Aude Stresser
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Aude Stresser has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Abdessamad El Krine
Cerema ENDSUM Research Team (Evaluation Non Destructive des StrUctures et des Matériaux), 11 Rue Jean Mentelin, 67035 Strasbourg, France
1 shared publication - Christophe Heinkele
Cerema ENDSUM Research Team (Evaluation Non Destructive des StrUctures et des Matériaux), 11 Rue Jean Mentelin, 67035 Strasbourg, France
1 shared publication - Joffrey Girard
Cerema EL Research Team (Eclairage et Lumière), 23 Avenue Amiral Chauvin, 49130 Les Ponts-de-Cé, France
1 shared publication - Maxime Redondin
CORE Center by COLAS, Data Science Digital Road Inspection and Material, 4 rue Jean Mermoz, F-78114 Magny-Les-Hameaux, France
1 shared publication - Valérie Muzet
Cerema, ENDSUM, F-67035, Strasbourg, France
1 shared publication
Latest Publications
- Open Access
Does the Condition of the Road Markings Have a Direct Impact on the Performance of Machine Vision during the Day on Dry Roads?
The forthcoming arrival of automated vehicles (AV) on the roads requires the re-evaluation or even adaptation of existing infrastructures as they are currently designed on the basis of human perception. Indeed, advanced driver-assistance systems (ADAS) do not necessarily have the same needs as drivers to detect road markings. One of the main challenges related to AV is the optimisation of the vehicle–infrastructure pair in order to guarantee the safety of all users. In this context, we compared the performance of a vehicle equipped with an ADAS machine-vision system with a dynamic retroreflectometer during the daytime on a road section. Our results questioned the reliability of the literature thresholds of the luminance contrast ratio on a dry road under sunny conditions. Despite the presence of old and worn road markings, the ADAS camera was able to detect the edge lines in more than 90% of the cases. The non-detections were not related to the poor condition of the markings but to the environmental conditions or the complexity of the infrastructure.
Open AccessDoes the Condition of the Road Markings Have a Direct Impact on the Performance of Machine Vision during the Day on Dry Roads?
The forthcoming arrival of automated vehicles (AV) on the roads requires the re-evaluation or even adaptation of existing infrastructures as they are currently designed on the basis of human perception. Indeed, advanced driver-assistance systems (ADAS) do not necessarily have the same needs as drivers to detect road markings. One of the main challenges related to AV is the optimisation of the vehicle–infrastructure pair in order to guarantee the safety of all users. In this context, we compared the performance of a vehicle equipped with an ADAS machine-vision system with a dynamic retroreflectometer during the daytime on a road section. Our results questioned the reliability of the literature thresholds of the luminance contrast ratio on a dry road under sunny conditions. Despite the presence of old and worn road markings, the ADAS camera was able to detect the edge lines in more than 90% of the cases. The non-detections were not related to the poor condition of the markings but to the environmental conditions or the complexity of the infrastructure.