Our overarching goal is to discover new characteristics of Vehicle-to-Everything communication and improve transportation safety by implementing intelligent devices.
Soft robotics is a new field of engineering ready to be explored, because of its use of unconventional materials it can withstand copious amounts of stress which makes it ideal for applications involving vehicular accidents. In this groundbreaking work, we attempt to integrate soft robotics technologies with Vehicle-to-Everything (V2X) communications. Specifically, we introduce the preliminary planning stages for creating a novel V2X rollover antenna that can reduce road deaths and provide more reliable accident data. An up-right roof mounted antenna could be damaged during a roll-over accident thereby severely limiting the V2X radio from providing reliable warning signals to other V2X equipped vehicles or infrastructure. Our proposed soft robotic V2X antenna will deploy from beneath the car using pneumatic actuation and extend up until it is able to send a reliable signal. To the best of our knowledge, this is the first attempt within the literature to address a rollover accident use-case for V2X communications.
Wi-Fi has been in existence since 1998 providing an increase in the amount of data transmitted and generated by machines. With the growing market demand for network bandwidth, it will make it nearly impossible for typical radio frequency (RF) technologies like Wi-Fi to supply the resources needed for the data transmission. As a complementary solution, Li-Fi was introduced in 2011 as a method of data transfer through the use light of light sources. Li-Fi employs the use of visible light spectrum which has 1000 more times the bandwidth of typical RF spectrums. This study investigates the distance to which this method of data transmission can be done on a simple LI-Fi transmission system. We use a basic LED to send signals to a photoresistor exploring the basis of using different lenses to further increase the distance of reception. In lab observations indicate that data transmission occurs after the light source was made to pass through different lenses. The result of this can be used as a starting point to determine how far a Li-Fi data packet can be sniffed without loss of packet information and increasing the distance of transmission.
Vehicle-to-Everything (V2X) communications is a burgeoning technology that will enable safer, greener, and more productive usage of roadways. In the V2X paradigm, all equipped vehicles and infrastructure can communicate with each other in real-time. By utilizing V2X communications as an Internet-of-Things gateway, a sensor array installed under roadways, allows real-time monitoring of road conditions which increases overall road safety and road maintenance cost. In our research, we have utilized the WAVE Short Message Protocol (WSMP) as the means of communication between roadway sensors and roadside gateways. We implemented the first proof-of-concept using this protocol, with a single-board computer to format sensor information into a WSMP packet and send this information via radio transmission across multiple hops to V2X gateway which can then relay the road temperature information to a remote server. We envision the packet format to be all purpose-built for V2X communication, making it the optimal choice for networking transportation information.
Vehicle-to-Everything communications (V2X) is gaining additional ground as an upcoming ad hoc safety network. In V2X, basic safety messages are used for exchanging critical information between vehicles at a set broadcast rate. However, jamming attacks on the safety spectrum could deny V2X radios the ability to save lives on the roadway. This preliminary work analyzes two types of primitive jamming attacks performed on target V2X devices. Lab results reveal that V2X networks are easily susceptible to jamming attacks, due to all V2X standards lacking a requirement to detect/mitigate jamming. To avert this threat and promote safety of life on the roadways, we demonstrate a supervised machine learning model implemented at the baseband chipset could detect and classify the type of jamming attack with outstanding stability and an accuracy of 99.84%.
Intelligent transportation systems (ITS) are being deployed globally to support vehicular safety innovation using wireless communication. The ITS paradigm of vehicle-to-everything communication (V2X) enables vehicles equipped with an on-board unit (OBU) to communicate with a roadside unit (RSU) infrastructure to provide safe intersection movements between similarly equipped vehicles, pedestrians, and animal life. However, the current paradigm relies heavily on the availability of a Global Positioning System (GPS) for ensuring road user safety. In a doomsday scenario where GPS becomes unavailable, collision avoidance services provided through V2X may be rendered unavailable. The proposed solution is to develop a secure and reliable method for V2X nodes to reliably request positioning information from RSUs. The advantages are two-fold: when GPS is offline V2X nodes can continue to receive positioning information for safety applications, and when GPS is online V2X positioning information could be corrected/improved through ground truth positioning verification.
Radio Frequency Identification (RFID) is a well-known technology in wireless communication. It is hypothesized that the capabilities of RFID can be extended by reading an ID number and detecting movement around the reader during the read. Following regulatory standards, this study presents the foundation for a software defined RFID reader that may simultaneously detects and classifies the type of movement during the interrogation operation. A frequency hopping signal in unlicensed 5.8GHz can be analyzed using machine learning to extract a Doppler profile. We effectively collect information about an object through RFID by potentially detecting the speed of the object or classifying its size. This innovation could positively impact multiple industries. A few applications for this technology include: robust security mechanisms for RFID readers enabling reliable supply chains, ticketing speeding cars in the electronic toll lanes to enable safer roads, and enabling safer warehouses such that forklifts equipped with our RFID Doppler reader technology could detect human movement during inventory tracking.