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- Automated Driving (1)
- Autonomous Vehicles (1)
- Autonomous driving (1)
- CACC (1)
- Connected Vehicles (1)
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- DSRC (1)
- Decision Process (1)
- Deep Reinforcement Learning (1)
- Formal methods (1)
- Game Theory (1)
- Human-robot interaction (1)
- Human-robot interaction (HRI) (1)
- Inverse reinforcement learning (1)
- Model checking (1)
- Monte Carlo Tree Search (1)
- Motion planning (1)
- Multi-robot system (1)
- Simulation (1)
- Trust model (1)
- V2X (1)
- VANET (1)
- Vehicle-to-vehicle (V2V) communication (1)
Articles 1 - 4 of 4
Full-Text Articles in Computer Engineering
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim
All Dissertations
In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …
Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi
All Dissertations
Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …
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 …
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 …