should not be built only from regulations or from sound level measurements. It should also be built around how people actually hear and describe vehicle sounds. That is why the study combined user feedback, listening tests, semantic evaluation, and psychoacoustic analysis into one design process. In the workflow described in the paper, the researchers first gathered user expectations, then compared real vehicle sounds, then linked perception to measurable sound features, and finally tested newly synthesized warning sounds. The first step was to ask people what they wanted from an electric truck sound. In an open-ended survey with 29 participants, people described a tension that sound designers often face: the sound should be noticeable enough for safety, but not so loud or sharp that it becomes annoying in urban areas. Some wanted a deeper, more rumbling and truck-like sound. Others preferred something more futuristic and less noisy. Several responses pointed toward the same balance: audible, distinctive, lower in pitch than electric cars, and clearly different from existing car AVAS sounds. The next step was to compare real sounds from different vehicle categories. The semantic profiling experiment used 24 vehicle sounds, including ICE trucks, ICE cars, electric cars with and without AVAS, and electric trucks with and without AVAS. Twenty-one participants rated these sounds using 24 semantic terms such as hard, powerful, roaring, buzzing, whistling, annoying, and truck-like. This matters because it translates vague impressions into structured data. Instead of saying “this sound feels wrong,” listeners can show how it feels wrong. That experiment revealed a clear pattern. ICE trucks were perceived as more truck-like, thicker, and more powerful. Electric cars with AVAS tended to sound more whistling, howling, and less thick. Most importantly, the current electric truck sounds in the study were judged as too thin, too high-pitched, and not truck-like enough. In other words, existing AVAS approaches were carrying the “electric” identity, but not the “truck” identity. That is a critical result, because it suggests that simply reusing e-car warning sounds for heavy-duty vehicles is a poor design shortcut. To move from description to design, the paper linked perception to psychoacoustic features. Think of psychoacoustics as the bridge between physics and hearing: not just what frequencies exist in a sound, but how rough, tonal, fluctuating, or annoying that sound feels to a listener. The analysis showed that “truck-like” perception was associated with stronger tonality in the 7th–12th Bark bands and with low-frequency fluctuation and roughness that supported a “roaring” character. “Electric-like” perception, by contrast, depended more on higher-frequency tonality, especially in the 13th–18th Bark bands, and on cues above about 1 kHz. The paper also identified “buzzing” as a useful perceptual marker for electric identity. This led to a practical design strategy. Instead of copying existing vehicles, the researchers synthesized new AVAS sounds from scratch. They used sawtooth waves to create buzzing electric cues, narrowband noise to imitate some of the harmonic structure of ICE truck engines, and turbine-like components to suggest a larger vehicle. They also experimented with low-pass filtering and different spectral combinations to shape harshness, depth, and annoyance. A validation study with 20 participants then tested 35 sounds, including both real vehicle sounds and synthesized candidates. The result is encouraging. The synthesized sounds performed better than real reference sounds on several dimensions, including electric-like character, truck-like character, and buzzing. At the same time, the study confirmed a real design challenge: electric-like and truck-like qualities tend to pull in opposite directions. The more a sound feels electric, the less it may feel like a truck, and vice versa. That means AVAS design is not about maximizing one attribute. It is about tuning a compromise that gives pedestrians useful information without creating unnecessary annoyance. One of the strongest contributions of the paper is that it turns this compromise into concrete design principles. The study argues that designers should increase truck-likeness rather than directly reuse current EV AVAS sounds, strengthen lower-frequency roaring-related cues, use buzzing carefully to preserve electric identity, and place electric design cues mainly above 1 kHz. It also suggests that annoyance can be reduced by controlling excessive high-frequency energy while preserving enough tonality for detectability and identity. That is a far more useful takeaway than “make it louder” or “make it futuristic.” It gives sound designers a structured path. The broader message is bigger than trucks. This work shows how product sound design can be treated as both an engineering problem and a human-perception problem. A warning sound is not just a signal. It communicates size, category, intent, and even brand character. For electric trucks, the sound must tell people: “I am electric, but I am also large, heavy, and worth noticing.” The paper shows that user-centered psychoacoustic design can help build that message more effectively than regulation-driven minimum compliance alone. The next step is real-world validation. The paper points out that current standards such as UNECE R138 and FMVSS 141 do not yet fully address the special case of heavy-duty electric trucks. Future work should therefore test these sounds in real traffic, under real masking conditions, and with the acoustic effects of actual truck structures and weights. That is where laboratory design principles become deployable mobility solutions.

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Photo by Sander Yigin on Unsplash

Photo by Sander Yigin on Unsplash