Review of learning-based longitudinal motion planning for autonomous vehicles: research gaps between self-driving and traffic congestion

H Zhou, J Laval, A Zhou, Y Wang… - Transportation …, 2022 - journals.sagepub.com
Self-driving technology companies and the research community are accelerating the pace of
use of machine learning longitudinal motion planning (mMP) for autonomous vehicles (AVs) …

Autonomous vehicle's impact on traffic: Empirical evidence from waymo open dataset and implications from modelling

X Hu, Z Zheng, D Chen, J Sun - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Previous empirical behavior analysis on Autonomous Vehicles (AV) mainly focused on
vehicles with Adaptive Cruise Control (ACC) system due to the lack of high-level AV dataset …

Evidence on impacts of automated vehicles on traffic flow efficiency and emissions: Systematic review

E Aittoniemi - IET Intelligent Transport Systems, 2022 - Wiley Online Library
Despite high expectations of driving automation improving road traffic, its practical
implications on traffic flow and emissions are not yet definite. This study systematically …

Reinforcement Learning based cooperative longitudinal control for reducing traffic oscillations and improving platoon stability

L Jiang, Y Xie, NG Evans, X Wen, T Li… - … Research Part C …, 2022 - Elsevier
Stop-and-go traffic poses significant challenges to the efficiency and safety of traffic
operations. In this study, a cooperative longitudinal control based on Soft Actor Critic (SAC) …

Congestion-mitigating MPC design for adaptive cruise control based on Newell's car following model: History outperforms prediction

H Zhou, A Zhou, T Li, D Chen, S Peeta… - … Research Part C …, 2022 - Elsevier
Currently, model predictive control (MPC) for adaptive cruise control (ACC) systems relies
on the prediction of the leader's motion to plan the follower's trajectory. However, such …

Car-following behavior of human-driven vehicles in mixed-flow traffic: A driving simulator study

A Zhou, Y Liu, E Tenenboim… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs) will
inevitably coexist on roads in the future, creating mixed-flow traffic. The heterogeneous car …

Comparing the observable response times of ACC and CACC systems

JS Brunner, MA Makridis… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper analyzes trajectory observations from vehicles driving in platoon formation and
they are equipped with Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise …

Driving strategy of connected and autonomous vehicles based on multiple preceding vehicles state estimation in mixed vehicular traffic

H Ding, H Pan, H Bai, X Zheng, J Chen… - Physica A: Statistical …, 2022 - Elsevier
In the near future, connected and autonomous vehicles (CAVs) will share road space with
human-driven vehicles (HVs). In this mixed vehicular traffic, effective following cooperation …

A stochastic model for stop-and-go phenomenon in traffic oscillation: On the prospective of macro and micro traffic flow

J Wen, L Hong, M Dai, X Xiao, C Wu - Applied Mathematics and …, 2023 - Elsevier
To investigate the stop-and-go phenomenon triggered by car-following, a hybrid model of
micro and macro is proposed. Firstly, with the stochastic nature of driving behavior, a …

Revolution on wheels: A survey on the positive and negative impacts of connected and automated vehicles in era of mixed-autonomy

W Yue, C Li, P Duan, FR Yu - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of autonomous driving technology, it is foreseeable that connected
and automated vehicles (CAVs) will be fully popularized in people's lives. During this …