Abstract
Assessing the traffic safety and an impact of
Advanced Driver Assistance Systems (ADAS) on it based on
collision data is a challenging task since the crashes are rare
and usually there is a lack of high quality accident data. Still, in
order to be able to evaluate the performance of ADAS, different
Surrogate Safety Measures (SSMs) are continuously introduced
in the literature. Unfortunately, single SSMs have in general
a limited application scope so that combining several SSMs
seems a sensible option. However, combining them to produce
a single value is difficult, as there is not a clear guideline about
the different weights. Against this background, in this paper
we propose a grid-based SSM characterizing the traffic safety
by 6 categories ranging from conflict-free to safety critical.
The advantages of the approach include the ability to perform
a more comprehensive traffic safety analysis or an efficient
comparison of different ADAS by their impact on safety. The
latter one is illustrated by simulation-based comparison of three
Adaptive Cruise Control (ACC) set-ups.
| Original language | English |
|---|---|
| Number of pages | 6 |
| Journal | International Conference on Connected Vehicle and Expo (ICCVE) |
| DOIs | |
| Publication status | Published - 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
Fields of science
- 206002 Electro-medical engineering
- 207109 Pollutant emission
- 202 Electrical Engineering, Electronics, Information Engineering
- 202027 Mechatronics
- 202034 Control engineering
- 203027 Internal combustion engines
- 206001 Biomedical engineering
JKU Focus areas
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
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