| 1. |
- Bengtsson, Mats, et al.
(författare)
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Developing and Implementing a Program Interfacing Project Course in Electrical Engineering
- 2012
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Konferensbidrag (refereegranskat)abstract
- In this paper, we describe the ideas behind a second-year Design-Build course in Electrical Engineering. Electrical Engineering is a theoretical subject, and in such it is difficult to maintain the theoretical level in project courses introduced too early in the program, especially when core subjects like electromagnetic field theory are involved. This issue is addressed and we also describe our approach for the assessment of the students. We also discuss the different goals that were set up prior to the course from a program perspective; how we reasoned when designing the course, the assessment structure, and the output once the course was implemented
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| 2. |
- Bossér, Daniel, et al.
(författare)
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A Statistically Motivated Likelihood for Track-Before-Detect
- 2022
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Ingår i: 2022 IEEE INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS (MFI). - : IEEE. - 9781665460262 - 9781665460279
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Konferensbidrag (refereegranskat)abstract
- A theoretically sound likelihood function for passive sonar surveillance using a hydrophone array is presented. The likelihood is derived from first order principles along with the assumption that the source signal can be approximated as white Gaussian noise within the considered frequency band. The resulting likelihood is a nonlinear function of the delay-and-sum beamformer response and signal-to-noise ratio (SNR). Evaluation of the proposed likelihood function is done by using it in a Bernoulli filter based track-before-detect (TkBD) framework. As a reference, the same TkBD framework, but with another beamforming response based likelihood, is used. Results from Monte-Carlo simulations of two bearings-only tracking scenarios are presented. The results show that the TkBD framework with the proposed likelihood yields an approx. 10 seconds faster target detection for a target at an SNR of -27 dB, and a lower bearing tracking error. Compared to a classical detect-and-track target tracker, the TkBD framework with the proposed likelihood yields 4 dB to 5 dB detection gain.
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| 3. |
- Bossér, Daniel, et al.
(författare)
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A Statistically Motivated Likelihood for Track-Before-Detect
- 2022
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Ingår i: 2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI). - : IEEE. - 9781665460279 - 9781665460262
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Konferensbidrag (refereegranskat)abstract
- A theoretically sound likelihood function for passive sonar surveillance using a hydrophone array is presented. The likelihood is derived from first order principles along with the assumption that the source signal can be approximated as white Gaussian noise within the considered frequency band. The resulting likelihood is a nonlinear function of the delay-and-sum beamformer response and signal-to-noise ratio (SNR).Evaluation of the proposed likelihood function is done by using it in a Bernoulli filter based track-before-detect (TkBD) framework. As a reference, the same TkBD framework, but with another beamforming response based likelihood, is used. Results from Monte-Carlo simulations of two bearings-only tracking scenarios are presented. The results show that the TkBD framework with the proposed likelihood yields an approx. 10 seconds faster target detection for a target at an SNR of -27 dB, and a lower bearing tracking error. Compared to a classical detect-and-track target tracker, the TkBD framework with the proposed likelihood yields 4 dB to 5 dB detection gain.
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| 4. |
- Bossér, Daniel, et al.
(författare)
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Underwater Environment Modeling for Passive Sonar Track-Before-Detect
- 2023
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Ingår i: OCEANS 2023 - LIMERICK. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350332278 - 9798350332261
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Konferensbidrag (refereegranskat)abstract
- Underwater surveillance using passive sonar and track-before-detect technology requires accurate models of the tracked signal and the background noise. However, in an underwater environment, the signal channel is time-varying and prior knowledge about the spatial distribution of the background noise is unavailable. In this paper, an autoregressive model that captures a time-varying signal level caused by multi-path propagation is presented. In addition, a multi-source model is proposed to describe spatially distributed background noise. The models are used in a Bernoulli filter track-before-detect framework and evaluated using both simulated and sea trial data. The simulations demonstrate clear improvements in terms of target loss and improved ability to discern the target from the noisy background. An evaluation of the track-before-detect algorithm on the sea trial data indicates a performance gain when incorporating the proposed models in underwater surveillance and tracking problems.
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| 5. |
- Carlsson, Håkan, et al.
(författare)
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Inertial Navigation Using an Inertial Sensor Array
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We present a comprehensive framework for fusing measurements from multiple and generally placed accelerometers and gyroscopes to perform inertial navigation. Using the angular acceleration provided by the accelerometer array, we show that the numerical integration of the orientation can be done with second-order accuracy, which is more accurate compared to the traditional first-order accuracy that can be achieved when only using the gyroscopes. Since orientation errors are the most significant error source in inertial navigation, improving the orientation estimation reduces the overall navigation error. The practical performance benefit depends on prior knowledge of the inertial sensor array, and therefore we present four different state-space models using different underlying assumptions regarding the orientation modeling. The models are evaluated using a Lie Group Extended Kalman filter through simulations and real-world experiments. We also show how individual accelerometer biases are unobservable and can be replaced by a six-dimensional bias term whose dimension is fixed and independent of the number of accelerometers.
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| 6. |
- Carlsson, Håkan, et al.
(författare)
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On-The-Fly Geometric Calibration of Inertial Sensor Arrays
- 2017
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Ingår i: Proceedings 2017 international conference on indoor positioning and indoor navigation (IPIN). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- We present a maximum likelihood estimator for estimating the positions of accelerometers in an inertial sensor array. This method simultaneously estimates the positions of the accelerometers and the motion dynamics of the inertial sensor array and, therefore, does not require a predefined motion sequence nor any external equipment. Using an iterative block coordinate descent optimization strategy, the calibration problem can be solved with a complexity that is linear in the number of time samples. The proposed method is evaluated by Monte-Carlo simulations of an inertial sensor array built out of 32 inertial measurement units. The simulation results show that, if the array experiences sufficient dynamics, the position error is inversely proportional to the number of time samples used in the calibration sequence. Further, results show that for the considered array geometry and motion dynamics in the order of 2000 degrees/s and 2000 degrees/s(2), the positions of the accelerometers can be estimated with an accuracy in the order of 10(-6) m using only 1000 time samples. This enables fast on-the-fly calibration of the geometric errors in an inertial sensor array by simply twisting it by hand for a few seconds.
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| 7. |
- Carlsson, Håkan, et al.
(författare)
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Quantifying the Uncertainty of the Relative Geometry in Inertial Sensors Arrays
- 2021
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Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 21:17, s. 19362-19373
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Tidskriftsartikel (refereegranskat)abstract
- We present an algorithm to estimate and quantify the uncertainty of the accelerometers' relative geometry in an inertial sensor array. We formulate the calibration problem as a Bayesian estimation problem and propose an algorithm that samples the accelerometer positions' posterior distribution using Markov chain Monte Carlo. By identifying linear substructures of the measurement model, the unknown linear motion parameters are analytically marginalized, and the remaining non-linear motion parameters are numerically marginalized. The numerical marginalization occurs in a low dimensional space where the gyroscopes give information about the motion. This combination of information from gyroscopes and analytical marginalization allows the user to make no assumptions of the motion before the calibration. It thus enables the user to estimate the accelerometer positions' relative geometry by simply exposing the array to arbitrary twisting motion. We show that the calibration algorithm gives good results on both simulated and experimental data, despite sampling a high dimensional space.
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| 8. |
- Carlsson, Håkan, et al.
(författare)
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Self-Calibration of Inertial Sensor Arrays
- 2021
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Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 21:6, s. 8451-8463
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Tidskriftsartikel (refereegranskat)abstract
- A maximum likelihood estimator is presented for self-calibrating both accelerometers and gyroscopes in an inertial sensor array, including scale factors, misalignments, biases, and sensor positions. By simultaneous estimation of the calibration parameters and the motion dynamics of the array, external equipment is not required for the method. A computational efficient iterative optimization method is proposed where the calibration problem is divided into smaller subproblems. Further, an identifiability analysis of the calibration problem is presented. The analysis shows that it is sufficient to know the magnitude of the local gravity vector and the average scale factor gain of the gyroscopes, and that the array is exposed to two types of motions for the calibration problem to be well defined. The proposed estimator is evaluated by real-world experiments and by Monte Carlo simulations. The results show that the parameters can be consistently estimated and that the calibration significantly improves the accuracy of the motion estimation. This enables on-the-fly calibration of small inertial sensors arrays by simply twisting them by hand.
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| 9. |
- Das, Sandipan
(författare)
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State estimation with auto-calibrated sensor setup
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Localization and mapping is one of the key aspects of driving autonomously in unstructured environments. Often such vehicles are equipped with multiple sensor modalities to create a 360o sensing coverage and add redundancy to handle sensor dropout scenarios. As the vehicles operate in underground mining and dense urban environments the Global navigation satellite system (GNSS) is often unreliable. Hence, to create a robust localization system different sensor modalities like camera, lidar and IMU are used along with a GNSS solution. The system must handle sensor dropouts and work in real-time (~15 Hz), so that there is enough computation budget left for other tasks like planning and control. Additionally, precise localization is also needed to map the environment, which may be later used for re-localization of the autonomous vehicles as well. Finally, for all of these to work seamlessly, accurate calibration of the sensors is of utmost importance.In this PhD thesis, first, a robust system for state estimation that fuses measurements from multiple lidars and inertial sensors with GNSS data is presented. State estimation was performed in real-time, which produced robust motion estimates in a global frame by fusing lidar and IMU signals with GNSS components using a factor graph framework. The proposed method handled signal loss with a novel synchronization and fusion mechanism. To validate the approach extensive tests were carried out on data collected using Scania test vehicles (5 sequences for a total of ~ 7 Km). An average improvement of 61% in relative translation and 42% rotational error compared to a state-of-the-art estimator fusing a single lidar/inertial sensor pair is reported. Since precise calibration is needed for the localization and mapping tasks, in this thesis, methods for real-time calibration of the sensor setup is proposed. First, a method is proposed to calibrate sensors with non-overlapping field-of-view. The calibration quality is verified by mapping known features in the environment. Nevertheless, the verification process was not real-time and no observability analysis was performed which could give us an indicator of the analytical traceability of the trajectory required for motion-based online calibration. Hence, a new method is proposed where calibration and verification were performed in real-time by matching estimated sensor poses in real-time with observability analysis. Both of these methods relied on estimating the sensor poses using the state estimator developed in our earlier works. However, state estimators have inherent drifts and they are computationally intensive as well. Thus, another novel method is developed where the sensors could be calibrated in real-time without the need for any state estimation.
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| 10. |
- De Angelis, Alessio, et al.
(författare)
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Indoor positioning by ultra wide band radio aided inertial navigation
- 2009
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Ingår i: 19th IMEKO World Congress 2009. - 9781615675937 ; , s. 450-455
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Konferensbidrag (refereegranskat)abstract
- In this paper, a research activity aimed at developing an indoor positioning system is presented. The realized system prototype uses sensor fusion techniques to combine information from two sources: a local Ultra-Wideband (UWB) radio based distance-measuring system infrastructure and an Inertial Navigation System (INS). The UWB system provides a measure of distance between two transceivers by measuring the time-of-flight of pulses. Its principle of operation is briefly described, together with the main features of its architecture. Furthermore, the main characteristics of the INS and of the Extended Kalman Filter information fusion approach are presented. Finally, some experimental results are provided, relative to static and dynamic position measurements.
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| 11. |
- De Angelis, Alessio, et al.
(författare)
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Indoor positioning by ultra wide band radio aided inertial navigation
- 2010
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Ingår i: Metrology and Measurement Systems. - : Polish Academy of Sciences Chancellery. - 0860-8229. ; 17:3, s. 447-460
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Tidskriftsartikel (refereegranskat)abstract
- A research study aimed at developing a novel indoor positioning system is presented. The realized system prototype uses sensor fusion techniques to combine information from two sources: an in-house developed local Ultra-Wideband (UWB) radio-based ranging system and an inertial navigation system (INS). The UWB system measures the distance between two transceivers by recording the round-trip-time (RTT) of UWB radio pulses. Its principle of operation is briefly described, together with the main design features. Furthermore, the main characteristics of the INS and of the Extended Kalman Filter information fusion approach are presented. Finally, selected static and dynamic test scenario experimental results are provided. In particular, the advantages of the proposed information fusion approach are further investigated by means of a high dynamic test scenario.
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| 12. |
- De Angelis, Alessio, et al.
(författare)
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UWB Ranging Hardware Platform
- 2010
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Ingår i: GigaHertz Symposium. - Lund, Sweden.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 13. |
- Eek, Jacob, et al.
(författare)
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A Novel and Fast Approach for Reconstructing CASSI-Raman Spectra using Generative Adversarial Networks
- 2022
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Ingår i: 2022 ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA). - : IEEE. - 9781665469647 - 9781665469654
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Konferensbidrag (refereegranskat)abstract
- Raman spectroscopy in conjunction with a Coded Aperture Snapshot Spectral Imaging (CASSI) system allows for detection of small amounts of explosives from stand-off distances. The obtained Compressed Sensing (CS) measurements from CASSI consists of mixed spatial and spectral information, from which a HyperSpectral Image (HSI) can be reconstructed. The HSI contains Raman spectra for all spatial locations in the scene, revealing the existence of substances. In this paper we present the possibility of utilizing a learned prior in the form of a conditional generative model for HSI reconstruction using CS. A Generative Adversarial Network (GAN) is trained using simulated samples of HSI, and conditioning on their respective CASSI measurements to refine the prior. Two different types of simulated HSI were investigated, where spatial overlap of substances was either allowed or disallowed. The results show that the developed method produces precise reconstructions of HSI from their CASSI measurements in a matter of seconds.
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| 14. |
- Gupta, Amit K., et al.
(författare)
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Long-term Performance Evaluation of a Foot-mounted Pedestrian Navigation Device
- 2015
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Ingår i: 2015 ANNUAL IEEE INDIA CONFERENCE (INDICON). - 9781467365406
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present a long term experimental study performed on a foot mounted pedestrian navigation device, the Osmium MIMU22BTP, which is based on the OpenShoe platform. The aim of the study is to investigate the performance that can be expected in mass market applications. Accordingly, we investigate the error characteristics over a large number of tracking devices and their alternative mounting schemes, over several wearers, and over different walking scenarios. By a massive data collection corresponding to more than 150 km of elapsed walking distance over almost 1,000 independent tests, the law of large numbers provides us with illustrative rule-of-thumbs for the tracking performance in realistic use cases. We observe no outlier performance and relative errors less than 4% in 95% of the test-cases, indicating its potential for a variety of indoor Location Based Services (LBS) and IoT applications based on foot-mounted inertial sensing and dead reckoning. The experimental findings are validated with long distance walks.
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| 15. |
- Hari, K.V.S., et al.
(författare)
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A prototype of a first-responder indoor localization system
- 2013
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Ingår i: Journal of the Indian Institute of Science. - 0970-4140. ; 93:3, s. 511-520
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Forskningsöversikt (refereegranskat)abstract
- In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.
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| 16. |
- Huang, Chuan, 1996-, et al.
(författare)
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A Tightly-Integrated Magnetic-Field aided Inertial Navigation System
- 2022
-
Ingår i: 2022 25th International Conference on Information Fusion (FUSION). - : IEEE. - 9781737749721 - 9781665489416
-
Konferensbidrag (refereegranskat)abstract
- A tightly integrated magnetic-field aided inertial navigation system is presented. The system uses a magnetometer sensor array to measure spatial variations in the local magnetic-field. The variations in the field are - via a recursively updated polynomial magnetic-field model - mapped into displacement and orientation changes of the array, which in turn are used to aid the inertial navigation system. Simulation results show that the resulting navigation system has three orders of magnitude lower position error at the end of a 40 seconds trajectory as compared to a standalone inertial navigation system. Thus, the proposed navigation solution has the potential to solve one of the key challenges faced with current magnetic-field simultaneous localization and mapping (SLAM) systems - the very limited allowable length of the exploration phase during which unvisited areas are mapped.
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| 17. |
- Huang, Chuan, et al.
(författare)
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MAINS : A Magnetic-Field-Aided Inertial Navigation System for Indoor Positioning
- 2024
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Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 24:9, s. 15156-15166
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Tidskriftsartikel (refereegranskat)abstract
- A magnetic-field-aided inertial navigation system (MAINS) for indoor navigation is proposed in this article. MAINS leverages an array of magnetometers to measure spatial variations in the magnetic field, which are then used to estimate the displacement and orientation changes of the system, thereby aiding the inertial navigation system (INS). Experiments show that MAINS significantly outperforms the stand-alone INS, demonstrating the remarkable two orders of magnitude reduction in position error. Furthermore, when compared with the state-of-the-art magnetic-field-aided navigation approach, the proposed method exhibits slightly improved horizontal position accuracy. On the other hand, it has noticeably larger vertical error on datasets with large magnetic-field variations. However, one of the main advantages of MAINS compared with the state of the art is that it enables flexible sensor configurations. The experimental results show that the position error after 2 min of navigation in most cases is less than 3 m when using an array of 30 magnetometers. Thus, the proposed navigation solution has the potential to solve one of the key challenges faced with current magnetic-field simultaneous localization and mapping (SLAM) solutions-the very limited allowable length of the exploration phase during which unvisited areas are mapped.
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| 18. |
- Huang, Chuan, 1996-, et al.
(författare)
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MAINS: A Magnetic-Field-Aided Inertial Navigation System for Indoor Positioning
- 2024
-
Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 24:9, s. 15156-15166
-
Tidskriftsartikel (refereegranskat)abstract
- A Magnetic-field-Aided Inertial Navigation System (MAINS) for indoor navigation is proposed in this paper. MAINS leverages an array of magnetometers to measure spatial variations in the magnetic field, which are then used to estimate the displacement and orientation changes of the system, thereby aiding the inertial navigation system (INS). Experiments show that MAINS significantly outperforms the stand-alone INS, demonstrating a remarkable two orders of magnitude reduction in position error. Furthermore, when compared to the state-of-the-art magnetic-field-aided navigation approach, the proposed method exhibits slightly improved horizontal position accuracy. On the other hand, it has noticeably larger vertical error on datasets with large magnetic field variations. However, one of the main advantages of MAINS compared to the state-of-the-art is that it enables flexible sensor configurations. The experimental results show that the position error after 2 minutes of navigation in most cases is less than 3 meters when using an array of 30 magnetometers. Thus, the proposed navigation solution has the potential to solve one of the key challenges faced with current magnetic-field simultaneous localization and mapping (SLAM) solutions — the very limited allowable length of the exploration phase during which unvisited areas are mapped.
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| 19. |
- Huang, Chuan, 1996-
(författare)
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On Indoor Localization Using Magnetic Field-Aided Inertial Navigation Systems
- 2024
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Localization and navigation technologies have become integral to modern society, playing crucial roles in daily life. They enable efficient and safe travel, allow emergency services to reach and assist individuals quickly, and are indispensable components of autonomous systems. Indoor localization technology, aimed at enabling precise location determination in indoor environments, has garnered significant research interest. One intriguing research direction is magnetic field-based localization technology, which exploits spatial variations in indoor magnetic fields to provide position information.This thesis investigates how indoor magnetic fields can be used for localization and develops a magnetic field-aided localization system that does not rely on any preinstalled infrastructures, such as electric coils, or external localization information. To achieve this, a sensor platform consisting of a planar magnetometer array and an inertial measurement unit (IMU) was built. The array captures the spatial variations of the magnetic field, from which odometry information can be inferred. This odometry information is then used to aid an inertial navigation system (INS) constructed around the IMU on the array.The thesis addresses three key challenges faced when realizing a magnetic field-based INS using the developed sensor platform. The first challenge is the calibration of the sensors to ensure their measurements are accurate enough for the localization system. The second challenge is to create a magnetic field model that can be used to realize a magnetic field-aided INS. The final challenge is to design a state estimation algorithm that provides consistent estimates so that the perceived uncertainties match the true estimation errors as closely as possible.To address the first challenge, an easy-to-use and efficient calibration method is proposed to correct the misalignment of the IMU’s and magnetometer’s sensitivity axes, sensor biases, and scale factors. The second challenge is met by proposing a polynomial magnetic field model to construct a local small-scale magnetic field map and a tightly integrated magnetic field-aided INS. The proposed system was evaluated on simulation and real-world datasets, demonstrating a significant reduction in position drift compared to a stand-alone INS and showing performance comparable to state-of-the-art magnetic field odometry. Additionally, the system offers flexibility in sensor configurations, including sensor placement and the number of sensors involved. Finally, an observability-constrained magnetic field-aided INS is proposed to address the inconsistencies identified in the developed magnetic field-aided INS. This new system maintains the yaw angle unobservable, and demonstrates improved performance and consistency compared to the initial system.The results show that the proposed magnetic field-aided INS can be realized by low-cost sensors and appropriate signal-processing algorithms. It could be integrated into magnetic field simultaneous localization and mapping (SLAM) systems to extend their exploration phase. Most importantly, it showcases the possibility of building self-contained, accurate, and consistent indoor localization systems with magnetic fields.
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| 20. |
- Händel, Peter, et al.
(författare)
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Anordning för att bestämma identitet hos ett motorfordon
- 2012
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Patent (populärvet., debatt m.m.)abstract
- A device (100) for determining an identity of a vehicle comprises a connector (110) configured to be connected to the cigarette lighter outlet (230) of the vehicle (200). The device further comprises measuring equipment (310; 320; 330) configured to provide an electric signal (400) related to the engine speed of the vehicle, such that oscillations in the electric signal have a frequency proportional to the engine speed of the vehicle. The device is configured to allow determination of an identity of the vehicle based on the electric signal, such that the identity is independent of variations in the engine speed of the vehicle. The device also comprises a memory (340) configured to store the electric signal, and/or the identity of the vehicle.
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| 21. |
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| 22. |
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| 23. |
- Händel, Peter, et al.
(författare)
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Determination of activity rate of portable electronic equipment
- 2012
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Patent (populärvet., debatt m.m.)abstract
- A method for obtaining activity rate of a portable electronic device (250) during travel with a vehicle (200) comprises determining (S100) a calculated driving distance based on the portable electronic device utilizing a sequence of measured positions for the portable electronic device. The method further comprises determining (S200) a read driving distance by reading of odometer indication (270) of the vehicle. The method also comprises calculating (S300) an activity rate by comparison of the calculated driving distance with the read driving distance. The method further comprises calculating (S400) a flag which indicates the validity of the calculated activity rate, where the flag is calculated based on the sequence of measured positions for the portable electronic device. The method also comprises transferring (S500) an information packet (280) to a central server (290), where the information packet comprises the activity rate, and/or the read driving distance, and/or the flag.
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| 24. |
- Händel, Peter, 1962-, et al.
(författare)
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Far infrared camera platform and experiments for moose early warning systems
- 2009
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Ingår i: Transactions of Society of Automotive Engineers of Japan. - Tokyo : Society of Automotive Engineers of Japan. - 0287-8321. ; 40:4, s. 1095-1099
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Tidskriftsartikel (refereegranskat)abstract
- Encounters between big game, such as the moose, and private cars often result in severe injuries and death. A vehicle-based moose detection early warning system is a technical countermeasure to increase the traffic safety by alerting the driver in case of danger. Based on available off-the-shelf consumer electronics, a infrared night vision system was built to serve as a platform for experiments with moose early warning driver assistance systems. Aspects of a moose thermal replica employing a horse are discussed and typical vehicle-moose movements are directed and recorded to form a publicly available database for research and education.
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| 25. |
- Händel, Peter, et al.
(författare)
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Insurance telematics : Opportunities and challenges with the smartphone solution
- 2014
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - 1524-9050 .- 1558-0016. ; 6:4, s. 57-70
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Tidskriftsartikel (refereegranskat)abstract
- Smartphone-based insurance telematics or usage based insurance is a disruptive technology which relies on insurance premiums that reflect the risk profile of the driver; measured via smartphones with appropriate installed software. A survey of smartphone-based insurance telematics is presented, including definitions; Figure-of-Merits (FoMs), describing the behavior of the driver and the characteristics of the trip; and risk profiling of the driver based on different sets of FoMs. The data quality provided by the smartphone is characterized in terms of Accuracy, Integrity, Availability, and Continuity of Service. The quality of the smartphone data is further compared with the quality of data from traditional in-car mounted devices for insurance telematics, revealing the obstacles that have to be combated for a successful smartphone-based installation, which are the poor integrity and low availability. Simply speaking, the reliability is lacking considering the smartphone measurements. Integrity enhancement of smartphone data is illustrated by both second-by-second lowlevel signal processing to combat outliers and perform integrity monitoring, and by trip-based map-matching for robustification of the recorded trip data. A plurality of FoMs are described, analyzed and categorized, including events and properties like harsh braking, speeding, and location. The categorization of the FoMs in terms of Observability, Stationarity, Driver influence, and Actuarial relevance are tools for robust risk profiling of the driver and the trip. Proper driver feedback is briefly discussed, and rule-of-thumbs for feedback design are included. The work is supported by experimental validation, statistical analysis, and experiences from a recent insurance telematics pilot run in Sweden.
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