PUVAME - New French Approach for Vulnerable Road Users Safety

Aycard, Olivier; Spalanzani, Anne; Yguel, Manuel; Burlet, J.; Du, Nan; Fortelle, Arnaud de La; Fraichard, Thierry; Ghorayeb, Hicham; Kais, Mikael; Laugier, Christian; Laurgeau, Claude; Michel, Gilles; Raulo, David; Steux, Bruno

doi:10.1109/ivs.2006.1689596

Cited by 15 publications

(11 citation statements)

References 7 publications

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“…The term Pðx t jx tÀ1 ; u t Þ represents the motion model which is the probability that the vehicle is at location x t given that the vehicle was previously at positionx tÀ1 and executed an action u t . The resulting posex t is then used to generate a new map M t according to (6):…”

Section: Left)mentioning

confidence: 99%

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Grid-based localization and local mapping with moving object detection and tracking

Vu¹,

Burlet²,

Aycard³

2011

Information Fusion

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International audienceWe present a real-time algorithm for simultaneous localization and local mapping (local SLAM) with detection and tracking of moving objects (DATMO) in dynamic outdoor environments from a moving vehicle equipped with a laser scanner, short-range radars and odometry. To correct the vehicle odometry we introduce a new fast implementation of incremental scan matching method that can work reliably in dynamic outdoor environments. After obtaining a good vehicle localization, the map surrounding of the vehicle is updated incrementally and moving objects are detected without a priori knowledge of the targets. Detected moving objects are finally tracked by a Multiple Hypothesis Tracker (MHT) coupled with an adaptive Interacting Multiple Model (IMM) filter. The experimental results on datasets collected from different scenarios such as: urban streets, country roads and highways demonstrate the efficiency of the proposed algorithm

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Section: Left)mentioning

confidence: 99%

“…In this context, we designed and developed a generic perception architecture addressing these problems focusing on outdoor dynamic environments [6]. The architecture ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Grid-based localization and local mapping with moving object detection and tracking

Vu¹,

Burlet²,

Aycard³

2011

Information Fusion

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“…We're not working with occupancy grid as in [13], but we're dividing the scanning plan into these areas to solve the problem of the partially hidden objects.…”

Section: A Laser Scannermentioning

confidence: 99%

“…Vision system can analyze the area classified by the laser scanner data processor as occupied by an object to confirm its existence [14] and to recognize its type and dimensions. The data fusion can be at higher level; the vision system can run an object tracking algorithm [13], and the obtained tracks can be fused with the laser scanner trackers results.…”

Section: B Object Characteristicsmentioning

confidence: 99%

Tracking objects using a laser scanner in driving situation based on modeling target shape

Fayad

Cherfaoui

2007

2007 IEEE Intelligent Vehicles Symposium

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In this paper, we present a new approach to solve the problem of tracking partially hidden objects by a single layer laser scanner. Taking into consideration the shape of the detected object, we have optimized the clustering and the estimation of results. We propose to adapt the detection according to the predicted pose and the occlusions. We have developed an algorithm to detect the security barriers of the road in some conditions. Finally, we have projected our interpretation in the image of a vision system to provide the area of interest to be analyzed and fused with our results. This method is experimented using a single layer laser scanner of type SICK mounted on a vehicle and validated by the means of video data.

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“…The experimental setup used to evaluate our method is an evolution of the ParkView platform [17], initially developped for a French national project designed for the Interpretation of Complex Dynamic Scenes and Reactive Motion Planning.…”

Section: A Experimental Platformmentioning

confidence: 99%

Adaptive Interacting Multiple Models applied on pedestrian tracking in car parks

Burlet

Aycard

Spalanzani

et al. 2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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To address perception problems we must be able to track dynamics targets of the environment. An important issue of tracking is filtering problem in which estimates of the target's state are computed while observations are progressively received. This paper presents an adaptive Interacting Multiple Models (IMM) based filtering method. Interacting Multiple Models have been successfully applied to many applications as they allow, using several filters in parallel, to deal with the uncertainty on motion model, a critical component of filtering. Indeed targets can rapidly change their motion over a lapse of time. This is the case of pedestrians for which it is difficult to define an unique motion model which matches all their possible displacements. Nevertheless, the Transition Probability Matrix (TPM) which models the interaction between different filters in an IMM is in currently defined a priori or needs an important amount of tuning to be used efficiently.In this paper, we put forward a method which automatically adapts online the TPM. The TPM adaptation using on-line data significantly improves the effectiveness of IMM filtering and so better target estimates are obtained. To validate our work we applied our method to pedestrian tracking in car parks on a real platform.

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PUVAME - New French Approach for Vulnerable Road Users Safety

Cited by 15 publications

References 7 publications

Grid-based localization and local mapping with moving object detection and tracking

Grid-based localization and local mapping with moving object detection and tracking

Tracking objects using a laser scanner in driving situation based on modeling target shape

Adaptive Interacting Multiple Models applied on pedestrian tracking in car parks

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