Connected-Autonomous-Vehicles (CAV) Test Beds
Traffic is one of the largest issues that plague the transportation industries and its consumers. To remedy the issue, we can implement the technological advancements of Connected-Autonomous-Vehicles (CAVs) to improve efficiency and safety of traffic flow while reducing emissions at the same time.
The scenarios that are being researched currently are the stop-and-go wave motions and the traffic light eco speed. The stop-and-go wave motions are created through traffic where the shockwaves travel backward.
The ability to implement the CAVs to this scenario will have an overall positive effect as the CAVs will be able to adjust their own speeds and distances. The traffic light eco speed will allow the vehicle to maintain a speed within the speed limit allowing the vehicle to pass the traffic light without stopping.
The CAV will be able to communicate with the infrastructure, in this case, the traffic light, allowing the CAV to grasp the situation and adjust accordingly. The future of transportation will dramatically change, in a positive manner, when the CAVs will be driven on the roads.
Connected Vehicle: The Future of Transportation, by United States Department of Transportation
Concept Design Overview
Urban Multi-Sensor System Project
Urban Multi-Sensor System project focuses on monitoring city areas' health data and analyzing potential impacts of environmental factors and hazard.
Chosen sensing elements include:
- Traffic Count
- Noise Levels
- Gas Levels
To collect data, multi-sensors are deployed to sense the research variables in the surrounding areas. The data is wirelessly transmitted to the server for modeling and analysis. Future development includes deploying sensing stations to expand coverage area.
Wireless Transmission of collected sensor data to server
Station Module Concept
Project Poster at 2nd Annual Sikand Faculty Endowment Symposium at California State University, Los Angeles, February 2018
Digital Media, Social Campaigns, and Fake News: Mathematical Modeling and Control Methods
The role of information spread and the impact it has on societies in the modern world cannot be understated. In the age of mass communication, digital misinformation, and social media, the importance of understanding and developing control mechanisms for information spread are doubly necessary.
While traditional information spread has been examined in detail from a variety of angles over the decades, little attention has been given to the relatively recent phenomena of the super-fast spread of information via social media and the rise and impact of “fake news” within said information networks.
In this project, several traditional dynamic models are presented, built upon, and re-framed in the modern context of social media information spread using differential equations.
A new model is proposed to address networks and sets of adjacent networks in which information learned and spread is highly polarized, contentious, or unverified.