Scenario understanding and motion prediction for autonomous vehicles—review and comparison
Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
A review of vehicle lane change research
C Ma, D Li - Physica A: Statistical Mechanics and its Applications, 2023 - Elsevier
Vehicle lane change behavior, which is an important part of traffic flow theory, can have a
fundamental impact on the macro and micro characteristics of traffic flow. At the same time, it …
fundamental impact on the macro and micro characteristics of traffic flow. At the same time, it …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Survey on deep neural networks in speech and vision systems
This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …
algorithms, and systems in speech and vision applications. Recent advances in deep …
Simultaneous modeling of car-following and lane-changing behaviors using deep learning
Car-following (CF) and lane-changing (LC) behaviors are two basic movements in traffic
flow which are generally modeled separately in the literature, and thus the interaction …
flow which are generally modeled separately in the literature, and thus the interaction …
A xgboost-based lane change prediction on time series data using feature engineering for autopilot vehicles
Road accidents wreck lives. Could technology stop them from happening? Driving better
road safety with technology and artificial intelligence are the key elements considered by …
road safety with technology and artificial intelligence are the key elements considered by …
Environment-attention network for vehicle trajectory prediction
In vehicle trajectory prediction, the difficulty in modeling the interaction relationship between
vehicles lies in constructing the interaction structure between the vehicles in the traffic …
vehicles lies in constructing the interaction structure between the vehicles in the traffic …
Key feature selection and risk prediction for lane-changing behaviors based on vehicles' trajectory data
Risky lane-changing (LC) behavior of vehicles on the road has negative effects on traffic
safety. This study presents a research framework for key feature selection and risk prediction …
safety. This study presents a research framework for key feature selection and risk prediction …
Toward safe and smart mobility: Energy-aware deep learning for driving behavior analysis and prediction of connected vehicles
Connected automated driving technologies have shown tremendous improvement in recent
years. However, it is still not clear how driving behaviors and energy consumption correlate …
years. However, it is still not clear how driving behaviors and energy consumption correlate …
Predicting vehicle behaviors over an extended horizon using behavior interaction network
Anticipating possible behaviors of traffic participants is an essential capability of
autonomous vehicles. Many behavior detection and maneuver recognition methods only …
autonomous vehicles. Many behavior detection and maneuver recognition methods only …