A review of HMM-based approaches of driving behaviors recognition and prediction
Current research and development in recognizing and predicting driving behaviors plays an
important role in the development of Advanced Driver Assistance Systems (ADAS). For this …
important role in the development of Advanced Driver Assistance Systems (ADAS). For this …
[HTML][HTML] Yellow light dilemma zone researches: a review
Y Zhang, C Fu, L Hu - Journal of traffic and transportation engineering …, 2014 - Elsevier
The yellow light dilemma zone is widely known as an area on the high-speed intersection
approach, where vehicles neither safely stop before the stop line nor proceed through the …
approach, where vehicles neither safely stop before the stop line nor proceed through the …
Aggressive driving behavior prediction considering driver's intention based on multivariate-temporal feature data
Aggressive driving behavior is mainly motivated by the intention of the driver; therefore, the
underlying intention of behavior should be considered in investigating aggressive driving …
underlying intention of behavior should be considered in investigating aggressive driving …
Prediction performance of lane changing behaviors: a study of combining environmental and eye-tracking data in a driving simulator
Q Deng, J Wang, K Hillebrand… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Advanced Driver Assistance Systems (ADAS) are systems developed to assist the human
driver and therefore to make driving safer and better. Understanding and predicting human …
driver and therefore to make driving safer and better. Understanding and predicting human …
Kernelized convolutional transformer network based driver behavior estimation for conflict resolution at unsignalized roundabout
The modeling of driver behavior plays an essential role in developing Advanced Driver
Assistance Systems (ADAS) to support the driver in various complex driving scenarios. The …
Assistance Systems (ADAS) to support the driver in various complex driving scenarios. The …
Modeling and simulation of approaching behaviors to signalized intersections based on risk quantification
J Hua, G Lu, HX Liu - Transportation research part C: emerging …, 2022 - Elsevier
The stop/go decisions made by drivers who are approaching signalized intersections during
yellow period will affect the safety and efficiency of intersections. Existing research mostly …
yellow period will affect the safety and efficiency of intersections. Existing research mostly …
Improved driving behaviors prediction based on fuzzy logic-hidden markov model (fl-hmm)
Research and development of human driving behaviors play an important role in the
development of assistance systems. In this contribution, a driving behaviors prediction …
development of assistance systems. In this contribution, a driving behaviors prediction …
Predicting time-varying, speed-varying dilemma zones using machine learning and continuous vehicle tracking
This paper proposes an innovative framework of predicting driver behavior under varying
dilemma zone conditions using artificial intelligence-based machine learning. The …
dilemma zone conditions using artificial intelligence-based machine learning. The …
Analysing driver's decision in dilemma zone at signalized intersections under disordered traffic conditions
Delay in the decision-making process of stop or go during the amber phase of the signal
cycle often leads to abrupt hard deceleration or red light violations at signalized …
cycle often leads to abrupt hard deceleration or red light violations at signalized …
Analysis of yellow-light running at signalized intersections using high-resolution traffic data
G Lu, Y Wang, X Wu, HX Liu - Transportation research part A: policy and …, 2015 - Elsevier
Many accidents occurring at signalized intersections are closely related to drivers' decisions
of running through intersections during yellow light, ie, yellow-light running (YLR). Therefore …
of running through intersections during yellow light, ie, yellow-light running (YLR). Therefore …