Intelligent Vehicle Systems:Applications and New Trends

Gusikhin, Oleg; Filev, Dimitar; Rychtyckyj, Nestor

doi:10.1007/978-3-540-79142-3_1

Cited by 27 publications

(15 citation statements)

References 25 publications

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“…Seven video sequences V [1][2][3][4][5][6][7] have been used to evaluate the algorithm performances (V 1-3 are from pedestrian detection sequences in Ref. [8] and V [4][5][6][7] have been used in Refs.…”

Section: Trackers and Datasetmentioning

confidence: 99%

“…During the 1990s, many autonomous driving projects have been supported by government, such as the National Automated Highway Systems Consortium (NAHSC) project in U.S., the Assist Highway Systems Research Association (AHSRA) project in Japan, the PROMETHEUS project in Germany and the La Route Automatisée (LARA) project in France [3]. The early autonomous driving was designed for low-speed freeway scenarios and has the function of lane changes, obstacle avoidance and close-headway platooning [4]. These applications usually need the help of supported infrastructures (such as magnetic markers or dedicated lanes).…”

Section: Introductionmentioning

confidence: 99%

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Review on Kernel based Target Tracking for Autonomous Driving

Wang

Yue

Dong

et al. 2016

Journal of Information Processing

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Significant progress has been made in the field of autonomous driving during the past decades. However, fully autonomous driving in urban traffic is still extremely difficult in the near future. Visual tracking of vehicles or pedestrians is an essential part of autonomous driving. Among these tracking methods, kernel-based object tracking is an effective means of tracking in video sequences. This paper reviews the kernel theory adopted in target tracking of autonomous driving and makes a qualitative and quantitative comparison among several well-known kernel based methods. The theoretical and experimental analysis allow us to conclude that the kernel based online subspace learning algorithm achieves a good trade-off between the stability and real-time processing for target tracking in the practical application environments of autonomous driving. This paper reports on the result of evaluating the performances of five algorithms by using seven video sequences.

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Section: Trackers and Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Review on Kernel based Target Tracking for Autonomous Driving

Wang

Yue

Dong

et al. 2016

Journal of Information Processing

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show abstract

“…According to Gusikhin et al 2008, a vehicle can be defined as intelligent if it is able to sense its own status and that of the environment, to communicate with the environment and to plan and execute appropriate maneuvers. The first application of intelligent vehicle systems has been the increase of safety by providing driver assistance in critical moments.…”

Section: Intelligent Vehicle Technologiesmentioning

confidence: 99%

Intelligent Usage of Internal Combustion Engines in Hybrid Electric Vehicles

Donateo¹

2012

Internal Combustion Engines

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“…The incorporation of affective and non-verbal about the emotional expressions of others [12], a technology that may improve the quality of life for those with autism or other disorders that impair human-human communication [13]. Existing devices that are in close contact with the user may also have potential to be used as affect sensing devices, for example a mouse may sense the user's stress levels [14], or a car steering wheel may sense when the user is falling asleep or identify lapses in attention [15].…”

Section: Introductionmentioning

confidence: 99%

Affective Stack — A Model for Affective Computing Application Development

Thompson

McGill²

2015

JSW

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Affective computing applications hold promise to revolutionize human-computer interaction by enabling more natural and intuitive interaction modalities. These may include the communication of vocal expressions, physiological signals or other non-verbal indicators of underlying affective state. Although the field has experienced substantial expansion in recent years, the tools and techniques utilized are not yet mature or well established. A notable issue is the one-off nature of currently implemented affective computing systems. There is as yet no notion of standardized program architecture and there is no straightforward way to extend the functionality of existing software to include affective components. This paper introduces a new model which describes the affective computing application in terms of a set of loosely coupled functional components. This model encourages a uniform and replicable approach to affective application development in which functional components can be improved independently and subsequently re-used. The model also incorporates existing third party software as a functional component highlighting the potential to build upon existing, well established, software packages. It is hoped that this model and discussion spurs further, focused development in this growing field.

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Intelligent Vehicle Systems:Applications and New Trends

Cited by 27 publications

References 25 publications

Review on Kernel based Target Tracking for Autonomous Driving

Review on Kernel based Target Tracking for Autonomous Driving

Intelligent Usage of Internal Combustion Engines in Hybrid Electric Vehicles

Affective Stack — A Model for Affective Computing Application Development

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