Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance
In this review, we assess the real-world effectiveness of ADAS! (ADAS!) in preventing vehicle crashes. We propose a new, data-driven framework of safety performance based on dimensions urgency and level of control as an alternative to existing taxonomies.We identified 28 ADAS! and collected data on...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Transportation Research Interdisciplinary Perspectives |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590198225000156 |
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| author | Ksander N de Winkel Michiel Christoph |
| author_facet | Ksander N de Winkel Michiel Christoph |
| author_sort | Ksander N de Winkel |
| collection | DOAJ |
| description | In this review, we assess the real-world effectiveness of ADAS! (ADAS!) in preventing vehicle crashes. We propose a new, data-driven framework of safety performance based on dimensions urgency and level of control as an alternative to existing taxonomies.We identified 28 ADAS! and collected data on (real-world) safety performance of from grey (technical reports) and white (scientific) literature. ADAS! were categorized by functional class (longitudinal/lateral control, monitoring, information systems) and by interaction type (informing, warning, intervening, comfort-enhancing).The data analysis showed that LKA! (LKA!) (−19.1%) and DMS! (DMS!) (−14%) had the strongest crash rate reduction effects, followed by AEB! (AEB!) (−10.7%). However, systems like ACC! (ACC!) and CC! (CC!) were associated with increased crash rates (+8%, +12%). Categorizing systems by either functional class or interaction type revealed central tendencies favoring safety of longitudinal control and intervening systems, while comfort-enhancing systems showed detrimental effects.From the categorizations, we derived dimensions urgency and level of control, scoring individual ADAS! accordingly. A linear model based on these dimensions (pseudo-R2=0.103) explained a similar amount of variance as the categorizations (functional class: 0.140, interaction type: 0.087). The analysis indicated that low urgency and high level of control, typical of comfort-enhancing systems, did not improve safety.Our findings support the positive safety effects of ADAS!, but also point to risks, particularly for comfort-enhancing technologies. The proposed framework offers an explanation for the observations. It is simple and generalizable, and avoids disadvantages inherent to categorical classifications, making it a potentially valuable tool for designers and policymakers. |
| format | Article |
| id | doaj-art-20548a789e1c459eaecee4043a1fae8a |
| institution | Kabale University |
| issn | 2590-1982 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Research Interdisciplinary Perspectives |
| spelling | doaj-art-20548a789e1c459eaecee4043a1fae8a2025-02-09T05:01:20ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822025-01-0129101336Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performanceKsander N de Winkel0Michiel Christoph1Corresponding author.; SWOV institute for road safety research, Henri Faasdreef 312, The Hague, 2492JP, The NetherlandsSWOV institute for road safety research, Henri Faasdreef 312, The Hague, 2492JP, The NetherlandsIn this review, we assess the real-world effectiveness of ADAS! (ADAS!) in preventing vehicle crashes. We propose a new, data-driven framework of safety performance based on dimensions urgency and level of control as an alternative to existing taxonomies.We identified 28 ADAS! and collected data on (real-world) safety performance of from grey (technical reports) and white (scientific) literature. ADAS! were categorized by functional class (longitudinal/lateral control, monitoring, information systems) and by interaction type (informing, warning, intervening, comfort-enhancing).The data analysis showed that LKA! (LKA!) (−19.1%) and DMS! (DMS!) (−14%) had the strongest crash rate reduction effects, followed by AEB! (AEB!) (−10.7%). However, systems like ACC! (ACC!) and CC! (CC!) were associated with increased crash rates (+8%, +12%). Categorizing systems by either functional class or interaction type revealed central tendencies favoring safety of longitudinal control and intervening systems, while comfort-enhancing systems showed detrimental effects.From the categorizations, we derived dimensions urgency and level of control, scoring individual ADAS! accordingly. A linear model based on these dimensions (pseudo-R2=0.103) explained a similar amount of variance as the categorizations (functional class: 0.140, interaction type: 0.087). The analysis indicated that low urgency and high level of control, typical of comfort-enhancing systems, did not improve safety.Our findings support the positive safety effects of ADAS!, but also point to risks, particularly for comfort-enhancing technologies. The proposed framework offers an explanation for the observations. It is simple and generalizable, and avoids disadvantages inherent to categorical classifications, making it a potentially valuable tool for designers and policymakers.http://www.sciencedirect.com/science/article/pii/S2590198225000156ADASAdvanced Driver Assistant SystemsSafetyRiskEffectivenessReal-world |
| spellingShingle | Ksander N de Winkel Michiel Christoph Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance Transportation Research Interdisciplinary Perspectives ADAS Advanced Driver Assistant Systems Safety Risk Effectiveness Real-world |
| title | Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance |
| title_full | Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance |
| title_fullStr | Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance |
| title_full_unstemmed | Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance |
| title_short | Rethinking Advanced Driver Assistance System taxonomies: A framework and inventory of real-world safety performance |
| title_sort | rethinking advanced driver assistance system taxonomies a framework and inventory of real world safety performance |
| topic | ADAS Advanced Driver Assistant Systems Safety Risk Effectiveness Real-world |
| url | http://www.sciencedirect.com/science/article/pii/S2590198225000156 |
| work_keys_str_mv | AT ksanderndewinkel rethinkingadvanceddriverassistancesystemtaxonomiesaframeworkandinventoryofrealworldsafetyperformance AT michielchristoph rethinkingadvanceddriverassistancesystemtaxonomiesaframeworkandinventoryofrealworldsafetyperformance |