Pei Li

Pei Li

University of Central Florida

H-index: 9

North America-United States

About Pei Li

Pei Li, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at University of Central Florida, specializes in the field of Traffic Safety, Data Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Demystifying Deep Reinforcement Learning-Based Autonomous Vehicle Decision-Making

A probabilistic framework for estimating the risk of pedestrian-vehicle conflicts at intersections

Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems

How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials

PFL-LSTR: A privacy-preserving framework for driver intention inference based on in-vehicle and out-vehicle information

Real-time big data analytics and proactive traffic safety management visualization system

Improving spatiotemporal transferability of real-time crash likelihood prediction models using transfer-learning approaches

Real-time crash likelihood prediction using temporal attention–based deep learning and trajectory fusion

Pei Li Information

University

Position

___

Citations(all)

545

Citations(since 2020)

540

Cited By

78

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

9

i10Index(since 2020)

9

Email

University Profile Page

University of Central Florida

Google Scholar

View Google Scholar Profile

Pei Li Skills & Research Interests

Traffic Safety

Data Analysis

Top articles of Pei Li

Title

Journal

Author(s)

Publication Date

Demystifying Deep Reinforcement Learning-Based Autonomous Vehicle Decision-Making

arXiv preprint arXiv:2403.11432

Hanxi Wan

Pei Li

Arpan Kusari

2024/3/18

A probabilistic framework for estimating the risk of pedestrian-vehicle conflicts at intersections

IEEE Transactions on Intelligent Transportation Systems

Pei Li

Huizhong Guo

Shan Bao

Arpan Kusari

2023/7/28

Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems

Transportation research part C: emerging technologies

Jiqian Dong

Sikai Chen

Mohammad Miralinaghi

Tiantian Chen

Pei Li

...

2023/11/1

How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials

IEEE Transactions on Intelligent Vehicles

Pei Li

Keshu Wu

Yang Cheng

Steven T Parker

David A Noyce

2023/10/23

PFL-LSTR: A privacy-preserving framework for driver intention inference based on in-vehicle and out-vehicle information

arXiv preprint arXiv:2309.00790

Runjia Du

Pei Li

Sikai Chen

Samuel Labi

2023/9/2

Real-time big data analytics and proactive traffic safety management visualization system

Journal of transportation engineering, Part A: Systems

Mohamed Abdel-Aty

Ou Zheng

Yina Wu

Amr Abdelraouf

Heesub Rim

...

2023/8/1

Improving spatiotemporal transferability of real-time crash likelihood prediction models using transfer-learning approaches

Transportation research record

Pei Li

Mohamed Abdel-Aty

Shile Zhang

2022/11

Real-time crash likelihood prediction using temporal attention–based deep learning and trajectory fusion

Journal of transportation engineering, Part A: Systems

Pei Li

Mohamed Abdel-Aty

2022/7/1

Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles

Arpan Kusari

Pei Li

Hanzhi Yang

Nikhil Punshi

Mich Rasulis

...

2022/6/4

A hybrid machine learning model for predicting real-time secondary crash likelihood

Accident Analysis & Prevention

Pei Li

Mohamed Abdel-Aty

2022/2/1

A novel traffic simulation framework for testing autonomous vehicles using sumo and carla

arXiv preprint arXiv:2110.07111

Pei Li

Arpan Kusari

David J LeBlanc

2021/10/14

Driving maneuvers detection using semi-supervised long short-term memory and smartphone sensors

Transportation research record

Pei Li

Mohamed Abdel-Aty

Zubayer Islam

2021/9

Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data

Accident Analysis & Prevention

Pei Li

Mohamed Abdel-Aty

Jinghui Yuan

2021/2/1

Real-Time Traffic Safety Evaluation in the Context of Connected Vehicles and Mobile Sensing

Pei Li

2021

A deep learning approach for real-time crash risk prediction at urban arterials

Pei Li

2020

A deep learning approach to detect real-time vehicle maneuvers based on smartphone sensors

IEEE Transactions on Intelligent Transportation Systems

Pei Li

Mohamed Abdel-Aty

Qing Cai

Zubayer Islam

2020/10/28

The application of novel connected vehicles emulated data on real-time crash potential prediction for arterials

Accident Analysis & Prevention

Pei Li

Mohamed Abdel-Aty

Qing Cai

Cheng Yuan

2020/9

Prediction of pedestrian crossing intentions at intersections based on long short-term memory recurrent neural network

Transportation research record

Shile Zhang

Mohamed Abdel-Aty

Jinghui Yuan

Pei Li

2020/4

Using Smartphone as On-board unit (OBU) Emulator Implementation Study

Mohamed A Abdel-Aty

Qing Cai

Shaurya Agarwal

Zubayer Islam

Peiheng Li

...

2020/2/1

Real-time crash risk prediction on arterials based on LSTM-CNN

Accident Analysis & Prevention

Pei Li

Mohamed Abdel-Aty

Jinghui Yuan

2020/2/1

See List of Professors in Pei Li University(University of Central Florida)

Co-Authors

H-index: 98
M Abdel-Aty

M Abdel-Aty

University of Central Florida

H-index: 45
Samuel Labi

Samuel Labi

Purdue University

H-index: 36
David Noyce

David Noyce

University of Wisconsin-Madison

H-index: 29
Shan Bao

Shan Bao

University of Michigan-Dearborn

H-index: 22
Jinghui Yuan

Jinghui Yuan

University of Central Florida

academic-engine