A5058528908- Vehicle Dynamics and Control Systems
- Vehicle emissions and performance
- Autonomous Vehicle Technology and Safety
- Infrastructure Maintenance and Monitoring
- Advanced Measurement and Detection Methods
- Transport Systems and Technology
- Software System Performance and Reliability
- Network Security and Intrusion Detection
- Software-Defined Networks and 5G
- Asphalt Pavement Performance Evaluation
Tongji University
2022-2023
McGill University
2022
The tire-road peak adhesion coefficient (TRPAC) is defined as the ratio of to vertical load tire, which can characterize ability a tire adhere road. Reliable TRPAC estimation not only benefit vehicle active safety system, but also serve intelligent transportation system improve traffic participants. Considering problems low accuracy and poor real-time performance caused by low-quality sensor information in existing methods, fusion framework based on assessment multisource quality proposed...
The tire-road peak adhesion coefficient (TRPAC) describes the tire limit that a road can provide. TRPAC is key parameter for precise vehicle motion control and an important basis decision-making planning of intelligent vehicles. Considering critical difficult problems in estimation TRPAC, such as slow convergence low accuracy, method based on fusion dynamics machine vision proposed this paper. Based observability theory nonlinear systems, local weak dynamics-based estimator analyzed to...
Abstract Vehicle mass is an important parameter for motion control of intelligent vehicles, but hard to directly measure using normal sensors. Therefore, accurate estimation vehicle becomes crucial. In this paper, a method based on fusion machine learning and dynamic model introduced. method, feedforward neural network (FFNN) used learn the relationship between other state parameters, namely longitudinal speed acceleration, driving or braking torque, wheel angular speed. dynamics-based...
The tire-road peak adhesion coefficient (TRPAC), which cannot be directly measured by on-board sensors, is essential to road traffic safety. Reliable TRPAC estimation can not only serve the vehicle active safety system, but also benefit of other participants. In this paper, a fusion method considering model uncertainty proposed. Based on virtual sensing theory, an image-based estimator deep-learning and kinematic designed realize accurate classification surface condition will travel in...
Monitoring distributed service-based cloud applications and understanding the interactions among different components are crucial to diagnose resolve performance issues. However, many existing monitoring systems require sophisticated application and/or platform instrumentation cannot be deployed on-demand, or they provide only partial functionality. In most cases, comes with a significant overhead. To overcome these shortcomings, this paper presents DyMonD, holistic framework that...