Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Treiber, Martin"'
Autor:
Kulkarni, Mihir Mandar, Chaudhari, Ankit Anil, Srinivasan, Karthik K., Chilukuri, Bhargava Rama, Treiber, Martin, Okhrin, Ostap
Most car-following models were originally developed for lane-based traffic. Over the past two decades, efforts have been made to calibrate car-following models for non-lane-based traffic. However, traffic conditions with varying vehicle dimensions, i
Externí odkaz:
http://arxiv.org/abs/2405.10665
Publikováno v:
Physica A: Statistical Mechanics and its Applications 625, 128990 (2023)
While macroscopic models for single or multi-lane traffic flow are well established, these models are not applicable to the dynamics and characteristics of disordered traffic which is characterized by widely different types of vehicles and no lane di
Externí odkaz:
http://arxiv.org/abs/2310.16904
Autor:
Treiber, Martin, Chaudhari, Ankit Anil
Recently, a fully two-dimensional microscopic traffic flow model for lane-free vehicular traffic flow has been proposed [Physica A, 509, pp. 1-11 (2018)]. In this contribution, we generalize this model to describe any kind of human-driven directed fl
Externí odkaz:
http://arxiv.org/abs/2310.16816
Recent experimental and empirical observations have demonstrated that stochasticity plays a critical role in car following (CF) dynamics. To reproduce the observations, quite a few stochastic CF models have been proposed. However, while calibrating t
Externí odkaz:
http://arxiv.org/abs/2302.04648
While deep reinforcement learning (RL) has been increasingly applied in designing car-following models in the last years, this study aims at investigating the feasibility of RL-based vehicle-following for complex vehicle dynamics and strong environme
Externí odkaz:
http://arxiv.org/abs/2207.03257
Publikováno v:
In Physica A: Statistical Mechanics and its Applications 15 July 2024 646
We propose and validate a novel car following model based on deep reinforcement learning. Our model is trained to maximize externally given reward functions for the free and car-following regimes rather than reproducing existing follower trajectories
Externí odkaz:
http://arxiv.org/abs/2109.14268
Publikováno v:
In Transportation Research Part C February 2024 159
Publikováno v:
In Ocean Engineering 1 August 2023 281
We propose a microscopic decision model for route choice based on discrete choice theory. The correlation of overlapping routes is included in the random portions of the utility explicitly. For computational efficiency, we restrict the choice set to
Externí odkaz:
http://arxiv.org/abs/1811.11295