[HTML][HTML] Probabilistic field approach for motorway driving risk assessment
We present an approach to assess the risk taken by on-road vehicles within the framework
of artificial field theory, envisioned for safety analysis and design of driving …
of artificial field theory, envisioned for safety analysis and design of driving …
Criticality metric for the safety validation of automated driving using model predictive trajectory optimization
The safety validation of automated driving of SAE level 3 and higher (AD) is still an unsolved
issue. In the validation process, criticality metrics can be used for two different purposes …
issue. In the validation process, criticality metrics can be used for two different purposes …
Surrounding vehicles motion prediction for risk assessment and motion planning of autonomous vehicle in highway scenarios
L Zhang, W Xiao, Z Zhang, D Meng - IEEE Access, 2020 - ieeexplore.ieee.org
Safety is the cornerstone of autonomous driving vehicles. For autonomously controlled
vehicles driving safely in complex and dynamic traffic scenarios, it is essential to precisely …
vehicles driving safely in complex and dynamic traffic scenarios, it is essential to precisely …
A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics
M Benrabah, C Orou Mousse, E Randriamiarintsoa… - Sensors, 2024 - mdpi.com
Evaluating the risk associated with operations is an essential element of safe planning and
an essential prerequisite in mobile robotics. This issue is very broad, with numerous …
an essential prerequisite in mobile robotics. This issue is very broad, with numerous …
Bayesian environment representation, prediction, and criticality assessment for driver assistance systems
M Schreier - at-Automatisierungstechnik, 2017 - degruyter.com
The dissertation approaches the questions i) how to represent the driving environment in an
environment model, ii) how to obtain such a representation, and iii) how to predict the traffic …
environment model, ii) how to obtain such a representation, and iii) how to predict the traffic …
“Watch out!”: prediction-level intervention for automated driving
It seems that autonomous driving systems are substituting human responsibilities in the
driving task. However, this does not mean that vehicles should not interact with their driver …
driving task. However, this does not mean that vehicles should not interact with their driver …
The foresighted driver model
The Intelligent Driver Model (IDM) is a microscopic, time continuous car following model for
the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity and its …
the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity and its …
Learning interaction-aware guidance for trajectory optimization in dense traffic scenarios
B Brito, A Agarwal… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Autonomous navigation in dense traffic scenarios remains challenging for autonomous
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
Comparative assessment of safety indicators for vehicle trajectories on highways
Safety measurement and its analysis have been challenging and well-researched topics in
transportation. Conventionally, surrogate safety measures have been used as safety …
transportation. Conventionally, surrogate safety measures have been used as safety …
Risk-aversive behavior planning under multiple situations with uncertainty
This paper addresses the problem of future behavior evaluation and planning for upcoming
ADAS, especially for inner city traffic scenarios. Situations in inner city traffic scenarios are …
ADAS, especially for inner city traffic scenarios. Situations in inner city traffic scenarios are …