Search Results for author: Meixin Zhu

Found 12 papers, 2 papers with code

Data-driven Traffic Simulation: A Comprehensive Review

no code implementations24 Oct 2023 Di Chen, Meixin Zhu, Hao Yang, Xuesong Wang, Yinhai Wang

The primary objective of this paper is to review current research efforts and provide a futuristic perspective that will benefit future developments in the field.

Autonomous Driving Imitation Learning

EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning

no code implementations30 Aug 2023 Xu Han, Xianda Chen, Meixin Zhu, Pinlong Cai, Jianshan Zhou, Xiaowen Chu

The experimental results illustrate that EnsembleFollower yields improved accuracy of human-like behavior and achieves effectiveness in combining hybrid models, demonstrating that our proposed framework can handle diverse car-following conditions by leveraging the strengths of various low-level models.

EquiDiff: A Conditional Equivariant Diffusion Model For Trajectory Prediction

no code implementations12 Aug 2023 Kehua Chen, Xianda Chen, Zihan Yu, Meixin Zhu, Hai Yang

The growing popularity of deep learning has led to the development of numerous methods for trajectory prediction.

Autonomous Vehicles Graph Attention +1

FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling

1 code implementation25 May 2023 Xianda Chen, Meixin Zhu, Kehua Chen, Pengqin Wang, Hongliang Lu, Hui Zhong, Xu Han, Yinhai Wang

To address this gap and promote the development of microscopic traffic flow modeling, we establish a public benchmark dataset for car-following behavior modeling.

Autonomous Vehicles object-detection +1

Environment Transformer and Policy Optimization for Model-Based Offline Reinforcement Learning

no code implementations7 Mar 2023 Pengqin Wang, Meixin Zhu, Shaojie Shen

It models the probability distribution of the environment dynamics and reward function to capture aleatoric uncertainty and treats epistemic uncertainty as a learnable noise parameter.

Continuous Control Offline RL +4

TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformer

no code implementations4 Feb 2022 Meixin Zhu, Simon S. Du, Xuesong Wang, Hao, Yang, Ziyuan Pu, Yinhai Wang

Through cross-attention between encoder and decoder, the decoder learns to build a connection between historical driving and future LV speed, based on which a prediction of future FV speed can be obtained.

Trajectory Prediction

Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications

no code implementations2 Aug 2020 Ruimin Ke, Zhiyong Cui, Yanlong Chen, Meixin Zhu, Hao Yang, Yinhai Wang

It is among the first efforts in applying edge computing for real-time traffic video analytics and is expected to benefit multiple sub-fields in smart transportation research and applications.

Autonomous Driving Edge-computing +2

Personalized Context-Aware Multi-Modal Transportation Recommendation

no code implementations13 Oct 2019 Meixin Zhu, Jingyun Hu, Hao, Yang, Ziyuan Pu, Yinhai Wang

Also, results of the multinomial logit model show that (1) an increase in travel cost would decrease the utility of all the transportation modes; (2) people are less sensitive to the travel distance for the metro mode or a multi-modal option that containing metro, i. e., compared to other modes, people would be more willing to tolerate long-distance metro trips.

feature selection Learning-To-Rank

Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning

no code implementations3 Jan 2019 Meixin Zhu, Xuesong Wang, Yinhai Wang

This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.

Autonomous Driving reinforcement-learning +1

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