Recent developments and research needs in modeling lane changing
Z Zheng - Transportation research part B: methodological, 2014 - Elsevier
This paper comprehensively reviews recent developments in modeling lane-changing
behavior. The major lane changing models in the literature are categorized into two groups …
behavior. The major lane changing models in the literature are categorized into two groups …
A review of the effect of traffic and weather characteristics on road safety
Taking into consideration the increasing availability of real-time traffic data and stimulated by
the importance of proactive safety management, this paper attempts to provide a review of …
the importance of proactive safety management, this paper attempts to provide a review of …
Crash data augmentation using variational autoencoder
In this paper, we present a data augmentation technique to reproduce crash data. The
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach
It has been well recognized that human driver's limits, heterogeneity, and selfishness
substantially compromise the performance of our urban transport systems. In recent years, in …
substantially compromise the performance of our urban transport systems. In recent years, in …
A data-driven lane-changing model based on deep learning
DF **e, ZZ Fang, B Jia, Z He - Transportation research part C: emerging …, 2019 - Elsevier
Abstract Lane-changing (LC), which is one of the basic driving behavior, largely impacts on
traffic efficiency and safety. Modeling an LC process is challenging due to the complexity …
traffic efficiency and safety. Modeling an LC process is challenging due to the complexity …
A Bayesian generalised extreme value model to estimate real-time pedestrian crash risks at signalised intersections using artificial intelligence-based video analytics
Pedestrians represent a vulnerable road user group at signalised intersections. As such,
properly estimating pedestrian crash risk at discrete short intervals is important for real-time …
properly estimating pedestrian crash risk at discrete short intervals is important for real-time …
A recurrent neural network based microscopic car following model to predict traffic oscillation
This paper proposes a recurrent neural network based microscopic car following model that
is able to accurately capture and predict traffic oscillation. Neural network models have …
is able to accurately capture and predict traffic oscillation. Neural network models have …
On the impact of cooperative autonomous vehicles in improving freeway merging: a modified intelligent driver model-based approach
Transport researchers and practitioners have long been seeking capable solutions to deal
with the traffic oscillations caused by freeway merging. Although existing approaches based …
with the traffic oscillations caused by freeway merging. Although existing approaches based …
[HTML][HTML] Variable speed limit: A microscopic analysis in a connected vehicle environment
B Khondaker, L Kattan - Transportation Research Part C: Emerging …, 2015 - Elsevier
This paper presents a Variable Speed Limit (VSL) control algorithm for simultaneously
maximizing the mobility, safety and environmental benefit in a Connected Vehicle …
maximizing the mobility, safety and environmental benefit in a Connected Vehicle …
A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles
Y Zhang, Y Chen, X Gu, NN Sze, J Huang - Accident Analysis & Prevention, 2023 - Elsevier
Driving style may have an important effect on traffic safety. Proactive crash risk prediction for
lane-changing behaviors incorporating individual driving styles can help drivers make safe …
lane-changing behaviors incorporating individual driving styles can help drivers make safe …