Advisory speed for Intelligent Speed Adaptation in adverse conditions

In this paper, a novel approach to compute advisory speeds to be used in an adaptive Intelligent Speed Adaptation system (ISA) is proposed. This method is designed to be embedded in the vehicles. It estimates an appropriate speed by fusing in real-time the outputs of ego sensors which detect adverse conditions with roadway characteristics transmitted by distant servers. The method presents two major novelties. First, the 85 th percentile of observed speeds (V 85 ) is estimated along a road, this speed profile is considered as a reference speed practised and practicable in ideal conditions for a lonely vehicle. In adverse conditions, this reference speed is modulated in order to account for lowered friction and lowered visibility distance (top-down approach). Second, this method allows us taking into account the potential seriousness of crashes using a generic scenario of accident. Within this scenario, the difference in speed that should be applied in adverse conditions is estimated so that global injury risk is the same as in ideal conditions

A Three Resolution Framework for Reliable Road Obstacle Detection using Stereovision

International audienceMany approaches have been proposed for in-vehicle obstacle detection using stereovision. Unfortunately, computation cost is generally a limiting factor for all these methods, especially for systems using large base-lines, as they need to explore a wide range of disparities. Considering this point, we propose a reliable three resolution framework, designed for real time operation, even with high resolution images and a large baseline

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Background Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials. Methods We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality). Findings Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5–14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21·4% for NACT versus 15·9% for adjuvant chemotherapy (5·5% increase [95% CI 2·4–8·6]; rate ratio 1·37 [95% CI 1·17–1·61]; p=0·0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38·2% for NACT vs 38·0% for adjuvant chemotherapy; rate ratio 1·02 [95% CI 0·92–1·14]; p=0·66), breast cancer mortality (34·4% vs 33·7%; 1·06 [0·95–1·18]; p=0·31), or death from any cause (40·9% vs 41·2%; 1·04 [0·94–1·15]; p=0·45). Interpretation Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered—eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy

Assistance à la conduite en conditions atmosphériques dégradées par la prise en compte du risque routier

Thèse réalisée au sein des laboratoires LIVIC et LEPSiS de l'IFSTTAR entre septembre 2007 et septembre 2010.Adverse weather conditions such as rain or fog impair temporarily the driving conditions. On secondary roads, the numerous accidents that occur during these events exemplify a bad adaptation of the driving and specifically of the speed practised. We propose to estimate a reference speed along a path and to adapt speed in degraded conditions of visibility or friction. Our method of assessing roadway risk relies on the realisation of dynamic scenarios, extracted from accident studies, using a model of the interactions between vehicle, driver and infrastructure. We use static characteristics of the infrastructure and of its environment. We also use dynamic characteristics of the meteorological environment of the car estimated in real time. We show that the models used for friction and visibility estimation and we show that tools already exist allowing to estimate the necessary static inputs of the models. We then present the online methods used to detect degraded atmospheric conditions with embedded cameras. We detail an original method allowing night fog detection based on the detection of halos around light sources and on the backscattered veil of the car front lights. We finally present a static method based on the use of a camera intended to calibrate the system in real conditions of fog.Les conditions atmosphériques dégradées telles que la pluie et le brouillard altèrent temporairement les conditions de conduite. Sur le réseau secondaire, la sur-accidentologie observée dans ces conditions témoigne d'une mauvaise adaptation de la conduite et en particulier de la vitesse. Nous proposons une méthodologie permettant d'estimer une vitesse de référence le long d'un trajet ainsi qu'une méthode fondée sur l'étude du risque routier pour moduler la vitesse en conditions d'adhérence et de visibilité dégradées. Notre estimation du risque routier s'appuie sur la réalisation de scénarios, extraits de l'accidentologie, à l'aide d'un modèle d'interactions véhicule-infrastructure-conducteur. Nous prenons en compte des caractéristiques statiques propres à l'infrastructure et à son environnement et les conditions météorologiques estimées en temps réel dans l'environnement direct du véhicule. Nous montrons qu'il existe des outils permettant d'alimenter les modèles en caractéristiques statiques. Enfin, nous présentons les méthodes fondées sur l'utilisation d'une caméra embarquée permettant de détecter et de caractériser en ligne les conditions atmosphériques dégradées. Nous détaillons en particulier notre contribution au travers d'une méthode de détection et de caractérisation du brouillard de nuit. Celle-ci est constituée d'un système dual s'appuyant sur la détection des halos autour des sources de lumière et sur la détection du voile de rétrodiffusion des phares du véhicule. Nous proposons finalement une méthode statique par caméra permettant de calibrer le système en conditions écologiques

Static Estimation of Meteorological Visibility Distance in Night Fog with Imagery

In this paper, we propose a new way to estimate fog extinction at night using a classification of fog depending on the forward scattering. We show that a characterization of fog based on the atmospheric extinction parameter only is not sufficient. This method works in dense fogs (meteorological visibility distances < 400m) with a single image and three known light sources. The method is validated on synthetic images generated with a semi Monte-Carlo ray tracing software dedicated to fog simulation. We drove this study in simulated environment in order to help us designing a test site located outdoor