Integrating Naturalistic Insights in Objective Multi-Vehicle Safety Framework
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866915215517417472 |
|---|---|
| author | Del Re, Enrico Aghanouri, Amirhesam Olaverri-Monreal, Cristina |
| author_facet | Del Re, Enrico Aghanouri, Amirhesam Olaverri-Monreal, Cristina |
| contents | As autonomous vehicle technology advances, the precise assessment of safety in complex traffic scenarios becomes crucial, especially in mixed-vehicle environments where human perception of safety must be taken into account. This paper presents a framework designed for assessing traffic safety in multi-vehicle situations, facilitating the simultaneous utilization of diverse objective safety metrics. Additionally, it allows the integration of subjective perception of safety by adjusting model parameters. The framework was applied to evaluate various model configurations in car-following scenarios on a highway, utilizing naturalistic driving datasets. The evaluation of the model showed an outstanding performance, particularly when integrating multiple objective safety measures. Furthermore, the performance was significantly enhanced when considering all surrounding vehicles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_09769 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrating Naturalistic Insights in Objective Multi-Vehicle Safety Framework Del Re, Enrico Aghanouri, Amirhesam Olaverri-Monreal, Cristina Robotics As autonomous vehicle technology advances, the precise assessment of safety in complex traffic scenarios becomes crucial, especially in mixed-vehicle environments where human perception of safety must be taken into account. This paper presents a framework designed for assessing traffic safety in multi-vehicle situations, facilitating the simultaneous utilization of diverse objective safety metrics. Additionally, it allows the integration of subjective perception of safety by adjusting model parameters. The framework was applied to evaluate various model configurations in car-following scenarios on a highway, utilizing naturalistic driving datasets. The evaluation of the model showed an outstanding performance, particularly when integrating multiple objective safety measures. Furthermore, the performance was significantly enhanced when considering all surrounding vehicles. |
| title | Integrating Naturalistic Insights in Objective Multi-Vehicle Safety Framework |
| topic | Robotics |
| url | https://arxiv.org/abs/2408.09769 |