Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling

Long-term situation prediction plays a crucial role in the development of intelligent vehicles. A major challenge still to overcome is the prediction of complex downtown scenarios with multiple road users, e.g., pedestrians, bikes, and motor vehicles, interacting with each other. This contribution tackles this challenge by combining a Bayesian filtering technique for environment representation, and machine learning as long-term predictor. More specifically, a dynamic occupancy grid map is utilized as input to a deep convolutional neural network. This yields the advantage of using spatially distributed velocity estimates from a single time step for prediction, rather than a raw data sequence, alleviating common problems dealing with input time series of multiple sensors. Furthermore, convolutional neural networks have the inherent characteristic of using context information, enabling the implicit modeling of road user interaction. Pixel-wise balancing is applied in the loss function counteracting the extreme imbalance between static and dynamic cells. One of the major advantages is the unsupervised learning character due to fully automatic label generation. The presented algorithm is trained and evaluated on multiple hours of recorded sensor data and compared to Monte-Carlo simulation

The Distance and Morphology of V723 Cassiopeiae (NOVA CASSIOPEIA 1995)

We present spatially resolved infrared spectra of V723 Cas (Nova Cassiopeia 1995) obtained over four years with the integral field spectrograph OSIRIS on Keck II. Also presented are one epoch of spatially unresolved spectra from the long slit spectrograph NIRSPEC on Keck II. The OSIRIS observations made use of the laser guide star adaptive optics facility that produced diffraction-limited spatial resolution of the strong coronal emission features in the nova ejecta. We remove the point-like continuum from V723 Cas data cubes to reveal details of the extended nebula and find that emission due to [Si VI] and [Ca VIII] has an equatorial ring structure with polar nodules-a strikingly different morphology than emission due to [Al IX], which appears as a prolate spheroid. The contrast in structure may indicate separate ejection events. Using the angular expansion and Doppler velocities observed over four epochs spaced at one year intervals, we determine the distance to V723 Cas to be 3.85+0.23-0.21 kpc. We present the OSIRIS three-dimensional data here in many ways: as narrowband images, one- and two-dimensional spectra, and a volume rendering that reveals the true shape of the ejecta.Comment: 37 pages, 8 figure

A survey on Human Mobility and its applications

Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, traffic engineering, traffic prediction and urban planning. In this survey we review major characteristics of human mobility studies including from trajectory-based studies to studies using graph and network theory. In trajectory-based studies statistical measures such as jump length distribution and radius of gyration are analyzed in order to investigate how people move in their daily life, and if it is possible to model this individual movements and make prediction based on them. Using graph in mobility studies, helps to investigate the dynamic behavior of the system, such as diffusion and flow in the network and makes it easier to estimate how much one part of the network influences another by using metrics like centrality measures. We aim to study population flow in transportation networks using mobility data to derive models and patterns, and to develop new applications in predicting phenomena such as congestion. Human Mobility studies with the new generation of mobility data provided by cellular phone networks, arise new challenges such as data storing, data representation, data analysis and computation complexity. A comparative review of different data types used in current tools and applications of Human Mobility studies leads us to new approaches for dealing with mentioned challenges