Intelligent technologies of Honda ASV

Kamiya, Hiroyuki; Fujita, Y; Tsuruga, T; Nakamura, Y.; Matsuda, S.; Enomoto, Koji

doi:10.1109/ivs.1996.566384

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…Left weakly more important than top 5 Left moderately more important than top 7 Left strongly more important than top 9 Left absolutely more important than top 2,4,6,8 Between the above-mentioned two adjacent judgments L1, L2, L3, L4 and L5 is supposed to represent five criteria layers in Fig.4 respectively, namely the basic behavior of vehicles, the basic driving behavior, the basic traffic behavior, number of manual intervention and intervention extent, and completion time of task. According to the definition of importance, the mutual importance relationships among these five criteria layers can be gained.…”

Section: B Weight Distribution Of Evaluation Factorsmentioning

confidence: 99%

“…Department of Transportation in USA held the test on AHS project of automatic driving vehicle in 1997 [6]. During this period, Japan was also carried out major projects including ASV, SSVS and ARTS, which involved the research and evaluation of autonomous vehicles [7,8,9]. With the development of single technology and integrated systems, the test and assessment methods are developed from single-item tests to complex integrated ability test, and the third-party test appears gradually.…”

Section: Introductionmentioning

confidence: 99%

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Research on the quantitative evaluation system for unmanned ground vehicles

Xiong

Zhao

Liu

et al. 2010

2010 IEEE Intelligent Vehicles Symposium

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The first Chinese unmanned ground vehicles competition -The 2009 Future Challenge: Intelligent Vehicles and Beyond (FC'09) pushed China's unmanned vehicles out of laboratories and into application environments. In order to further promote the development of unmanned vehicle technologies, the test and evaluation system for unmanned vehicles needs to be studied. The design method of test environment is proposed in accordance with the definition and classification of test environment elements. Based on the multi-platform and multi-sensor, an omnidirectional video monitoring test system of unmanned vehicles is built. The fuzzy comprehensive evaluation method combined with AHP (analytic hierarchy process) is applied to the comprehensive evaluation of unmanned vehicles. The evaluation examples of unmanned vehicles show that the proposed evaluation system can quantitatively evaluate the overall technical performance and individual technical performance of unmanned vehicles.

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Section: B Weight Distribution Of Evaluation Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on the quantitative evaluation system for unmanned ground vehicles

Xiong

Zhao

Liu

et al. 2010

2010 IEEE Intelligent Vehicles Symposium

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show abstract

“…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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“…The Suzuki advanced safety vehicle (ASV) system [6] can generate a warning signal by using a buzzer or showing it on the screen to alert the driver when the relative distance between the ego-car and other target vehicle reaches a low limit. Honda ASV [7] has a device to switch on the emergency brake system when the relative distance between the ego-car and neighbouring vehicle detected by laser radar is less than a threshold value. The Honda ASV2 [8] can provide a stop and go adaptive cruising control system.…”

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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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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Intelligent technologies of Honda ASV

Cited by 6 publications

References 3 publications

Research on the quantitative evaluation system for unmanned ground vehicles

Research on the quantitative evaluation system for unmanned ground vehicles

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

A new lateral impact warning system with grey prediction

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