A driving intention prediction method based on hidden Markov model for autonomous driving
In a mixed-traffic scenario where both autonomous vehicles and human-driving vehicles
exist, a timely prediction of driving intentions of nearby human-driving vehicles is essential …
exist, a timely prediction of driving intentions of nearby human-driving vehicles is essential …
Vehicle trajectory prediction considering driver uncertainty and vehicle dynamics based on dynamic bayesian network
Vehicle trajectory prediction is a crucial but intricate problem for lateral driving assistance
systems because of driver uncertainty. This article presents a probabilistic vehicle-trajectory …
systems because of driver uncertainty. This article presents a probabilistic vehicle-trajectory …
Application of naturalistic driving data: A systematic review and bibliometric analysis
MR Alam, D Batabyal, K Yang, T Brijs… - Accident Analysis & …, 2023 - Elsevier
The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …
research questions in the area of driving behavior assessment, as well as the impact of …
Early recognition of driving intention for lane change based on recurrent hidden semi-Markov model
Timely recognition of driving intention is crucial in the design of a safe and effective driving
assistance system. This study proposes an efficient recognition approach based on …
assistance system. This study proposes an efficient recognition approach based on …
Driving intention identification based on long short-term memory and a case study in shifting strategy optimization
Identification of driving intentions has increasingly attracted wide attention since it can be a
valuable reference input of vehicle intelligent control systems. In this study, the long short …
valuable reference input of vehicle intelligent control systems. In this study, the long short …
Identification of driver's braking intention based on a hybrid model of GHMM and GGAP-RBFNN
X Zhao, S Wang, J Ma, Q Yu, Q Gao, M Yu - Neural Computing and …, 2019 - Springer
Driving intention has been widely used in intelligent driver assistance systems, automated
driving systems, and electric vehicle control strategies. The accuracy, practicality, and …
driving systems, and electric vehicle control strategies. The accuracy, practicality, and …
Deep learning with attention mechanism for predicting driver intention at intersection
In this paper, a driver's intention prediction near a road intersection is proposed. Our
approach uses a deep bidirectional Long Short-Term Memory (LSTM) with an attention …
approach uses a deep bidirectional Long Short-Term Memory (LSTM) with an attention …
Driving intention recognition of surrounding vehicles based on a time-sequenced weights hidden Markov model for autonomous driving
P Liu, T Qu, H Gao, X Gong - Sensors, 2023 - mdpi.com
Accurate perception, especially situational awareness, is central to the evolution of
autonomous driving. This necessitates understanding both the traffic conditions and driving …
autonomous driving. This necessitates understanding both the traffic conditions and driving …
Infrastructure-based vehicle maneuver estimation with intersection-specific models
CE Framing, FJ Heßeler, D Abel - 2018 26th mediterranean …, 2018 - ieeexplore.ieee.org
Advanced Driver Assistance Systems have the potential of making traffic safer, more efficient
and convenient. At urban intersections the conflicting intentions of different traffic participants …
and convenient. At urban intersections the conflicting intentions of different traffic participants …
An interaction-aware predictive motion planner for unmanned ground vehicles in dynamic street scenarios
International Journal of Robotics and Automation, Vol. 34, No. 3, 2019 AN INTERACTION-AWARE
PREDICTIVE MOTION PLANNER FOR UNMANNED GROUND VEHICLES IN DYNAMIC …
PREDICTIVE MOTION PLANNER FOR UNMANNED GROUND VEHICLES IN DYNAMIC …