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CMetric: A Driving Behavior Measure Using Centrality Functions [article]

Rohan Chandra, Uttaran Bhattacharya, Trisha Mittal, Aniket Bera, Dinesh Manocha
2020 arXiv   pre-print
We present a new measure, CMetric, to classify driver behaviors using centrality functions.  ...  CMetric is used to compute the probability of a vehicle executing a driving style, as well as the intensity used to execute the style.  ...  part of future work, we plan to use the CMetric measure for improving realtime planning and decision-making. VII.  ... 
arXiv:2003.04424v2 fatcat:uinlimtnxjdbzi2b4stv42w56i

B-GAP: Behavior-Rich Simulation and Navigation for Autonomous Driving [article]

Angelos Mavrogiannis, Rohan Chandra, Dinesh Manocha
2022 arXiv   pre-print
We then use the enriched simulator to train a deep reinforcement learning (DRL) policy that consists of a set of high-level vehicle control commands and use this policy at test time to perform local navigation  ...  We generate these trajectories with the help of a driver behavior modeling algorithm.  ...  These centrality measures are defined in [14] (See section III-C). Each function measures a different property of a vertex.  ... 
arXiv:2011.03748v6 fatcat:etysioulnjgo3lkatwdedqldja

Game-Theoretic Planning for Autonomous Driving among Risk-Aware Human Drivers [article]

Rohan Chandra, Mingyu Wang, Mac Schwager, Dinesh Manocha
2022 arXiv   pre-print
In our approach, we learn a mapping from a data-driven human driver behavior model called the CMetric to a driver's entropic risk preference.  ...  Our approach takes into account the wide range of human driver behaviors on the road, from aggressive maneuvers like speeding and overtaking, to conservative traits like driving slowly and conforming to  ...  centrality functions [37] represented by Φ : G → R.  ... 
arXiv:2205.00562v1 fatcat:xw6f4xlh3nahlesoo7dvhljrtu

GamePlan: Game-Theoretic Multi-Agent Planning with Human Drivers at Intersections, Roundabouts, and Merging [article]

Rohan Chandra, Dinesh Manocha
2022 arXiv   pre-print
Our algorithm uses game theory to develop a new auction, called GamePlan, that directly determines the optimal action for each agent based on their driving style (which is observable via commonly available  ...  techniques including economic auctions, time-based auctions (first-in first-out), and random bidding and show that each of these methods result in collisions among agents when taking into account driver behavior  ...  Our formulation, GAMEPLAN, differs in this regard wherein we use a novel online driving behavior-based bidding strategy using the CMetric model [5] .  ... 
arXiv:2109.01896v5 fatcat:katwxrsulbdktndcb7ejfvnn4u

Motion of charged particles around a magnetized/electrified black hole

Yen-Kheng Lim
2015 Physical Review D  
The case of the magnetic Ernst metric contains a limit which reduces to the Melvin magnetic universe.  ...  We find that the electric field strength must be below a certain charge-dependent critical value for these orbits to be stable.  ...  Figure 2b shows a similar solution for a charged particle of e = 1, demonstrating the behavior of a driven oscillator with driving frequency given by Ω.  ... 
doi:10.1103/physrevd.91.024048 fatcat:wwdy7aknxjckbcpu36ztqrqzte

Black Hole Solutions and Pair Creation of Black Holes in Three, Four and Higher Dimensional Spacetimes [article]

Oscar J. C. Dias
2004 arXiv   pre-print
This later solutions are then used to study in detail the quantum process of black hole pair creation in an external field.  ...  Black holes, first found as solutions of Einstein's General Relativity, are important in astrophysics, since they result from the gravitational collapse of a massive star or a cluster of stars, and in  ...  One wants to use an action for which it is natural to fix the boundary data on Σ specified in (9.67).  ... 
arXiv:hep-th/0410294v1 fatcat:zyizj2k4t5d45dxhcfsxfq6kzm