15,128 research outputs found
Multi-Object Tracking with Interacting Vehicles and Road Map Information
In many applications, tracking of multiple objects is crucial for a
perception of the current environment. Most of the present multi-object
tracking algorithms assume that objects move independently regarding other
dynamic objects as well as the static environment. Since in many traffic
situations objects interact with each other and in addition there are
restrictions due to drivable areas, the assumption of an independent object
motion is not fulfilled. This paper proposes an approach adapting a
multi-object tracking system to model interaction between vehicles, and the
current road geometry. Therefore, the prediction step of a Labeled
Multi-Bernoulli filter is extended to facilitate modeling interaction between
objects using the Intelligent Driver Model. Furthermore, to consider road map
information, an approximation of a highly precise road map is used. The results
show that in scenarios where the assumption of a standard motion model is
violated, the tracking system adapted with the proposed method achieves higher
accuracy and robustness in its track estimations
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A data extraction system for underwater particle holography
Pulsed laser holography is an extremely powerful technique for the study of particle fields as it allows instantaneous, noninvasive high-resolution recording of substantial volumes. By replaying the real image one can obtain the size, shape,
position and - if multiple exposures are made - velocity of every object in the recorded field. Manual analysis of large volumes containing thousands of particles is, however, an enormous and time-consuming task, with operator fatigue an
unpredictable source of errors. Clearly the value of holographic measurements also depends crucially on the quality of the reconstructed image: not only will poor resolution degrade size and shape measurements, but aberrations such as coma and astigmatism can change the perceived centroid of a particle, affecting position and velocity measurements.
For large-scale applications of particle field holography, specifically the in situ recording of marine plankton with 'HoloCam,' we have developed an automated data extraction system that can be readily switched between the in-line and off-axis geometries and provides optimised reconstruction from holograms recorded underwater. As a videocamera is automatically stepped through the 200 by 200 by 1000mm sample volume, image processing and object tracking routines locate and extract particle images for further classification by a separate software module
Dynamic Arrival Rate Estimation for Campus Mobility on Demand Network Graphs
Mobility On Demand (MOD) systems are revolutionizing transportation in urban
settings by improving vehicle utilization and reducing parking congestion. A
key factor in the success of an MOD system is the ability to measure and
respond to real-time customer arrival data. Real time traffic arrival rate data
is traditionally difficult to obtain due to the need to install fixed sensors
throughout the MOD network. This paper presents a framework for measuring
pedestrian traffic arrival rates using sensors onboard the vehicles that make
up the MOD fleet. A novel distributed fusion algorithm is presented which
combines onboard LIDAR and camera sensor measurements to detect trajectories of
pedestrians with a 90% detection hit rate with 1.5 false positives per minute.
A novel moving observer method is introduced to estimate pedestrian arrival
rates from pedestrian trajectories collected from mobile sensors. The moving
observer method is evaluated in both simulation and hardware and is shown to
achieve arrival rate estimates comparable to those that would be obtained with
multiple stationary sensors.Comment: Appears in 2016 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS).
http://ieeexplore.ieee.org/abstract/document/7759357
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