Transportation

In this appendix, the tested implementation in Matlab of our 2D-TDOA localization algorithm is given for the easier repetition of the obtained results and the future hardware implementation, due to the complexity of the formulas (25)-(31).
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This dataset inludes a nonlinear disturbance observer (NDOB)-based controller for attitude and altitude control of a quadrotor. The NDOB is used to estimate and compensate disturbances that are imposed naturally on the quadrotor due to aerodynamics and parameter uncertainties. It is demonstrated herein that the proposed observer can estimate external disturbances asymptotically.
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This dataset is based on the ACFR Five Roundabouts Dataset. The original tracking data of over 23,000 traffic vehicles have been processed with an optimization-based filtering method to combat measurement noise and errors. Smooth velocity and acceleration signals are reconstructed. The processed recordings have then undergone a selection process using DBSCAN to remove the erroneous samples. The remaining samples contained in this dataset are considered representative of how average human drivers approach a roundabout scenario in daily driving.
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The Jackal UGV, from Clearpath Robotics, was used as the data collecting platform. This skid-steer four-wheel-drive vehicle comes with an onboard IMU, two DC motors with encoders that measure wheel angular speeds, and current sensors that measure motor current outputs. On each side of the robot, the front wheel and back wheel are jointed with a gearbox and so spin together at the same rate and direction. The IMU provided vehicle attitude measurements in terms of Euler angles, as well as linear acceleration and angular rate of the vehicle body in three Euclidean axes.
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Extensive experimental measurement campaigns of more than 30,000 data points of end-to-end latency measurements for the following network architecture schemes is available:
- Unlicensed IoT (standalone LoRa)
- Cellular IoT (standalone LTE-M)
- Concatenated IoT (LoRa interfaced with LTE-M)
Download Data.zip to access all relevant files for the open data measurements.
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Exit Advance Guide Signs play an important role in driving safety on highway tunnels. With the increase of mountain highway in recent 10 years, how to set exit advance guide signs inside the mountain highway tunnels become a new problem in China. The paper highlighted the influence of exit advance guide signs on the driver’s eye movement in the mountainous highway tunnel.
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The proposed dataset, termed PC-Urban (Urban Point Cloud), is captured with an Ouster LiDAR sensor with 64 channels. The sensor is installed on an SUV that drives through the downtown of Perth, Western Australia (WA), Australia. The dataset comprises over 4.3 billion points captured for 66K sensor frames. The labelled data is organized as registered and raw point cloud frames, where the former has a different number of registered consecutive frames. We provide 25 class labels in the dataset covering 23 million points and 5K instances.
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This dataset contains road networks used in experiments for DRL-Router, including Sioux Falls, Anaheim, Winnipeg and Barcelona.
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The dataset collects the results of a survey of 325 respondents. Each respondent is asked to design a route from an origin to a destination taking into account the following considerations:
- The route should avoid crowds to avoid getting COVID-19.
- They should take into account the context provided: day, time, month, holiday period.
A total of 10 scenarios located in the city of Ciudad Real were designed.
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