Estimating Vehicle Movement Direction from Smartphone Accelerometers Using Deep Neural Networks

Characterization of driving maneuvers or driving styles through motion sensors has become a field of great interest. Before now, this characterization used to be carried out with signals coming from extra equipment installed inside the vehicle, such as On-Board Diagnostic (OBD) devices or sensors in pedals. Nowadays, with the evolution and scope of smartphones, these have become the devices for recording mobile signals in many driving characterization applications. Normally multiple available sensors are used, such as accelerometers, gyroscopes, magnetometers or the Global Positioning System (GPS). However, using sensors such as GPS increase significantly battery consumption and, additionally, many current phones do not include gyroscopes. Therefore, we propose the characterization of driving style through only the use of smartphone accelerometers. We propose a deep neural network (DNN) architecture that combines convolutional and recurrent networks to estimate the vehicle movement direction (VMD), which is the forward movement directional vector captured in a phone’s coordinates. Once VMD is obtained, multiple applications such as characterizing driving styles or detecting dangerous events can be developed. In the development of the proposed DNN architecture, two different methods are compared. The first one is based on the detection and classification of significant acceleration driving forces, while the second one relies on longitudinal and transversal signals derived from the raw accelerometers. The final success rate of VMD estimation for the best method is of 90.07%.

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Relationship Between Winter Road-Surface Conditions and Vehicular Motion: Measurements by Probe Vehicles Equipped with Global Positioning System

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1824-12 ◽

2003 ◽

Vol 1824 (1) ◽

pp. 106-114 ◽

Cited By ~ 3

Author(s):

Takashi Nakatsuji ◽

Akira Kawamura

Keyword(s):

Global Positioning System ◽

Field Experiments ◽

Wheel Speed ◽

Road Surface ◽

Positioning System ◽

Motion Sensors ◽

Slip Ratio ◽

Surface Conditions ◽

Probe Vehicles ◽

Global Positioning

A major concern of drivers in winter is the current road condition. Taxis, which move ceaselessly around a wide area, have great potential as sensors for detecting road-surface conditions in a given area. To establish a method with which to estimate road conditions based on the vehicular motion of taxis, field experiments were conducted by using probe vehicles fitted with vehicular-motion sensors and a Global Positioning System device, before implementation in taxis. Preliminary analyses were performed by using data measured on a test track, urban streets, and an expressway. The slip ratio, defined as the relative difference in speed between vehicle and tire wheel, was effective in indicating how slippery the road surfaces were. Taxi vehicular-motion data were collected for more than 1 month, although unlike with probe vehicles, the wheel speed was not measured. Some features of vehicular motion specific to slippery roads were identified, and the discriminability of road conditions, whether icy or dry, without the use of wheel-speed data, was examined.

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A new analytical method for the classification of time–location data obtained from the global positioning system (GPS)

Journal of Environmental Monitoring ◽

10.1039/c2em30190c ◽

2012 ◽

Vol 14 (8) ◽

pp. 2270 ◽

Cited By ~ 11

Author(s):

Taehyun Kim ◽

Kiyoung Lee ◽

Wonho Yang ◽

Seung Do Yu

Keyword(s):

Global Positioning System ◽

Analytical Method ◽

Positioning System ◽

Location Data ◽

Global Positioning

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Surge of Bering Glacier and Bagley Ice Field, Alaska: an update to August 1995 and an interpretation of brittle-deformation patterns

Journal of Glaciology ◽

10.1017/s0022143000035012 ◽

1997 ◽

Vol 43 (145) ◽

pp. 427-434 ◽

Cited By ~ 22

Author(s):

Ute Christina Herzfeld ◽

Helmut Mayer

Keyword(s):

Global Positioning System ◽

Brittle Deformation ◽

Location Data ◽

The Past ◽

Ice Surface ◽

Bering Glacier ◽

Global Positioning ◽

Ice Field ◽

Deformation Patterns

AbstractIn the summers of 1993, 1994 and 1995, video and Global Positioning System location data and 35 mm photographs were collected in a series of systematic survey flights undertaken over the Bering Glacier and Bagley Ice Field system (Alaska) in an effort to characterize surge-crevasse patterns and surge propagation. During survey flights in late August 1995, we observed that the 1993–94. Bering Glacier surge was continuing and still expanding affecting new areas farther up in Bagley Ice Field. New crevasse fields, similar in pattern to the first surge crevasses we had observed in June 1993 below Khitrov Hills and in other isolated areas of central Bering Glacier and in July 1994 near the head of Bering Glacier (near the junction of Bering Glacier and Bagley Ice Field, in both upper Bering Glacier and Bagley Ice Field), were opening in eastern Bagley Ice Field and in the “Stellet” side of Bagley Ice Field. The type of crevasses seen in the new fields suggested that the surge was propagating into these areas. By analysis and interpretation of the brittle-deformation patterns apparent in the crevasse patterns, some aspects of the past kinematic framework of the surge can be deduced. This approach may lead to a more general classification of ice-surface structures and to their linkage to ongoing processes.

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Slow slip events in the roots of the San Andreas fault

Science Advances ◽

10.1126/sciadv.aav3274 ◽

2019 ◽

Vol 5 (2) ◽

pp. eaav3274 ◽

Cited By ~ 14

Author(s):

Baptiste Rousset ◽

Roland Bürgmann ◽

Michel Campillo

Keyword(s):

Global Positioning System ◽

San Andreas Fault ◽

Slow Slip ◽

Slow Slip Events ◽

San Andreas ◽

Global Positioning ◽

The Moment ◽

Episodic Tremor ◽

Seismic Signature

Episodic tremor and accompanying slow slip are observed at the down-dip edge of subduction seismogenic zones. While tremors are the seismic signature of this phenomenon, they correspond to a small fraction of the moment released; thus, the associated fault slip can be quantified only by geodetic observations. On continental strike-slip faults, tremors have been observed in the roots of the Parkfield segment of the San Andreas fault. However, associated transient aseismic slip has never been detected. By making use of the timing of transient tremor activity and the dense Parkfield-area global positioning system network, we can detect deep slow slip events (SSEs) at 16-km depth on the Parkfield segment with an average moment equivalent toMw4.90 ± 0.08. Characterization of transient SSEs below the Parkfield locked asperity, at the transition with the creeping section of the San Andreas fault, provides new constraints on the seismic cycle in this region.

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Characterization of the Long-term Radiosonde Temperature Biases in the Lower Stratosphere using COSMIC and Metop-A/GRAS Data from 2006 to 2014

10.5194/acp-2016-801 ◽

2016 ◽

Author(s):

Shu-Peng Ho ◽

Liang Peng ◽

Holger Vömel

Keyword(s):

Global Positioning System ◽

Lower Stratosphere ◽

Temperature Measurements ◽

Global Trend ◽

Global Positioning ◽

The Mean ◽

Geographical Locations

Abstract. Radiosonde observations (RAOBs) have provided the only long-term global in situ temperature measurements in the troposphere and lower stratosphere since 1958. In this study, we use consistently reprocessed Global Positioning System (GPS) radio occultation (RO) temperature data derived from COSMIC and Metop-A/GRAS missions from 2006 to 2014 to characterize the inter-seasonal and inter-annual variability of temperature biases in the lower stratosphere for different sensor types. The results show that the RAOB temperature biases for different RAOB sensor types are mainly owing to i) uncorrected solar zenith angle dependent errors, and ii) change of radiation correction. The mean daytime temperature difference (ΔT) for Vaisala RS92 is equal to 0.18 K in Australia, 0.20 K in Germany, 0.10 K in Canada, 0.13 K in England, and 0.33 K in Brazil. The mean daytime ΔT is equal to −0.06 K for Sippican, 0.71 K for VIZ-B2, 0.66 K for AVK-MRZ, and 0.18 K for Shanghai. The daytime trend of anomalies for Vaisala RS92 and RO temperature at 50 hPa is equal to 0.00 K/5 yrs over United States, −0.02 K/5 yrs over Germany, 0.17 K/5 yrs over Australia, 0.23 K/5 yrs over Canada, 0.26 K/5 yrs over England, and 0.12 K/5 yrs over Brazil, respectively. Although there still exist uncertainties for Vaisala RS92 temperature measurements over different geographical locations, the global trend of temperature anomaly between Vaisala RS92 and RO from June 2006 to April 2014 is within +/−0.09 K/5 yrs globally. Comparing with Vaisala RS80, Vaisala RS90 and sondes from other manufacturers, the Vaisala RS92 seems to provide the best RAOB temperature measurements, which can potentially be used to construct long term temperature CDRs. Results from this study also demonstrate the feasibility to use RO data to correct RAOB temperature biases for different sensor types.

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Prototipo electrónico simple y de bajo costo para rastreo de vehículos basado en GPS

Revista de Ingenieria Innovativa ◽

10.35429/joie.2019.12.3.9.16 ◽

2019 ◽

pp. 9-16

Author(s):

Maricela Morales-Hernández ◽

Franco Gabriel Caballero-Julian ◽

Antonio Erick Wong-Díaz ◽

Gabriela Aguilar-Ortiz

Keyword(s):

Global Positioning System ◽

Short Message Service ◽

Short Message ◽

C Language ◽

Global Positioning ◽

Message Service ◽

Communication Module ◽

Complete Circuit ◽

Vehicle Movement

This article presents an electronic prototype for vehicle tracking based on GPS (Global Positioning System) location as a proposed solution to the problem of vehicle theft that affects the Oaxaca de Juarez municipality and its surrounding municipalities, according to statistics from the Office of the Prosecutor Specialized in High Impact Crimes, vehicle thefts have increased rapidly in recent years. The "V" diagram was used to make the prototype, which proposes a solution within reach of the owners of vehicles, since similar products require the device and the payment of a membership to follow up in real time. The prototype consists of an Arduino board, a GPS module, a communication module for sending SMS (Short Message Service) messages, an accelerometer to detect vehicle movements and other components that are required for the operation of the complete circuit. The program has been developed in C language for Arduino and a free application of GoogleMaps is being used to send the location of the vehicle when detecting any vehicle movement

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An Effective Approach to Improving Low-Cost GPS Positioning Accuracy in Real-Time Navigation

The Scientific World JOURNAL ◽

10.1155/2014/671494 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Md. Rashedul Islam ◽

Jong-Myon Kim

Keyword(s):

Real Time ◽

State Of The Art ◽

Low Cost ◽

Movement Direction ◽

Gps Receiver ◽

Positioning Accuracy ◽

Global Positioning ◽

Art Methods ◽

Coordinate Data ◽

Vehicle Movement

Positioning accuracy is a challenging issue for location-based applications using a low-cost global positioning system (GPS). This paper presents an effective approach to improving the positioning accuracy of a low-cost GPS receiver for real-time navigation. The proposed method precisely estimates position by combining vehicle movement direction, velocity averaging, and distance between waypoints using coordinate data (latitude, longitude, time, and velocity) of the GPS receiver. The previously estimated precious reference point, coordinate translation, and invalid data check also improve accuracy. In order to evaluate the performance of the proposed method, we conducted an experiment using a GARMIN GPS 19xHVS receiver attached to a car and used Google Maps to plot the processed data. The proposed method achieved improvement of 4–10 meters in several experiments. In addition, we compared the proposed approach with two other state-of-the-art methods: recursive averaging and ARMA interpolation. The experimental results show that the proposed approach outperforms other state-of-the-art methods in terms of positioning accuracy.

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