Factors affecting traffic flow efficiency implications of connected and autonomous vehicles: A review and policy recommendations

S Narayanan, E Chaniotakis, C Antoniou - Advances in Transport Policy …, 2020 - Elsevier
Connected and autonomous vehicles are expected to gradually enter the transport modal
mix sooner or later. Academic discussions of their expected impacts are well underway …

Data-driven models for train control dynamics in high-speed railways: LAG-LSTM for train trajectory prediction

J Yin, C Ning, T Tang - Information Sciences, 2022 - Elsevier
The construction of an accurate train control model (TCM) is crucial to the design of
automatic train operation and real-time traffic management systems in high-speed railways …

Personalized car-following control based on a hybrid of reinforcement learning and supervised learning

D Song, B Zhu, J Zhao, J Han… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the development of intelligent vehicles, more research has focused on achieving
human-like driving. As an important component of intelligent vehicle control, car-following …

A novel asymmetric car following model for driver-assist enabled vehicle dynamics

M Shang, B Rosenblad, R Stern - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Adaptive cruise control (ACC) vehicles are proving to be the first generation of driver-assist
enabled vehicles. In order to study the impacts of ACC vehicles on string stability and traffic …

Car-following models: A multidisciplinary review

TT Zhang, PJ **, ST McQuade… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Car-following (CF) algorithms are crucial components of traffic simulations and have been
integrated into many production vehicles equipped with Advanced Driving Assistance …

[HTML][HTML] Geometry-aware car-following model construction: Theoretical modeling and empirical analysis on horizontal curves

X Yang, Z Liu, Q Cheng, P Liu - Transportation Research Part C: Emerging …, 2024 - Elsevier
Road geometry significantly influences the physical forces acting on vehicles and the
perceptual ability of drivers. Unfortunately, most available car-following models ignore the …

Data-driven approaches for modeling train control models: Comparison and case studies

J Yin, S Su, J Xun, T Tang, R Liu - ISA transactions, 2020 - Elsevier
In railway systems, the train dynamics are usually affected by the external environment (eg,
snow and wind) and wear-out of on-board equipment, leading to the performance …

Gaussian process-based personalized adaptive cruise control

Y Wang, Z Wang, K Han, P Tiwari… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Advanced driver-assistance systems (ADAS) have matured over the past few decades with
the dedication to enhance user experience and gain a wider market penetration. However …

Controllable probability-limited and learning-based human-like vehicle behavior and trajectory generation for autonomous driving testing in highway scenario

C Wei, F Hui, AJ Khattak, Y Zhang, W Wang - Expert Systems with …, 2023 - Elsevier
Virtual simulation testing (VST) has become the main testing method for autonomous driving
systems (ADSs) and autonomous driving assistance algorithms (ADAAs). The behavior and …

Car following behavioral stochasticity analysis and modeling: Perspective from wave travel time

J Tian, C Zhu, D Chen, R Jiang, G Wang… - … Research Part B …, 2021 - Elsevier
This paper analyzes the car following behavioral stochasticity based on two sets of field
experimental trajectory data by measuring the wave travel time series τ˜ n (t) of vehicle n …