PERANCANGAN PERBAIKAN PROTOTIPE KENDARAAN OTONOM “SEATER” DENGAN PENDEKATAN TRUST, INTERACTION, DAN RECEPTIVITY PEJALAN KAKI

Autonomous vehicle (AV) technology is planned to be implemented in Ibu Kota Negara (IKN) in East Kalimantan. In line with this plan, AV are already being developed in Indonesia with support from the government’s “Making Indonesia 4.0” program. To realize this program, Badan Riset dan Inovasi Nasi...

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Bibliographic Details
Main Author: Levina, Josephine
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/86129
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Autonomous vehicle (AV) technology is planned to be implemented in Ibu Kota Negara (IKN) in East Kalimantan. In line with this plan, AV are already being developed in Indonesia with support from the government’s “Making Indonesia 4.0” program. To realize this program, Badan Riset dan Inovasi Nasional (BRIN) focus on research on autonomous electric vehicles. The autonomous electric vehicle currently being developed by BRIN is a Single-passenger, Electric Autonomous Transporter (Seater). Seater is still a prototype and requires user validation before it can be used in the transportation system. Trust, interaction, and receptivity between out-vehicle users such as pedestrians, are important in the implementation AV into the transportation system. However, the absence of the driver in AV causes concerns and uncertainties, leading to reduced trust and acceptance towards AV. This study aims to evaluate the autonomous vehicle “Seater” from the perspectives of pedestrian’s trust, interaction, and receptivity towards the AV before “Seater” is ready for use in a real environment. This study consists of experiment and questionnaires. The experiment involved 20 participants using an eye tracker and Perception Neuron 2.0 while interacting with AV under three task of experiments and two conditions with and without passengers on the AV. The eye tracker was used to analyze trust derived from the gaze durations of participants towards AV. Perception Neuron 2.0 was used to analyze participant’s motions and walking speed, and a camera to analyze participant behavior with AV. After conducting the experiment, participants performed retrospective thinking-aloud (RTA) related to their reflection on the experience during the experiment, filled out subjective evaluations regarding their understanding of the AV’s movement and perceived of safety, also filled out the pedestrian receptivity towards fully autonomous vehicle (PRQF). The PRQF questionnaire was used to analyze factors influencing receptivity towards AV, including safety, interaction, and compatibility. The questionnaire consists of 15 questions and was distributed digitally to 241 people. The scale used was a Likert scale with 5 points, ranging from 1 (strongly disagree) to 5 (strongly agree). The results of this study show that participants do not fully trust AV. From the eye tracker result, participants gaze durations were longer when there was a passenger on the AV. The RTA results found that 75% of participants felt safer when there was passenger on the AV. The subjective evaluation result indicated that 40% of participants did not understand the AV’s movement and 60% of participants felt safe when interaction with the AV. The interaction between participants and AV showed that participants were cautious about AV’s movement. The questionnaire results found that the factors of interaction, and compatibility had a positive relationship with receptivity,but the relationship between receptivity and safety could not be concluded due to the occurence of Heywood case. Therefore, a review of the questionnaire model is necessary duet o multicollinearity and indicators that did not measure the constructs well. Based on these findings, a proposed solution was designed in the form of external Human-Machine Interfaces (eHMI) using lights and audio indicators to show AV’s movement intentions, which is expected to increase pedestrians trust and sense of safety towards AV.