Transit Vehicles as Traffic Probe Sensors

2002 ◽  
Vol 1804 (1) ◽  
pp. 23-30 ◽  
Author(s):  
F. W. Cathey ◽  
D. J. Dailey
Keyword(s):  
Tracking System ◽  
Sensor Data ◽  
Vehicle Speed ◽  
Virtual Sensors ◽  
Location Data ◽  
Estimate Travel Time ◽  
Vehicle Position ◽  
Speed Function ◽  
Probe Sensor ◽  
New Algorithms

New algorithms are presented that use transit vehicles as probes for determining traffic speeds and travel times along freeways and other primary arterials. A mass transit tracking system based on automatic vehicle location data and a Kalman filter used to estimate vehicle position and speed are described. A system of virtual probe sensors that measure transit vehicle speeds by using the track data is also described. Examples showing the correlation between probe data and inductance loop speed-trap data are presented. Also presented is a method that uses probe sensor data to define vehicle speed along an arbitrary roadway as a function of space and time, a speed function. This speed function is used to estimate travel time given an arbitrary starting time. Finally, a graphical application is introduced for viewing real-time speed measurements from a set of virtual sensors that can be located throughout King County, Washington, on arterials and freeways.

Development of a Data Acquisition System for Autonomous Vehicle Systems

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Yucheng Liu ◽  
Andrew Le Clair ◽  
Matthew Doude ◽  
V. Reuben F. Burch
Keyword(s):  
Data Acquisition ◽  
Autonomous Vehicle ◽  
Video Recording ◽  
Network Connectivity ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Sensor Data ◽  
Vehicle Speed ◽  
Usage Patterns ◽  
Sensor Package

A data acquisition system along with a sensor package was designed and installed on an existing mechanically-controlled system to gather more data on their usage patterns. The data collected through the developed system include GPS route, vehicle speed and acceleration, engine state, transmission state, seat occupancy, fuel level, and video recording. The sensor package was designed and integrated in a way that does not interfere with the driver’s operation of the system. Cellular network connectivity was employed to retrieve sensor data so as to minimize human effort and maintain typical usage patterns of the outfitted systems. Testing and validation results showed that the developed system can correctly and effectively record data necessary for further analysis and optimization. The collected data will significantly promote system activity simulations in order to facilitate optimizing work flow at large industrial facilities and improving energy efficiency.

Multi-Sensor Data Fusion Based on ADS-B and MLAT in Approach

2014 ◽  
Vol 602-605 ◽  
pp. 2491-2494
Author(s):  
Yu Lu ◽  
Rong Shun Huang ◽  
Zi Li Xu
Keyword(s):  
Data Fusion ◽  
High Precision ◽  
Traffic Control ◽  
Kalman Filters ◽  
Tracking System ◽  
High Accuracy ◽  
Experimental Results ◽  
Sensor Data ◽  
Multi Sensor Data Fusion ◽  
Fusion Framework

ADS-B (Automatic Dependent Surveillance - Broadcast) and MLAT (Multilateration) are the main surveillance techniques for ATC (Air Traffic Control), and will play an important role in the future's tracking system. The fusion between ADS-B and MLAT is able to achieve more accurate tracking. In views of the data characters of these two techniques, this paper designs a concrete fusion framework with multi-levels based on federal Kalman filters to fuse ADS-B and MLAT in approach. Under this framework, both ADS-B and MLAT data are processed intensively to achieve high accuracy. Experimental results based on simulation and practical data illustrate the algorithm can achieve high precision.

Variational formulation incorporating spatial capacity changes to reconstruct trajectory for heterogeneous traffic conditions

2017 ◽  
Vol 44 (8) ◽  
pp. 598-610 ◽  
Author(s):  
M. Hadiuzzaman ◽  
Nazmul Haque ◽  
Sarder Rafee Musabbir ◽  
Md. Atiqul Islam ◽  
Sanjana Hossain ◽  
...  
Keyword(s):  
Variational Formulation ◽  
Heterogeneous Traffic ◽  
Sensor Data ◽  
Reference Trajectory ◽  
Fundamental Diagram ◽  
Traffic Conditions ◽  
Cumulative Count ◽  
Vehicle Trajectory ◽  
Side Friction ◽  
Probe Sensor

This study deals with the reconstruction of vehicle trajectories incorporating a data fusion framework that combines video and probe sensor data in heterogeneous traffic conditions. The framework is based on the application of variational formulation (VF) of kinematic waves for multiple lane conditions. The VF requires cumulative count and reference trajectory as boundary conditions. The VF also requires generation of lopsided network using fundamental diagram (FD) parameters. In this regard, cumulative count and FD parameters are obtained from the video sensor, while reference vehicle trajectory is obtained from the probe sensor. The analysis shows that the framework can provide an accuracy of 83% in trajectory estimation from the nearest reference trajectory. However, the accuracy decreases as the reference trajectory gets farther away from the estimated one. Additionally, an extension of the VF to accommodate roadway side friction is presented. The FD as well as lopsided network reform when the roadway capacity varies due to side friction. Consequently, the vehicle trajectory bends to accommodate the capacity fluctuation.

scholarly journals Adaptive Framework Combining Sensors and IoT for Data Monitoring in Restricted Areas

2019 ◽  
Vol 8 (11) ◽  
pp. 564-567 ◽  
Keyword(s):  
Energy Efficiency ◽  
Data Transmission ◽  
Energy Efficient ◽  
Data Transfer ◽  
Sensor Data ◽  
Data Monitoring ◽  
Security Measures ◽  
Improve Energy Efficiency ◽  
Location Data ◽  
Adaptive Framework

The deployment of Internet-of-Things (IoT) enables an even richer variety of sensors at a much larger scale. Where offloading both the evaluation and the polling of IoT sensor data to the cloud would improve energy efficiency and data transfer costs for the mobile. We build an energy efficient framework for Combining Sensors and IoT to help developers easily builds applications that evaluate sensor data on the server via data transmission. We built a advanced framework to compress data i.e Novel Data Compression Approach that helps the user to know the regular movement of particular person with the sensor within the limited premises and the location surveillance of the host will be saving the location data with some security measures We also implement our protocol and compare it with the certificate-based scheme to illustrate its feasibility.

Testing and Analysis of Autonomous Emergency Braking Systems Using the Euro NCAP Vehicle Target

2014 ◽  
Author(s):  
Matthew L. Schwall ◽  
John D. Neal ◽  
Charles J. Retallack ◽  
Robert E. Larson ◽  
Graeme F. Fowler
Keyword(s):  
Sensor Data ◽  
Vehicle Speed ◽  
Test Results ◽  
Passenger Cars ◽  
Collision Warning ◽  
Euro Ncap ◽  
Emergency Braking ◽  
Collision Mitigation ◽  
The Subject ◽  
Forward Collision Warning

Passenger cars are increasingly available equipped with Autonomous Emergency Braking (AEB). AEB systems detect likely forward collisions and apply the vehicle’s brakes if the driver fails to do so, reducing vehicle speed in order to mitigate or potentially avoid a collision. The performance of these systems is experimentally evaluated in tests including those specified by the European New Car Assessment Program (Euro NCAP) and by the Insurance Institute for Highway Safety (IIHS). In both of these testing programs the subject vehicle is driven towards a Euro NCAP Vehicle Target, an inflatable device designed to have visual and radar reflective characteristics similar to the rear of a compact car. The results reported by Euro NCAP and the IIHS have revealed significant differences in the AEB test results achieved by various AEB-equipped vehicles. Such differences exist even between vehicles with similar sensing technologies, suggesting that the source of such disparities may be differences in sensor data processing methods or differences in collision mitigation and avoidance strategies. This paper details the performance of AEB as well as Forward Collision Warning (FCW) systems when tested with the Euro NCAP Vehicle Target. These results are analyzed, exploring the differences in the performance of these systems under the test conditions and discussing possible reasons for the observed disparities.

scholarly journals Articulated Trajectory Mapping for Reviewing Walking Tours

2020 ◽  
Vol 9 (10) ◽  
pp. 610
Author(s):  
Iori Sasaki ◽  
Masatoshi Arikawa ◽  
Akinori Takahashi
Keyword(s):  
Sensor Data ◽  
Gps Data ◽  
Trajectory Data ◽  
Characterization Methods ◽  
Indoor Location ◽  
Location Data ◽  
Line Simplification ◽  
Trajectory Mapping ◽  
New Framework ◽  
Walking Tours

This paper addresses how to enrich a map-based representation for reviewing walking tours with the features of trajectory mapping and tracing animation. Generally, a trajectory generated by raw GPS data can often be difficult to browse through on a map. To resolve this issue, we first illustrated tangled trajectory lines, inaccurate indoor positioning, and unstable trajectory lines as problems encountered when mapping raw trajectory data. Then, we proposed a new framework that focuses on GPS horizontal accuracy to locate indoor location points and find stopping points on an accelerometer. We also applied a conventional line simplification algorithm to make the trajectory cleaner and then integrated the extracted points with the clean trajectory line. Furthermore, our experiments with some actual logs of walking tours demonstrated that articulated trajectory mapping, which comprises simplification and characterization methods, sufficiently reliable and effective for better reviewing experiences. The paper contributes to the research on cleaning up map-based displays and tracing animations of raw trajectory GPS data by using not only location data but also sensor data that smartphones can collect.

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