Development of Nissan's ASV

Sugasawa, Fukashi; Ueno, Hiroshi; Kaneda, Masayuki; Koreishi, Jun; Shirato, Ryouta; Fukuhara, Nobuhiko

doi:10.1109/ivs.1996.566387

Cited by 5 publications

(5 citation statements)

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“…The second term of the first-order grey model, equation (10), can be defined as the average of y 1 (k + 1) and y 1 (k). Then, the first-order differential equation can be described as…”

Section: Grey Prediction Theorymentioning

confidence: 99%

“…The Mitsubishi Company has also developed an automatic collision avoidance system by using a multiradar system to detect obstacles and then, based on the measured data, actuating a warning buzzer in dangerous situations, even starting the vehicle automatic avoidance action. The Nissan ASV system [10] has emergency brake announcement, adaptive cruising control, and blockade warning functions. The Mazda ASV system [11] is designed to prevent pedestrian and cross-road vehicle collisions.…”

Section: Introductionmentioning

confidence: 99%

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A new lateral impact warning system with grey prediction

Huang

Chao

2009

Proceedings of the Institution of Mechanical Engineers, Part D:

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Vehicle lateral impact is one of the major traffic collision accidents. Usually, this collision accident is caused when the target vehicle appears in the driver's blind spot during lane change or crowded urban travelling and the driver has not carefully observed the approaching vehicle from the rear and side mirrors. Hence, additional sensors need to be installed to measure the relative distance between two closing vehicles for active collision warning purpose. Generally, the lateral distance between two neighbouring vehicles is small compared with longitudinal distance: for crowded city traffic it is less than 1.5m. It is difficult to estimate accurately or assess the time-to-collision (TTC) based on a single relative distance index between two cars. Here, a novel two-indices TTC decision algorithm is proposed, which can distinguish the safe passing of neighbouring lanes from the essential dangerous lateral collision situation. In addition, the grey prediction theory is introduced to estimate the relative distance of two approaching vehicles one step ahead for TTC estimation to gain additional driver reaction time. The simulation results show that this strategy can create 0.5s extra time for the driver to take collision avoidance action.

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“…The second term of the first-order grey model, equation (10), can be defined as the average of y 1 (k + 1) and y 1 (k). Then, the first-order differential equation can be described as…”

Section: Grey Prediction Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new lateral impact warning system with grey prediction

Huang

Chao

2009

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Driver vigilance monitoring systems continuously monitor the driver's performance for possible signs of conditions that may endanger the driver, such as drowsiness as a consequence of fatigue (Sugasawa et al 1996), alcohol abuse, medication, etc., or lack of attention, e.g. due to stress (Grace 1999.…”

Section: Driver Monitoringmentioning

confidence: 99%

“…Obstacle and pedestrian detection systems oVer similar services by warning the driver when pedestrians, vehicles, or obstacles are in close proximity to the driver's intended path (Butsuen et al 1996, Kamiya et al 1996, Sugasawa et al 1996, Papageorgiou et al 1998. Information from on-board sensors or infrastructurebased sensors is used to detect obstacles and pedestrians and speed and direction information from the on-board computer is used to estimate the vehicle's path.…”

Section: Collision Avoidancementioning

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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“…In Japan, the advanced safety vehicle (ASV) program [9]- [11] started in 1991. Its fourth phase, i.e., Nissan ASV-4, was presented in October 2007.…”

mentioning

confidence: 99%

Cooperative Maneuvering in Close Environments Among Cybercars and Dual-Mode Cars

Milanés¹,

Alonso²,

Bouraoui³

et al. 2011

IEEE Trans. Intell. Transport. Syst.

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Development of Nissan's ASV

Cited by 5 publications

References 0 publications

A new lateral impact warning system with grey prediction

A new lateral impact warning system with grey prediction

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

Cooperative Maneuvering in Close Environments Among Cybercars and Dual-Mode Cars

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