[HTML][HTML] About calibration of car-following dynamics of automated and human-driven vehicles: Methodology, guidelines and codes
A comprehensive literature review reveals that there exist lots of ambiguities, confusion and
even contradictions in setting a car-following calibration problem. In particular, confusion …
even contradictions in setting a car-following calibration problem. In particular, confusion …
Car-following models for human-driven vehicles and autonomous vehicles: A systematic review
The focus of car-following models is to analyze the microscopic characteristics of traffic
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
Human-like autonomous car-following model with deep reinforcement learning
This study proposes a framework for human-like autonomous car-following planning based
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
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 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 …
A car-following model considering asymmetric driving behavior based on long short-term memory neural networks
Asymmetric driving behavior is a critical characteristic of human driving behaviors and has a
significant impact on traffic flow. In consideration of the asymmetric driving behavior, this …
significant impact on traffic flow. In consideration of the asymmetric driving behavior, this …
Big data for social transportation
Big data for social transportation brings us unprecedented opportunities for resolving
transportation problems for which traditional approaches are not competent and for building …
transportation problems for which traditional approaches are not competent and for building …
A sequence to sequence learning based car-following model for multi-step predictions considering reaction delay
L Ma, S Qu - Transportation research part C: emerging technologies, 2020 - Elsevier
Car-following behavior modeling is of great importance for traffic simulation and analysis.
Considering the multi-steps decision-making process in human driving, we propose a …
Considering the multi-steps decision-making process in human driving, we propose a …
Personalized car following for autonomous driving with inverse reinforcement learning
Driving automation is gradually replacing human driving maneuvers in different applications
such as adaptive cruise control and lane keeping. However, contemporary driving …
such as adaptive cruise control and lane keeping. However, contemporary driving …
Velocity control in car-following behavior with autonomous vehicles using reinforcement learning
Car-following behavior is a common driving behavior. It is necessary to consider the
following vehicle in the car-following model of autonomous vehicle (AV) under the …
following vehicle in the car-following model of autonomous vehicle (AV) under the …