A5081266790- Traffic control and management
- Autonomous Vehicle Technology and Safety
- Traffic Prediction and Management Techniques
- Transportation Planning and Optimization
- Video Surveillance and Tracking Methods
- Vehicular Ad Hoc Networks (VANETs)
- Vehicle Dynamics and Control Systems
- Advanced Neural Network Applications
- Vehicle emissions and performance
- Robotics and Sensor-Based Localization
- Traffic and Road Safety
- Transportation and Mobility Innovations
- Advanced Sensor and Control Systems
- Advanced Algorithms and Applications
- Remote Sensing and LiDAR Applications
- Anomaly Detection Techniques and Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Measurement and Detection Methods
- Image and Signal Denoising Methods
- Advanced Vision and Imaging
- Industrial Technology and Control Systems
- Simulation and Modeling Applications
- Robotic Path Planning Algorithms
- Indoor and Outdoor Localization Technologies
- Real-time simulation and control systems
Chang'an University
2016-2025
North University of China
2025
China Mobile (China)
2016-2024
Center of Hubei Cooperative Innovation for Emissions Trading System
2023-2024
Xi'an Technological University
2022-2024
Gorgias Press (United States)
2023
Institute of Electrical and Electronics Engineers
2023
James Cook University
2022
Missouri Western State University
2022
Xi’an University
2021
Dedicated short-range communication (DSRC) and 4G-LTE are two widely used candidate schemes for Connected Vehicle (CV) applications. It is thus of great necessity to compare these most viable standards clarify which one can meet the requirements V2X scenarios with respect road safety, traffic efficiency, infotainment. To best our knowledge, almost all existing studies on comparing feasibility DRSC or LTE in applications use software-based simulations, may not represent realistic constraints....
It is vital that autonomous vehicles acquire accurate and real-time information about objects in their vicinity, which fully guarantees the safety of passengers vehicle various environments. Three-dimensional light detection ranging (3D LIDAR) sensors can directly obtain position geometric structure an object within its range, whereas use vision cameras most suitable for recognition. Accordingly, this paper, we present a novel identification method fuses complementary obtained by two types...
Improper handling of on-ramp merging may cause severe decrease traffic efficiency and contribute to lower fuel economy, even increasing the collision risk. Cooperative control for connected automated vehicles (CAVs) has potential significantly reduce negative impact improve safety efficiency. Implementation cooperative requires assistance vehicle (V2V) infrastructure (V2I) communication, wherein communication delay on CAV control. In this paper, scenario CAVs considering V2I are studied....
Vehicle merging is one of the main causes reduced traffic efficiency, increased risk collision, and fuel consumption. Connected automated vehicles (CAVs) can improve increase safety, reduce negative environmental impacts through effective communication control. Therefore, to efficiency consumption in on-ramp scenarios, this paper addresses global optimal coordination CAVs a zone. Herein, cooperative multi-player game-based optimization framework an algorithm are presented coordinate achieve...
Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning, and environmental understanding. To precisely extract irregular or those blocked by obstructions on from 3D LiDAR data, a dedicated algorithm consisting four steps proposed this paper. The are follows. First, data pre-processed, employing position attitude information, many noise points deleted. Second, ground quickly separated pre-processed...
Ramp merging represents a bottleneck scenario that causes traffic congestion, accidents, and increases emissions. Connected Automated Vehicles (CAVs) can realize the coordinated control of ramp through vehicle-to- infrastructure (V2I) for relieving above problems. Considering previous studies on centralized only involved single mainline, this paper proposes multi-lane collaborative strategy using cooperative game. First, rules different lanes vehicles in area are defined, so achieve safely....
Recently, deep convolutional neural networks (DCNN) have been widely used in semantic segmentation tasks and achieved high accuracy. However, most algorithms based on DCNN computational complexity, making them unsuitable for real‐time segmentation. To solve this problem, paper proposes a algorithm the STDC network. The adopts an “encoder–decoder” embedded U‐shaped architecture to realize while maintaining Following encoder, mixed pooling attention module is designed expand receptive field,...
Abstract In this research, by taking advantage of dynamic fuel consumption–speed data from Internet Vehicles, we develop two novel computational approaches to more accurately estimate truck consumption. The first approach is on the basis a index, named energy consumption which explicitly reflect relationship between and drivers’ driving behaviors obtained Vehicles. second based Generalized Regression Neural Network model implicitly establish same relationship. We further compare proposed...
Curve is the traffic accident-prone area in system of structural road. How to effectively detect lane-line and timely give information ahead for drivers a difficult point assisted safe driving. The traditional lane detection technology not very applicable curved road conditions. Thus, curve algorithm which based on straight-curve model proposed this paper method has good applicability most First, divides image into region interest background by analyzing basic characteristics image. further...
The traffic congestion detection based on the internet of vehicles is gaining enormous research interest. A vehicle‐to‐vehicle (V2V)‐based method for road proposed. Firstly, a fuzzy controller was constructed vehicle speed, density, and rating system, level local evaluated. Then, neighbouring queried V2V communication, regional obtained large sub‐sample hypothesis test. Finally, simulation test platform built in network simulation, back‐off time slots received packets nodes were calculated....
Real-time, precise and low-cost vehicular positioning systems associated with global continuous coordinates are needed for path planning motion control in autonomous vehicles. However, existing do not perform well urban canyons, tunnels indoor parking lots. To address this issue, paper proposes a multi-sensor system that combines (GPS), camera in-vehicle sensors assisted by kinematic dynamic vehicle models. First, the eliminates image blurring removes false feature correspondences to ensure...