Car following with an inertia-oriented driving technique: A driving simulator experiment

Tenenboim, Einat ; Lucas-Alba, Antonio (Universidad de Zaragoza) ; Melchor, Óscar M. ; Toledo, Tomer ; Bekhor, Shlomo

Resumen: For many decades, car-following (CF) and congestion models have assumed a basic invariance: drivers’ default driving strategy is to keep the safety distance. The present study questions that Driving to keep Distance (DD) is a traffic invariance and, therefore, that the difference between the time required to accelerate versus decelerate must necessarily determine the observed patterns of traffic oscillations. Previous studies have shown that drivers can adopt alternative CF strategies like Driving to keep Inertia (DI) by following basic instructions. The present work aims to test the effectiveness of a DI course that integrates 4 tutorials and 4 practice sessions in a standard PC computer designed to learn more adaptive driving behaviors in dense traffic. Methods. Sixty-eight drivers were invited to follow a leading car that varied its speed on a driving simulator, then they took a DI course on a PC computer, and finally they followed a fluctuating leader again on the driving simulator. The study adopted a pretest-intervention-posttest design with a control group. The experimental group took the full DI course (tutorials and then simulator practice). The control group had access to the DI simulator but not to the tutorials. Results. All participating drivers adopted DD as the default CF mode on the pre-test, yielding very similar results. But after taking the full DI course, the experimental group showed significantly less accelerations, decelerations, and speed variability than the control group, and required greater CF distance, that was dynamically adjusted, spending less fuel in the post-test. A group of 8 virtual cars adopting DD required less space on the road to follow the drivers that took the DI course.

Idioma: Inglés

DOI: 10.1016/j.trf.2022.06.003

Año: 2022

Publicado en: Transportation research. Part F, Traffic psychology and behaviour 89 (2022), 72-83
ISSN: 1369-8478

Factor impacto JCR: 4.1 (2022)

Categ. JCR: TRANSPORTATION rank: 18 / 37 = 0.486 (2022) - Q2 - T2
Categ. JCR: PSYCHOLOGY, APPLIED rank: 26 / 83 = 0.313 (2022) - Q2 - T1

Factor impacto CITESCORE: 8.4 - Engineering (Q1) - Psychology (Q1) - Social Sciences (Q1)

Factor impacto SCIMAGO: 1.352 - Applied Psychology (Q1) - Transportation (Q1) - Civil and Structural Engineering (Q1) - Automotive Engineering (Q1)

Tipo y forma: Article (Published version)

Área (Departamento): Área Psicología Básica (Dpto. Psicología y Sociología)