2 citations · 5 across the 6 of their papers we have counts for
10 papers
Sensitivity Analysis of Passenger Behavioral Model for Dynamic Pricing of Shared Mobility on Demand
Vineet Jagadeesan Nair, Yue Guan, Anuradha M. Annaswamy +2
This paper provides a framework to quantify the sensitivity associated with behavioral models based on Cumulative Prospect Theory (CPT). These are used to design dynamic pricing st…
Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning
Songan Zhang, Lu Wen, Huei Peng +1
It is essential for an automated vehicle in the field to perform discretionary lane changes with appropriate roadmanship - driving safely and efficiently without annoying or endang…
Safe Reinforcement Learning Using Robust Action Governor
Yutong Li, Nan Li, H. Eric Tseng +3
Reinforcement Learning (RL) is essentially a trial-and-error learning procedure which may cause unsafe behavior during the exploration-and-exploitation process. This hinders the ap…
Action Governor for Discrete-Time Linear Systems with Non-Convex Constraints
Nan Li, Kyoungseok Han, Anouck Girard +3
This paper introduces an add-on, supervisory scheme, referred to as Action Governor (AG), for discrete-time linear systems to enforce exclusion-zone avoidance requirements. It does…
A Game Theoretic Approach for Parking Spot Search with Limited Parking Lot Information
Yutong Li, Nan Li, H. Eric Tseng +4
We propose a game theoretic approach to address the problem of searching for available parking spots in a parking lot and picking the ``optimal'' one to park. The approach exploits…
Learning-Based Risk-Averse Model Predictive Control for Adaptive Cruise Control with Stochastic Driver Models
Mathijs Schuurmans, Alexander Katriniok, Hongtei Eric Tseng +1
We propose a learning-based, distributionally robust model predictive control approach towards the design of adaptive cruise control (ACC) systems. We model the preceding vehicle a…