A5042733624- Traffic control and management
- Autonomous Vehicle Technology and Safety
- Vehicular Ad Hoc Networks (VANETs)
- Vehicle emissions and performance
- Transportation and Mobility Innovations
- Transportation Planning and Optimization
- Advanced Neural Network Applications
- Air Quality and Health Impacts
- Human-Automation Interaction and Safety
- Traffic and Road Safety
- Blockchain Technology Applications and Security
- IoT and Edge/Fog Computing
- Aerodynamics and Fluid Dynamics Research
- Video Surveillance and Tracking Methods
- Advanced Optical Sensing Technologies
- Traffic Prediction and Management Techniques
- Adversarial Robustness in Machine Learning
- Robotics and Sensor-Based Localization
- Digital Transformation in Industry
- Information and Cyber Security
University of California, Riverside
2020-2024
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...
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...
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...
Ramp merging is considered to be one of the major causes traffic accidents and congestion due its inherent chaotic nature. With development connected automated vehicle (CAV) technology, CAVs can conduct cooperative using communication, also handle complicated situations even with legacy vehicles. In this article, a game theory-based ramp strategy has been developed for optimal coordination in mixed traffic, which determine dynamic sequence corresponding longitudinal/lateral control. This...
Connected and automated vehicles (CAVs) provide various valuable advanced services to manufacturers, owners, mobility service providers, transportation authorities. As a result, large number of CAV applications have been proposed improve the safety, mobility, sustainability system. With increasing connectivity automation, cybersecurity connected system (CATS) has raised attention community in recent years. Vulnerabilities CAVs can lead breakdowns compromise safety (e.g., causing crashes),...
In the foreseeable future, connected and auto-mated vehicles (CAVs) human-driven will share road networks together. such a mixed traffic environment, CAVs need to understand predict maneuvers of surrounding for safer more efficient interactions, especially when human drivers bring in wide range uncertainties. this paper, we propose learning-based lane-change prediction algorithm that considers driving behaviors target driver. To provide accurate maneuver prediction, adopt hierarchical...
Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as revolutionary promoter for next-generation transportation systems. However, the vehicle-based may suffer from limited sensing range and occlusion well low penetration rates connectivity. In this paper, we propose Cyber Mobility Mirror (CMM), real-world object system 3D detection, tracking, localization, reconstruction, to explore potential of roadside sensors enabling CDA real world. The...
Ramp merging is considered as one of the major causes traffic congestion and accidents because its chaotic nature. With development connected automated vehicle (CAV) technology, cooperative ramp has become popular solutions to this problem. In a mixed situation, CAVs will not only interact with each other, but also handle complicated situations human-driven vehicles involved. paper, game theory-based strategy been developed for optimal coordination in traffic, which determines dynamic...
Urban air quality and the impact of mobile source pollutants on human health are increasing concern in transportation studies. Existing research often focuses reducing traffic congestion carbon footprints, but there's a notable gap understanding impacts from an environmentally-just perspective. Addressing this, our paper introduces integrated simulation platform that models not only traffic-related also direct implications at microscopic level. This integrates five modules: SUMO for...
Connected and automated vehicle (CAV) technology has the potential to greatly improve transportation mobility, safety, energy efficiency. However, ubiquitous vehicular connectivity also opens up door cyberattacks. In this study, we investigate cybersecurity risks of a representative cooperative traffic management application, i.e., highway on-ramp merging, in mixed environment. We develop threat models with two trajectory spoofing strategies on CAVs create congestion devise an...
Connected and Automated Vehicle (CAV) technology has the potential to greatly improve transportation mobility, safety, energy efficiency. However, ubiquitous vehicular connectivity also opens up door for cyber-attacks. In this study, we investigate cybersecurity risks of a representative cooperative traffic management application, i.e., highway on-ramp merging, in mixed environment. We develop threat models with two trajectory spoofing strategies on CAVs create congestion, devise an...
Air quality and human exposure to mobile source pollutants have become major concerns in urban transportation. Existing studies mainly focus on mitigating traffic congestion reducing carbon footprints, with limited understanding of traffic-related health impacts from the environmental justice perspective. To address this gap, we present an innovative integrated simulation platform that models air at microscopic level. The consists five modules: SUMO for modeling, MOVES emissions a 3D...
Freeway ramp merging is a challenging task for an individual vehicle (in particular truck) and critical aspect of traffic management that often leads to bottlenecks accidents. While connected automated (CAV) technology has yielded efficient strategies, most them overlook the differentiation types assume uniform CAV presence. To address this gap, our study focuses on enhancing efficiency heavy-duty trucks in mixed environments. We introduce novel multi-human-in-the-loop (MHuiL) simulation...
Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as revolutionary promoter for the next-generation transportation systems. However, vehicle-based may suffer from limited sensing range and occlusion well low penetration rates connectivity. In this paper, we propose Cyber Mobility Mirror (CMM), real-time traffic surveillance system 3D object reconstruction, to explore potential of roadside sensors enabling CDA real world. The CMM consists six...
Vehicle automation and connectivity bring new opportunities for safe sustainable mobility in urban highway networks. Such are however not directly associated with traffic flow improvements. Research on exploitation of connected automated vehicles (CAVs) toward a more efficient currently remains at theoretical level, and/or based simulation models limited reliability. Furthermore, testing CAVs the real world is still costly very challenging from an implementation perspective. A possible...
Several studies indicate that exposure to pollutants emitted by vehicles is linked several adverse health effects. There are few measurements can be used examine emissions close idling or slowly moving vehicles; such situations occur when people waiting picked up public private vehicles. We report on a field study designed collect concentration data at distances of meters from the tailpipe vehicle: accelerator pedal was controlled simulate and acceleration stop. Analysis using dispersion...
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...