| 1. |
- Evestedt, Niclas, et al.
(författare)
-
Path tracking and stabilization for a reversing general 2-trailer configuration using a cascaded control approach
- 2016
-
Ingår i: Intelligent Vehicles Symposium (IV), 2016 IEEE. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509018215 - 9781509018222 ; , s. 1156-1161
-
Konferensbidrag (refereegranskat)abstract
- In this paper a cascaded approach for stabilizationand path tracking of a general 2-trailer vehicle configurationwith an off-axle hitching is presented. A low level LinearQuadratic controller is used for stabilization of the internalangles while a pure pursuit path tracking controller is used ona higher level to handle the path tracking. Piecewise linearityis the only requirement on the control reference which makesthe design of reference paths very general. A Graphical UserInterface is designed to make it easy for a user to design controlreferences for complex manoeuvres given some representationof the surroundings. The approach is demonstrated with challengingpath following scenarios both in simulation and on asmall scale test platform.
|
|
| 2. |
- Habibovic, Azra, et al.
(författare)
-
Evaluating interactions with non-existing automated vehicles: three Wizard of Oz approaches
- 2016
-
Ingår i: 2016 IEEE Intelligent Vehicles Symposium (IV). - Piscataway, NJ : IEEE. - 9781509018215 - 9781509018222 ; , s. 32-37
-
Konferensbidrag (refereegranskat)abstract
- Highly automated test vehicles are rare today, and (independent) researchers have often limited access to them. Also, developing fully functioning system prototypes is time and effort consuming. In this paper, we present three adaptions of the Wizard of Oz technique as a means of gathering data about interactions with highly automated vehicles in early development phases. Two of them address interactions between drivers and highly automated vehicles, while the third one is adapted to address interactions between pedestrians and highly automated vehicles. The focus is on the experimental methodology adaptations and our lessons learned.
|
|
| 3. |
- Öfjäll, Kristoffer, 1985-, et al.
(författare)
-
Visual Autonomous Road Following by Symbiotic Online Learning
- 2016
-
Ingår i: Intelligent Vehicles Symposium (IV), 2016 IEEE. - 9781509018215 - 9781509018222 ; , s. 136-143
-
Konferensbidrag (refereegranskat)abstract
- Recent years have shown great progress in driving assistance systems, approaching autonomous driving step by step. Many approaches rely on lane markers however, which limits the system to larger paved roads and poses problems during winter. In this work we explore an alternative approach to visual road following based on online learning. The system learns the current visual appearance of the road while the vehicle is operated by a human. When driving onto a new type of road, the human driver will drive for a minute while the system learns. After training, the human driver can let go of the controls. The present work proposes a novel approach to online perception-action learning for the specific problem of road following, which makes interchangeably use of supervised learning (by demonstration), instantaneous reinforcement learning, and unsupervised learning (self-reinforcement learning). The proposed method, symbiotic online learning of associations and regression (SOLAR), extends previous work on qHebb-learning in three ways: priors are introduced to enforce mode selection and to drive learning towards particular goals, the qHebb-learning methods is complemented with a reinforcement variant, and a self-assessment method based on predictive coding is proposed. The SOLAR algorithm is compared to qHebb-learning and deep learning for the task of road following, implemented on a model RC-car. The system demonstrates an ability to learn to follow paved and gravel roads outdoors. Further, the system is evaluated in a controlled indoor environment which provides quantifiable results. The experiments show that the SOLAR algorithm results in autonomous capabilities that go beyond those of existing methods with respect to speed, accuracy, and functionality.
|
|
| 4. |
- Biedermann, Daniel, et al.
(författare)
-
Evaluating visual ADAS components on the COnGRATS dataset
- 2016
-
Ingår i: 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV). - : IEEE. - 9781509018215 ; , s. 986-991
-
Konferensbidrag (refereegranskat)abstract
- We present a framework that supports the development and evaluation of vision algorithms in the context of driver assistance applications and traffic surveillance. This framework allows the creation of highly realistic image sequences featuring traffic scenarios. The sequences are created with a realistic state of the art vehicle physics model; different kinds of environments are featured, thus providing a wide range of testing scenarios. Due to the physically-based rendering technique and variable camera models employed for the image rendering process, we can simulate different sensor setups and provide appropriate and fully accurate ground truth data.
|
|
| 5. |
- Costache, Stefania, et al.
(författare)
-
Understanding the data-processing challenges in Intelligent Vehicular Systems
- 2016
-
Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. - 9781509018215 ; 2016-August, s. 611-618
-
Konferensbidrag (refereegranskat)abstract
- Vehicular sensors able to perceive and measure the environment, ranging from in-vehicle sensors to speed cameras, are revolutionizing how technology can interact with our daily lives, enabling Intelligent Vehicular Systems (IVSs). These sensors generate large volumes of data which can reveal useful information for enhancing the sustainable development (through improved utilization of resources), as well as the safety and functionality of the system.
|
|
| 6. |
- Fanani, Nolang, et al.
(författare)
-
Keypoint Trajectory Estimation Using Propagation Based Tracking
- 2016
-
Ingår i: 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV). - : IEEE. - 9781509018215 ; , s. 933-939
-
Konferensbidrag (refereegranskat)abstract
- One of the major steps in visual environment perception for automotive applications is to track keypoints and to subsequently estimate egomotion and environment structure from the trajectories of these keypoints. This paper presents a propagation based tracking method to obtain the 2D trajectories of keypoints from a sequence of images in a monocular camera setup. Instead of relying on the classical RANSAC to obtain accurate keypoint correspondences, we steer the search for keypoint matches by means of propagating the estimated 3D position of the keypoint into the next frame and verifying the photometric consistency. In this process, we continuously predict, estimate and refine the frame-to-frame relative pose which induces the epipolar relation. Experiments on the KITTI dataset as well as on the synthetic COnGRATS dataset show promising results on the estimated courses and accurate keypoint trajectories.
|
|
| 7. |
- Fu, Keren, 1988, et al.
(författare)
-
Geodesic Distance Transform-based Salient Region Segmentation for Automatic Traffic Sign Recognition
- 2016
-
Ingår i: Proceedings - 2016 IEEE Intelligent Vehicles Symposium, IV 2016, Gotenburg, Sweden, 19-22 June 2016. - 9781509018215 ; 2016-August, s. 948-953
-
Konferensbidrag (refereegranskat)abstract
- Visual-based traffic sign recognition (TSR) requiresfirst detecting and then classifying signs from capturedimages. In such a cascade system, classification accuracy is often affected by the detection results. This paper proposes a method for extracting a salient region of traffic sign within a detection window for more accurate sign representation and feature extraction, hence enhancing the performance of classification. In the proposed method, a superpixel-based distance map is firstly generated by applying a signed geodesic distance transform from a set of selected foreground and background seeds. An effective method for obtaining a final segmentation from the distancemap is then proposed by incorporating the shape constraints of signs. Using these two steps, our method is able to automatically extract salient sign regions of different shapes. The proposed method is tested and validated in a complete TSR system. Test results show that the proposed method has led to a high classification accuracy (97.11%) on a large dataset containing street images. Comparing to the same TSR system without using saliency-segmented regions, the proposed method has yielded a marked performance improvement (about 12.84%). Future work will be on extending to more traffic sign categories and comparing with other benchmark methods.
|
|
| 8. |
- Johansson, Rolf, et al.
(författare)
-
The need for an environment perception block to address all ASIL levels simultaneously
- 2016
-
Ingår i: 2016 IEEE Intelligent Vehicles Symposium (IV). - 9781509018215 ; , s. 1-4
-
Konferensbidrag (refereegranskat)abstract
- In order to perform safety assessment of vehicles for highly automated driving, it is critical that the vehicle can be proven to adapt its driving according to the sensed objects that might become a hinder. There is a complicated relation between the confidence of what hinders that might exist coming out of an environment perception block, and the tactical decisions about the driving style done by the autonomous vehicle. A good strategy that enables safety assessment according to ISO26262 implies that the environment perception block should address its safety requirements for all the ASIL attribute values simultaneously. In this paper we argue why every functional safety requirement allocated to an environment perception block should preferable be instantiated four times, each with a different ASIL value.
|
|
| 9. |
- Liao, Yuan, 1991, et al.
(författare)
-
Detection of driver cognitive distraction: An SVM based real-time algorithm and its comparison study in typical driving scenarios
- 2016
-
Ingår i: IEEE Intelligent Vehicles Symposium, Proceedings. 2016 IEEE Intelligent Vehicles Symposium, IV 2016; Gotenburg; Sweden; 19-22 June 2016. - 9781509018215 ; 2016-August:Art no 7535416, s. 394-399
-
Konferensbidrag (refereegranskat)abstract
- Detection of driver cognitive distraction is critical for active safety systems of road vehicles. Compared with visual distraction, cognitive distraction is more challenging for detection due to the lack of apparent exterior features. This paper presents a novel real-time detection algorithm for driver cognitive distraction by using support vector machine (SVM). Data are collected from 26 subjects, driving in typical urban and highway scenarios in a simulator. The chosen urban scenario is the stop-controlled intersection and the highway scenario is the speed-limited highway. Driver cognitive distraction while driving is induced by clock tasks which compete with the main driving tasks for visuospatial short working memory. For each subject, distracted driving instances and the equal number of non-distracted driving instances were collected (24 for urban scenario and 20 for highway scenario in total). Features concerning both driving performance and eye movement are used for training and validation. The proposed algorithm have correct rate of 93.0% and 98.5% for highway and urban scenarios respectively. Results also show that driver distraction can be recognized 6.5 s to 9.0 s after its happening, indicating good performance of the detection algorithm.
|
|
| 10. |
- Lindfors, Martin, 1990-, et al.
(författare)
-
Vehicle Speed Tracking Using Chassis Vibrations
- 2016
-
Ingår i: Proceedings of the 2016 IEEE Intelligent Vehicles Symposium (IV). - : IEEE conference proceedings. - 9781509018215 ; , s. 214-219
-
Konferensbidrag (refereegranskat)abstract
- The speed of a wheeled vehicle is usually estimatedusing wheel speed sensors (WSS) or GPS. If these signals are unavailable, other methods must be used. We propose a novelapproach exploiting the fact that vibrations from rotating axles,with fundamental frequency proportional to vehicle speed, aretransmitted via the vehicle chassis. Using an accelerometer, these vibrations can be tracked to estimate vehicle speed whileother sources of vibrations act as disturbances. A state-space model for the dynamics of the harmonics is presented andformulated such that there is a conditional linear-Gaussiansubstructure, enabling efficient Rao-Blackwellized methods. Avariant of the Rao-Blackwellized point-mass filter is derived, significantly reducing computational complexity, and reducingthe memory requirements from quadratic to linear in thenumber of grid points. It is applied to experimental data from the sensor cluster of a car and validated using therotational frequency from WSS data. The proposed methodshows improved performance and robustness in comparisonto a Rao-Blackwellized particle filter implementation and afrequency spectrum maximization method.
|
|
