68 citations
- Institut für RundfunktechnikDE2 papers
- Nokia (Germany)DE2 papers
- Technische Universität DresdenDE2 papers
- Universitat Politècnica de ValènciaES2 papers
- University of SurreyGB2 papers
- Arizona State UniversityUS1 paper
- Automated Precision (United States)US1 paper
- Brigham Young UniversityUS1 paper
- British Broadcasting Corporation (United Kingdom)GB1 paper
- BT Group (United Kingdom)GB1 paper
- Chalmers University of TechnologySE1 paper
- Deployable Space Systems (United States)US1 paper
10 papers
Developing a Safety Management System for the Autonomous Vehicle Industry
David Wichner, Jeffrey Wishart, Jason Sergent +1
Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (…
RAVE Checklist: Recommendations for Overcoming Challenges in Retrospective Safety Studies of Automated Driving Systems
John M. Scanlon, Eric R. Teoh, David G. Kidd +12
The public, regulators, and domain experts alike seek to understand the effect of deployed SAE level 4 automated driving system (ADS) technologies on safety. The recent expansion o…
Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task
Nathan Sandholtz, Yohsuke Miyamoto, Luke Bornn +1
This paper introduces a probabilistic framework to estimate parameters of an acquisition function given observed human behavior that can be modeled as a collection of sample paths…
Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V Communication
Alperen Gündogan, H. Murat Gürsu, Volker Pauli +1
We consider the distributed resource selection problem in Vehicle-to-vehicle (V2V) communication in the absence of a base station. Each vehicle autonomously selects transmission re…
Attentional Bottleneck: Towards an Interpretable Deep Driving Network
Jinkyu Kim, Mayank Bansal
Deep neural networks are a key component of behavior prediction and motion generation for self-driving cars. One of their main drawbacks is a lack of transparency: they should prov…
VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation
Jiyang Gao, Chen Sun, Hang Zhao +4
Behavior prediction in dynamic, multi-agent systems is an important problem in the context of self-driving cars, due to the complex representations and interactions of road compone…