Anticipating accidents in dashcam videos
Abstract We propose a Dynamic-Spatial-Attention (DSA) Recurrent Neural Network (RNN)
for anticipating accidents in dashcam videos (Fig. 1). Our DSA-RNN learns to (1) distribute …
for anticipating accidents in dashcam videos (Fig. 1). Our DSA-RNN learns to (1) distribute …
Convolution neural network-based lane change intention prediction of surrounding vehicles for ACC
Adaptive cruise control is one of the most widely used vehicle driver assistance systems.
However, uncertainty about drivers' lane change maneuvers in surrounding vehicles, such …
However, uncertainty about drivers' lane change maneuvers in surrounding vehicles, such …
Driver action prediction using deep (bidirectional) recurrent neural network
O Olabiyi, E Martinson, V Chintalapudi… - arXiv preprint arXiv …, 2017 - arxiv.org
Advanced driver assistance systems (ADAS) can be significantly improved with effective
driver action prediction (DAP). Predicting driver actions early and accurately can help …
driver action prediction (DAP). Predicting driver actions early and accurately can help …
The value of inferring the internal state of traffic participants for autonomous freeway driving
ZN Sunberg, CJ Ho… - 2017 American control …, 2017 - ieeexplore.ieee.org
Safe interaction with human drivers is one of the primary challenges for autonomous
vehicles. In order to plan driving maneuvers effectively, the vehicle's control system must …
vehicles. In order to plan driving maneuvers effectively, the vehicle's control system must …
Probabilistic long-term prediction for autonomous vehicles
S Hoermann, D Stumper… - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
Long-term prediction of traffic participants is crucial to enable autonomous driving on public
roads. The quality of the prediction directly affects the frequency of trajectory planning. With …
roads. The quality of the prediction directly affects the frequency of trajectory planning. With …
Estimation of collective maneuvers through cooperative multi-agent planning
J Schulz, K Hirsenkorn, J Löchner… - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
In order to determine a cooperative driving strategy, it is beneficial for an autonomous
vehicle to incorporate the intended motion of surrounding vehicles within its own motion …
vehicle to incorporate the intended motion of surrounding vehicles within its own motion …
Interaction-aware occupancy prediction of road vehicles
M Koschi, M Althoff - 2017 IEEE 20th International Conference …, 2017 - ieeexplore.ieee.org
A crucial capability of autonomous road vehicles is the ability to cope with the unknown
future behavior of surrounding traffic participants. This requires using non-deterministic …
future behavior of surrounding traffic participants. This requires using non-deterministic …
Trajectory prediction of traffic agents at urban intersections through learned interactions
To navigate a complex urban environment, it is essential for autonomous vehicles to make
educated assumptions and accurate predictions of the movement of other traffic agents …
educated assumptions and accurate predictions of the movement of other traffic agents …
Control of a city road network: Distributed exact verification of traffic safety
A Colombo, GR de Campos… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
A least-restrictive supervisor for vehicle collision avoidance is a control algorithm that can
detect an unsafe maneuver by a set of human-driven or autonomous vehicles, intervening …
detect an unsafe maneuver by a set of human-driven or autonomous vehicles, intervening …
[图书][B] Safe and interactive autonomy: Control, learning, and verification
D Sadigh - 2017 - search.proquest.com
The goal of my research is to enable safe and reliable integration of human-robot systems in
our society by providing a unified framework for modeling and design of these systems …
our society by providing a unified framework for modeling and design of these systems …