A5038550389- Traffic control and management
- Autonomous Vehicle Technology and Safety
- Vehicular Ad Hoc Networks (VANETs)
- Transportation Planning and Optimization
- Vehicle emissions and performance
- Advanced Neural Network Applications
- Transportation and Mobility Innovations
- Human-Automation Interaction and Safety
- Traffic Prediction and Management Techniques
- Privacy-Preserving Technologies in Data
- Traffic and Road Safety
- Digital Transformation in Industry
- Topic Modeling
- IoT and Edge/Fog Computing
- Advanced Sensor and Energy Harvesting Materials
- Blockchain Technology Applications and Security
- Video Surveillance and Tracking Methods
- Privacy, Security, and Data Protection
- Human Pose and Action Recognition
- Advanced Optical Sensing Technologies
- Multimodal Machine Learning Applications
- Natural Language Processing Techniques
- Analytical Chemistry and Sensors
- Infrastructure Maintenance and Monitoring
- Infrared Target Detection Methodologies
Purdue University West Lafayette
2023-2025
Rice University
2025
Nanjing Normal University
2009-2024
Shandong University
2021-2024
Nanjing Normal University Taizhou College
2017-2024
Columbia University
2019-2024
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
2020-2024
Toyota Motor North America (United States)
2020-2023
Harbin Institute of Technology
2019-2023
State Key Laboratory of Robotics and Systems
2022
Connected and automated vehicles (CAVs) have the potential to address a number of safety, mobility, sustainability issues our current transportation systems. Cooperative longitudinal motion control is one key CAV technologies that allows be driven in cooperative manner achieve system-wide benefits. In this paper, we provide literature survey on progress accomplished by researchers worldwide regarding systems multiple CAVs. Specifically, architecture various reviewed answer <italic...
A Digital Twin is a digital replica of living or nonliving physical entity, and this emerging technology attracted extensive attention from different industries during the past decade. Although few studies have been conducted in transportation domain very recently, there no systematic research with holistic framework connecting various mobility entities together. In study, twin (MDT) developed, which defined as an artificial intelligence (AI)-based data-driven cloud–edge–device for services....
Digital twins found their genesis in the halls of NASA and methods product lifecycle management. Rapidly evolving trends around proliferation sensors, Internet Things, Industry 4.0, cyber-physical systems have spurred growth digital twins. This paper reviews use connected automated vehicles (CAVs). Strictly speaking, must communication between a physical system its model, as opposed to similar methodologies that achieve indirect through iteration, or substitute different parts simulation...
With the emergence of Large Language Models (LLMs) and Vision Foundation (VFMs), multimodal AI systems benefiting from large models have potential to equally perceive real world, make decisions, control tools as humans. In recent months, LLMs shown widespread attention in autonomous driving map systems. Despite its immense potential, there is still a lack comprehensive understanding key challenges, opportunities, future endeavors apply LLM this paper, we present systematic investigation...
By March 25, our transaction has received a total of 619 original submissions. Our current average number submissions per day (SPD) rate is 7.37. Given this SPD, I would like to expand editorial board include at least 120 members ensure the review quality services.
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles (CAV), including perception, planning, control. However, its reliance on vehicular data model training presents significant challenges related to in-vehicle user privacy communication overhead generated by massive volumes. Federated (FL) a decentralized ML approach that enables multiple vehicles collaboratively develop models, broadening from various driving environments, enhancing overall performance,...
Federated learning (FL) has been gaining attention for its ability to share knowledge while maintaining user data, protecting privacy, increasing efficiency, and reducing communication overhead. Decentralized FL (DFL) is a decentralized network architecture that eliminates the need central server in contrast centralized (CFL). DFL enables direct between clients, resulting significant savings resources. In this paper, comprehensive survey profound perspective are provided DFL. First, review...
The future of autonomous vehicles lies in the convergence human-centric design and advanced AI capabilities. Autonomous will not only transport passengers but also interact adapt to their desires, making journey comfortable, efficient, pleasant. In this paper, we present a novel framework that leverages Large Language Models (LLMs) enhance vehicles' decision-making processes. By integrating LLMs' natural language capabilities contextual understanding, specialized tools usage, synergizing...
The fusion of human-centric design and artificial intelligence capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond traditional transportation. These can dynamically interact with passengers adapt to their preferences. This article proposes a novel framework leverages large language models (LLMs) enhance the decision-making process in vehicles. By utilizing LLMs' contextual understanding abilities specialized tools, we aim integrate reasoning...
The emergence of connected and automated vehicle (CAV) technology has the potential to bring a number benefits our existing transportation systems. Specifically, when CAVs travel along an arterial corridor with signalized intersections, they can not only be driven automatically using pre-designed control models but also communicate other roadside infrastructure. In this paper, we describe cooperative eco-driving (CED) system targeted for corridors, focusing on how penetration rate affects...
Abstract Wearable sensors that can conveniently detect cytokine levels in human biofluids are essential for assisting hospitals to maximize the benefits of anti‐inflammatory therapies and avoid storms. Measurement still remains challenging existing due high interference from background. Here, this challenge is overcome through developing a flexible regenerative aptameric field‐effect transistor biosensor, consisting graphene–Nafion composite film, detecting storm biomarkers undiluted...
Digital twin, an emerging representation of cyberphysical systems, has attracted increasing attentions very recently. It opens the way to real-time monitoring and synchronization real-world activities with virtual counterparts. In this study, we develop a digital twin paradigm using advanced driver assistance system (ADAS) for connected vehicles. By leveraging vehicle-to-cloud (V2C) communication, on-board devices can upload data server through cellular network. The creates world based on...
Abstract An ultraflexible and stretchable field‐effect transistor nanosensor is presented that uses aptamer‐functionalized monolayer graphene as the conducting channel. Specific binding of aptamer with target biomarker induces a change in carrier concentration graphene, which measured to determine concentration. Based on Mylar substrate only 2.5‐µm thick, capable conforming underlying surfaces (e.g., those human tissue or skin) undergo large bending, twisting, stretching deformations. In...
Digital Twin, as an emerging technology related to Cyber-Physical Systems (CPS) and Internet of Things (IoT), has attracted increasing attentions during the past decade. Conceptually, a Twin is digital replica physical entity in real world, this leveraged study design cooperative driving system at non-signalized intersections, allowing connected vehicles cooperate with each other cross intersections without any full stops. Within proposed framework, we developed enhanced first-in-first-out...
As a good example of Advanced Driver-Assistance Systems (ADAS), Advisory Speed Assistance (ASA) helps improve driving safety and possibly energy efficiency by showing advisory speed to the driver an intelligent vehicle. However, driver-based tracking errors often emerge, due perception reaction delay, as well imperfect vehicle control, degrading effectiveness ASA system. In this study, we propose learning-based approach modeling behavior, aiming predict compensate for in real time. Subject...
Ramp merging is considered as one of the most difficult driving scenarios due to chaotic nature in both longitudinal and lateral driver behaviors (namely lack effective coordination) area. In this study, we have designed a cooperative ramp system for connected vehicles, allowing vehicles cooperate with others prior arriving at zone. Different from existing studies that utilize dedicated short-range communication, adopt Digital Twin approach based on vehicle-to-cloud communication. On-board...
A Digital Twin is defined as a digital replica of real entity in the physical world. In this study, simulation developed for connected and automated vehicles (CAVs) by leveraging Unity game engine. architecture proposed, which contains world Particularly, consists three layers, where objects are built to simulate "hardware", scripting API used "software", external tools (e.g., SUMO, MATLAB, python, and/or AWS) leveraged enhance functionalities. case study personazlied adaptive cruise control...
Connected and automated vehicles (CAVs) are supposed to share the road with human-driven (HDVs) in a foreseeable future. Therefore, considering mixed traffic environment is more pragmatic, as well-planned operation of CAVs may be interrupted by HDVs. In circumstance that human behaviors have significant impacts, need understand HDV make safe actions. this study, we develop driver digital twin (DDT) for online prediction personalized lane-change behavior, allowing predict surrounding...
The metaverse is a perpetual, immersive, and shared digital universe that linked to but beyond the physical reality, this emerging technology attracting enormous attention from different industries. In article, we define first holistic realization of in mobility domain, coined as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">metamobility</i> . We present our vision what metamobility will be describe its basic architecture. also propose two...
Connected and Automated Vehicles (CAVs) represent a rapidly growing technology in the automotive domain sector, offering promising solutions to address challenges such as traffic accidents, congestion, pollution. By leveraging CAVs, we have opportunity create transportation system that is safe, efficient, environmentally sustainable. Machine learning-based methods are widely used CAVs for crucial tasks like perception, planning, control, where machine learning models solely trained with...
Cooperative Driving Automation (CDA) stands at the forefront of evolving landscape vehicle automation, elevating driving capabilities within intricate real-world environments. This research aims to navigate path toward future CDA by offering a thorough examination from perspective Planning and Control (PnC). It classifies state-of-the-art literature according classes defined Society Automotive Engineers (SAE). The strengths, weaknesses, requirements PnC for each class are analyzed. analysis...