Integration of ADAS algorithm into an experimental vehicle

Lussereau, Jerome; Stein, Procópio; David, Jean-Alix; Rummelhard, Lukas; Nègre, Amaury; Laugier, Christian; Vignard, Nicolas; Othmezouri, Gabriel

doi:10.1109/arso.2015.7428202

Cited by 4 publications

(3 citation statements)

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“…2b and represent target points for map matching algorithm. A particle filter based lane tracker [19] is used, that takes camera image and camera's intrinsic and extrinsic parameters as input and provides road parameters i.e. road width, curvature of the road, vehicle's lateral displacement with respect to ego lane marking.…”

Section: B Lane-level Map Matchingmentioning

confidence: 99%

Vehicle Localization Based on Visual Lane Marking and Topological Map Matching

Asghar

Garzón

Lussereau

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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Accurate and reliable localization is crucial to autonomous vehicle navigation and driver assistance systems. This paper presents a novel approach for online vehicle localization in a digital map. Two distinct map matching algorithms are proposed: i) Iterative Closest Point (ICP) based lane level map matching is performed with visual lane tracker and grid map ii) decision-rule based approach is used to perform topological map matching. Results of both the map matching algorithms are fused together with GPS and dead reckoning using Extended Kalman Filter to estimate vehicle's pose relative to the map. The proposed approach has been validated on real life conditions on an equipped vehicle. Detailed analysis of the experimental results show improved localization using the two aforementioned map matching algorithms.

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Section: B Lane-level Map Matchingmentioning

confidence: 99%

Vehicle Localization Based on Visual Lane Marking and Topological Map Matching

Asghar

Garzón

Lussereau

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

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“…The subscriber-publisher model uses one-way communication based on the concept of topics, and the client-server model uses two-way communication with the concept of service. ROS is a widely used platform for robotics implementations such as on the ADAS [13], [35]. Another advantage of using ROS is that many active communities have already created modules and drivers [35].…”

Section: A Materialsmentioning

confidence: 99%

“…ROS is a widely used platform for robotics implementations such as on the ADAS [13], [35]. Another advantage of using ROS is that many active communities have already created modules and drivers [35].…”

Section: A Materialsmentioning

confidence: 99%

Implementation 2D Lidar and Camera for detection object and distance based on RoS

Mulyanto

Borman

Prasetyawan

et al. 2020

JOIV : Int. J. Inform. Visualization

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The advanced driver assistance systems (ADAS) are one of the issues to protecting people from vehicle collision. Collision warning system is a very important part of ADAS to protect people from the dangers of accidents caused by fatigue, drowsiness and other human errors. Multi-sensors has been widely used in ADAS for environment perception such as cameras, radar, and light detection and ranging (LiDAR). We propose the relative orientation and translation between the two sensors are things that must be considered in performing fusion. we discuss the real-time collision warning system using 2D LiDAR and Camera sensors for environment perception and estimate the distance (depth) and angle of obstacles. In this paper, we propose a fusion of two sensors that is camera and 2D LiDAR to get the distance and angle of an obstacle in front of the vehicle that implemented on Nvidia Jetson Nano using Robot Operating System (ROS). Hence, a calibration process between the camera and 2D LiDAR is required which will be presented in session III. After that, the integration and testing will be carried out using static and dynamic scenarios in the relevant environment. For fusion, we use the implementation of the conversion from degree to coordinate. Based on the experiment, we result obtained an average of 0.197 meters

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