Recent technological advancements are revolutionizing last-mile package delivery, with autonomous delivery vehicles (ADVs) emerging as a sustainable alternative. These small ground vehicles autonomously navigate pavements, aiming to operate seamlessly in pedestrian-rich environme
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Recent technological advancements are revolutionizing last-mile package delivery, with autonomous delivery vehicles (ADVs) emerging as a sustainable alternative. These small ground vehicles autonomously navigate pavements, aiming to operate seamlessly in pedestrian-rich environments without any human intervention. The goal of this project is to design a concept of an autonomous delivery vehicle that portrays predictable behaviour for pedestrians.
Extensive research involving literature analysis, interviews, and observational studies unveiled the challenges that current ADVs are facing, including unpredictable behaviour and distrust. The absence of predictability has a big impact on effective on-road communication, and it potentially leads to unsafe traffic interactions. A viable solution lies in communicating the ADV's driving intent. This study delves into the nuances of intent communication in pedestrian environments, and identifies intent signals that are predominantly communicated through body language. The objective is to replicate human-like signals in the behaviour of ADVs, to ensure an intuitive understanding of such cues from previous traffic experiences.
Focusing on designing predictability through intent communication via body language, a test exploration is conducted, testing multiple different prototypes. Iterative trials resulted in interesting insights and eventually lead to the most promising intent signal – the "Looking" scenario. This intent signal is inspired by a head-turning or someone looking into the desired walking direction. Participants recognised this signal, facilitating an intuitive understanding of the meaning of the signal.
The evaluation test confirmed the intent signal's positive effect on enhancing pedestrians' feelings of safety, trust, and comfort during an ADV interaction. These increased feelings of safety, trust and comfortability came from the fact that they were able to predict the movements of the ADV and because they felt "seen". The robot reacted to the participants by showing its intent, this reaction gave participants the perception that the ADV has indeed detected them and therefore won't collide with them. Consequently, it is recommended to integrate intent communication into ADV designs to ensure safer and more harmonious ADV-pedestrian interactions.
Three design guidelines are formulated based on the insights from the exploration phase. The three guidelines emphasize the interpretation, visibility, and relevance of intent signals. The conceptual ADV design presented in this project, aligns with these guidelines. The intent signal in the design concept of the ADV makes their behaviour more predictable, gives people a sense of control because they feel detected, which both leads to an increase in safety, trust, and comfortability. Although the intent signal shows great promise in creating a safer and more comfortable traffic interaction between ADVs and pedestrians, additional research is needed to fully understand the impact of integrating this intent signal.