Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Automotive (2)
- Adaptive Cruise Control (1)
- Advanced driver assistance (1)
- Automation (1)
- Autonomous driving (1)
-
- Autopilot (1)
- Bidirectional charging systems (1)
- Cyber–physical systems (1)
- Driving simulator (1)
- E-mobility (1)
- Electric vehicles (1)
- Engineering (1)
- Formal methods (1)
- GRU (1)
- Human-robot interaction (1)
- Human-robot interaction (HRI) (1)
- Industrial engineering (1)
- Intelligent vehicles (1)
- Inverse reinforcement learning (1)
- LSTM (1)
- Level 3 automated vehicle (1)
- Machine learning (1)
- Machine-to-machine communications (1)
- Machinelearning (1)
- Mobility Forecasting (1)
- Model checking (1)
- Modeling and Simulation (1)
- Motion planning (1)
- Multi-robot system (1)
- Post takeover performance (1)
- Publication
- Publication Type
Articles 1 - 9 of 9
Full-Text Articles in Automotive Engineering
Machine Learning Approach To Investigate Ev Battery Characteristics, Shayan Falahatdoost
Machine Learning Approach To Investigate Ev Battery Characteristics, Shayan Falahatdoost
Major Papers
The main factor influencing an electric vehicle’s range is its battery. Battery electric vehicles experience driving range reduction in low temperatures. This range reduction results from the heating demand for the cabin and recuperation limits by the braking system. Due to the lack of an internal combustion engine-style heat source, electric vehicles' heating system demands a significant amount of energy. This energy is supplied by the battery and results in driving range reduction. Moreover, Due to the battery's low temperature in cold weather, the charging process through recuperation is limited. This limitation of recuperation is caused by the low reaction …
An Overview Of Bidirectional Electric Vehicles Charging System As A Vehicle To Anything (V2x) Under Cyber–Physical Power System (Cpps), Onur Elma, Umit Cali, Murat Kuzlu
An Overview Of Bidirectional Electric Vehicles Charging System As A Vehicle To Anything (V2x) Under Cyber–Physical Power System (Cpps), Onur Elma, Umit Cali, Murat Kuzlu
Engineering Technology Faculty Publications
Nowadays, EVs are rapidly increasing in popularity, and are accepted as the vehicles of the future all over the world. The most important components are their battery and charging systems. The energy capacity of EVs’ batteries has a significant potential to supply different energy requirements. Therefore, EVs must be designed in accordance with bidirectional power flow, and Electric Vehicle Supply Equipment (EVSE) should be upgraded as Electric Vehicle Power Exchange Equipment (EVPE). This power exchange infrastructure can be called Vehicle-to-Anything (V2X). V2X will also be the key solution for energy grids of the future that will turn into a much …
Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng
Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng
All Dissertations
Multi-robot systems (MRS) can accomplish more complex tasks with two or more robots and have produced a broad set of applications. The presence of a human operator in an MRS can guarantee the safety of the task performing, but the human operators can be subject to heavier stress and cognitive workload in collaboration with the MRS than the single robot. It is significant for the MRS to have the provable correct task and motion planning solution for a complex task. That can reduce the human workload during supervising the task and improve the reliability of human-MRS collaboration. This dissertation relies …
Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt
Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt
Electronic Theses and Dissertations
Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …
Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy
Automotive Sensor Fusion Systems For Traffic Aware Adaptive Cruise Control, Jonah T. Gandy
Theses and Dissertations
The autonomous driving (AD) industry is advancing at a rapid pace. New sensing technology for tracking vehicles, controlling vehicle behavior, and communicating with infrastructure are being added to commercial vehicles. These new automotive technologies reduce on road fatalities, improve ride quality, and improve vehicle fuel economy. This research explores two types of automotive sensor fusion systems: a novel radar/camera sensor fusion system using a long shortterm memory (LSTM) neural network (NN) to perform data fusion improving tracking capabilities in a simulated environment and a traditional radar/camera sensor fusion system that is deployed in Mississippi State’s entry in the EcoCAR Mobility …
The Effects Of Ecological Simulation For Ground Vehicle Mobility Forecasting, Christopher R. Hudson
The Effects Of Ecological Simulation For Ground Vehicle Mobility Forecasting, Christopher R. Hudson
Theses and Dissertations
Unmanned ground vehicles (UGV) are being explored for use in military domains. Military UGVs operate in complex off-road environments. Vehicle mobility forecasting plays an important role in understanding how and where a vehicle can operate. Traditional mobility forecasting has been done using an analytical model known as the NATO Reference Mobility Model (NRMM). There has been a push to extend the forecasting capabilities of NRMM by integrating more simulation methods. Simulation enables the repeated testing of UGVs in scenarios that would be difficult or dangerous to study in real world testing. To accurately capture UGV performance in simulation, the operating …
Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li
All Dissertations
By virtue of vehicular connectivity and automation, the vehicle becomes increasingly intelligent and self-driving capable. However, no matter what automation level the vehicle can achieve, humans will still be in the loop despite their roles. First, considering the manual driving car as a disturbance to the connected and autonomous vehicles (CAVs), a novel string stability is proposed for mixed traffic platoons consisting of both autonomous and manual driving cars to guarantee acceptable motion fluctuation and platoon safety. Furthermore, humans are naturally considered as the rider in the passenger vehicle. A human-centered cooperative adaptive cruise control (CACC) is designed to improve …
A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert
A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert
Student Research
Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …
Developing Takeover Request Warning System To Improve Takeover Time And Post-Takeover Performance In Level 3 Automated Drivin, Niloy Talukder
Developing Takeover Request Warning System To Improve Takeover Time And Post-Takeover Performance In Level 3 Automated Drivin, Niloy Talukder
Electronic Theses and Dissertations
The automotive industry is shifting towards partial (level 3) or fully automated vehicles. An important research question in level 3 automated driving is how quickly drivers can take over the vehicle control in response to a critical event. In this regard, this study develops an integrated takeover request (TOR) system which provides visual and auditorial TOR warning in both vehicle interface and personal portable device (e.g., tablet). The study also evaluated the effectiveness of the integrated TOR system in reducing the takeover time and improving post-takeover performance. For these purposes, 44 drivers participated in the driving simulator experiment where they …