Autonomous vehicle based in cooperative GPS and inertial systems

Milanés, Vicente; Naranjo, José Eugenio; González, Carlos; Alonso, Javier; Pedro, Teresa de

doi:10.1017/s0263574708004232

Cited by 100 publications

(62 citation statements)

References 9 publications

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“…This might be further improved by fusing vision data with GPS data (e.g., [21]), or combining the GPS with other features which are measured by the car [22], [23].…”

Section: Monitoring the Position Of A Vehiclementioning

confidence: 99%

Lane Determination With GPS Precise Point Positioning

Knoop

Bakker

Tiberius

et al. 2017

IEEE Trans. Intell. Transport. Syst.

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Abstract-Modern Intelligent Transport Solutions can achieve improvement of traffic flow on motorways. With lane-specific measurements and lane-specific control more measures are possible. Single Frequency Precise Point Positioning (PPP) is a newly developed and affordable technique to achieve an improved position accuracy compared to Global Positioning System (GPS) standalone positioning. GPS-PPP allows for sub-meter accurate positioning, in real time, of vehicles on a motorway. This paper tests this technique in real life; moreover, it presents a methodology to map the lanes on a motorway using data collected by this technique. The methodology exploits the high accuracy and the fact that most driving is within a lane. In a field test, a GPS-PPP equipped vehicle drives a specific motorway stretch 100 times, for which the GPS-PPP trajectory data are collected. Using these data the positions and the widths of different lanes are successfully estimated. Comparison with the ground truth shows a dm accuracy. With the parametrized lanes, vehicles can be tracked down to a lane with the GPS-PPP device.

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“…This might be further improved by fusing vision data with GPS data (e.g., [21]), or combining the GPS with other features which are measured by the car [22], [23].…”

Section: Monitoring the Position Of A Vehiclementioning

confidence: 99%

Lane Determination With GPS Precise Point Positioning

Knoop

Bakker

Tiberius

et al. 2017

IEEE Trans. Intell. Transport. Syst.

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“…The vehicle is equipped with a differential global positioning system (DGPS) and an inertial measurement unit (IMU) that are used for the vehicle's guidance (Milanés, Naranjo, González, Alonso, & Pedro, 2008). The stereo vision system located in the rear-view mirror ( Fig.…”

Section: Control Architecturementioning

confidence: 99%

Vision-based active safety system for automatic stopping

Milanés

Llorca

Villagrá

et al. 2012

Expert Systems with Applications

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Intelligent systems designed to reduce highway fatalities have been widely applied in the automotive sector in the last decade. Of all users of transport systems, pedestrians are the most vulnerable in crashes as they are unprotected. This paper deals with an autonomous intelligent emergency system designed to avoid collisions with pedestrians. The system consists of a fuzzy controller based on the time-to-collision estimate -obtained via a vision-based system -and the wheel-locking probability -obtained via the vehicle's CAN bus -that generates a safe braking action. The system has been tested in a real car -a convertible Citroen C3 Pluriel -equipped with an automated electro-hydraulic braking system capable of working in parallel with the vehicle's original braking circuit. The system is used as a last resort in the case that an unexpected pedestrian is in the lane and all the warnings have failed to produce a response from the driver.

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“…In order to overcome the multipath interference when the GPS signal is reflected by external agent, Milanes et al proposed a dynamic integration system using a decision unit, which can choose the correct one from GPS and INS (46) . Godha et al employed constraints to describe the behavior of a typical land vehicle in the GPS/INS integrated system, when a GPS outage occurred in urban areas (47) .…”

Section: Inertial Navigation System (Ins)mentioning

confidence: 99%

Autonomous Vehicle Technologies :Localization and Mapping

俊介

艶磊

立達

2015

Fundamentals Review

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Vehicle self-localization is an important and challenging issue in current driving assistance and autonomous driving research activities. This paper mainly investigates two kinds of methods for vehicle self-localization: active sensor based and passive sensor based. Active sensor based localization was firstly proposed for robot localization, and was introduced into autonomous driving recently. The Simultaneous Localization and Mapping (SLAM) techniques is the representative in active sensor based localization. The passive sensor based localization technologies are categorized and explained based on the type of sensors, Global Navigation Satellite System (GNSS), inertial sensors and cameras. In this paper, researches utilizing active sensors and passive sensors for autonomous vehicles are reviewed extensively. Finally, our challenges on self-localization in urban canyon by the system integration of passive sensors is introduced. GNSS error has been improved for the purpose of the self-localization in urban canyon. The performance of the proposed method would suggest possible solution autonomous vehicles which makes use of passive sensors more.

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Autonomous vehicle based in cooperative GPS and inertial systems

Cited by 100 publications

References 9 publications

Lane Determination With GPS Precise Point Positioning

Lane Determination With GPS Precise Point Positioning

Vision-based active safety system for automatic stopping

Autonomous Vehicle Technologies :Localization and Mapping

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