Integration Between Anticollision And AICC Functions The ALERT Project

Carrea, P; Saroldi, Andrea

doi:10.1109/ivs.1993.697309

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…obstacles detection [26] or lane recognition [25]. Consequently, it has been used for adjusting the power of headlights [3], [28] or for adjusting the headway in Automatic Cruise Control (ACC) [5] according to the prevailing meteorological conditions. However, it has been shown that the dynamic adaptation of the emitting power of a LIDAR with respect to visibility conditions is not always perfect [7].…”

Section: ) Lidarmentioning

confidence: 99%

Simultaneous Contrast Restoration and Obstacles Detection: First Results

Hautiére¹,

Tarel²,

Didier³

2007

2007 IEEE Intelligent Vehicles Symposium

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Abstract-Reliable obstacles detection under adverse weather conditions, especially foggy conditions, is a challenging task because the contrast is drastically reduced. Consequently, the classical approaches relying on pattern recognition techniques or points of interest matching are not so efficient anymore. In this paper, a novel approach is proposed which is able to simultaneously restore the contrast of the scene and to detect the presence of obstacles by stereovision once the atmosphere opacity is known. The different computation stages are detailed: fog density estimation, contrast enhancement, local distortions detection and obstacles detection, as well as their combination. The method is illustrated and partially assessed thanks to a video sequence under foggy weather. Finally, future research directions are indicated.

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Section: ) Lidarmentioning

confidence: 99%

Simultaneous Contrast Restoration and Obstacles Detection: First Results

Hautiére¹,

Tarel²,

Didier³

2007

2007 IEEE Intelligent Vehicles Symposium

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“…the preceding vehicle has stopped, and start again when the conditions allow it (Carrea 1993). Such systems could oVer signi®cant safety bene®ts in hazardous situations and in situations where frequent stop-and-go is required, such as congested conditions.…”

Section: General Vehicle Controlmentioning

confidence: 99%

Classification of driver-assistance systems according to their impact on road safety and traffic efficiency

Golias¹,

Yannis²,

Antoniou³

2002

Transport Reviews

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The aim was to examine driver-assistance systems that seem to have a considerable potential for road safety and tra c e ciency improvement, and to propose an impact-oriented classi®cation of these systems. A broad overview of a series of driver-assistance systems under development or in some cases already available is presented and it identi®es the basic characteristics of each system and its expected impact on tra c e ciency and road safety. The latter is assessed on the basis of appropriate evaluation criteria. Expert judgement and literature evidence available are used in this context. This impact approach, in contrast with the usually adopted user or system-oriented approaches, allows for more appropriate identi®cation of the priorities in the ®eld of future research, development and promotion of driver-assistance systems. The proposed classi®cation allocates the driver-assistance systems in four diVerent categories on the basis of whether tra c e ciency and safety impact are high or low. This categorization reveals that 40% of the systems considered are expected to have a high safety and low tra c-e ciency impact, while only 15% is expected to have both impacts high.

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ProLab2: A driving assistance system

Rombaut¹

1995

Mathematical and Computer Modelling

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Integration Between Anticollision And AICC Functions The ALERT Project

Cited by 5 publications

References 2 publications

Simultaneous Contrast Restoration and Obstacles Detection: First Results

Simultaneous Contrast Restoration and Obstacles Detection: First Results

Classification of driver-assistance systems according to their impact on road safety and traffic efficiency

ProLab2: A driving assistance system

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