Accurate vehicle positioning in urban areas

In this paper, a low-cost navigation system with high integrity and reliability is proposed for enhancing highway traffic safety in adverse weather situations, such as a foggy or rainy weather. A high-integrity, IS-state, estimation filter is proposed to obtain a high accuracy state estimate. The filter utilizes a vehicle velocity constraint measurement to enhance the accuracy of the estimate. Two estimations filters, the Kalman filter (KF) and the information filter (IF), are designed and compared to obtain the estimate of the vehicle state. An instrumentation system that consists of a microcontroller, a GPS receiver, an IMU, encoders, and a Zig bee transceiver is constructed. The microcontroller provides a vehicle navigation solution at 50 Hz by fusing the measurements of the IMU, the GPS receiver and the digital compass using the proposed filter design. Experimental tests, using the proposed system, are conducted and the obtained results are presented. These results are processed with and without the velocity constraints. The estimation accuracy improvement with the addition of the velocity constraints is demonstrated. Also, results of a static test are used to assess the accuracy of the low-cost navigation systems against a commercial solution.

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“…The quaternions are updated as follows. (9) where q e is an estimated quaternion and q e is a quaternion obtained from a measured value.…”

Section: B Velocity and Positionmentioning

confidence: 99%

Low-cost, high-accuracy, state estimation for vehicle collision prevention system

Saadeddin

Abdel–Hafez

Jarrah

2012

2012 8th International Symposium on Mechatronics and Its Applications

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“…So, for each road segment in the cache, a Mahalanobis distance ∆ j seg is computed between segment-j and the estimated pose [9]. It is given by:…”

Section: B Road Selectionmentioning

confidence: 99%

Enhancement of global vehicle localization using navigable road maps and dead-reckoning

Fouque

Bonnifait

Betaille³

2008

2008 IEEE/ION Position, Location and Navigation Symposium

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Abstract-This paper presents a data fusion strategy for the global localization of car-like vehicles. The system uses raw GNSS measurements, dead-reckoning sensors and road map data. We present a new method to use the map information as a heading observation in a Kalman filter. Experimental results show the benefit of such a method when the GPS information is not available. Then, we propose a conservative localization strategy that relies mainly on dead-reckoned navigation. The GNSS measurements and the map information are not used when consistency tests are doubtful. Experimental tests indicate that the performance is effectively better when using only the available consistent information.

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“…For road vehicles, geographic information can be used as well. Much research has been done with standard maps [4], [5], but precise digital surface models [6] and lane-level maps [7] are now available to provide strong positional constraints. Fusion of GPS measurements with geographical information for map-aided positioning has been an active area of research, either by using the map to correct raw GPS measurements, like in the Road Reduction Filter [8], or by adding a constraint stage after the update of a Kalman filter, like the two-step projection method proposed in [9].…”

Section: Introductionmentioning

confidence: 99%

iGPS: Global Positioning in Urban Canyons with Road Surface Maps

Drevelle

Bonnifait

2012

IEEE Intell. Transport. Syst. Mag.

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Interval Global Positioning with road Surface (iGPS) is a new method to obtain a robust and continuous positioning in urban areas by tightly-coupling precise 3-D drivable area maps with GPS pseudorange measurements. Map and GPS measurements are represented by geometric constraints, thus turning the localization problem into a constraint satisfaction problem whose solution is the confidence domain of position. Interval analysis is employed to solve the problem by using contractions and bisections of a prior position box. If more than 3 satellites are visible, the method is robust to erroneous pseudorange measurements. The system is also able to compute multiple position hypotheses where there are ambiguities. An experimental validation using real GPS pseudorange measurements and a precise 3-D map is reported to illustrate the performance of the method with real data in an urban area, and with reduced satellite visibility. Confidence domains are consistent with the ground truth throughout the 1 km trial, and a 6.5 m 95% accuracy is achieved with at least two satellites in view.

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Accurate vehicle positioning in urban areas

Cited by 14 publications

References 7 publications

Low-cost, high-accuracy, state estimation for vehicle collision prevention system

Low-cost, high-accuracy, state estimation for vehicle collision prevention system

Enhancement of global vehicle localization using navigable road maps and dead-reckoning

iGPS: Global Positioning in Urban Canyons with Road Surface Maps

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