Reinforcement learning approach for coordinated passenger inflow control of urban rail transit in peak hours

Z Jiang, W Fan, W Liu, B Zhu, J Gu - Transportation Research Part C …, 2018 - Elsevier
In peak hours, when the limited transportation capacity of urban rail transit is not adequate
enough to meet the travel demands, the density of the passengers waiting at the platform …

Optimize taxi driving strategies based on reinforcement learning

Y Gao, D Jiang, Y Xu - International Journal of Geographical …, 2018 - Taylor & Francis
The efficiency of taxi services in big cities influences not only the convenience of peoples'
travel but also urban traffic and profits for taxi drivers. To balance the demands and supplies …

An adaptive decision-making method with fuzzy Bayesian reinforcement learning for robot soccer

H Shi, Z Lin, S Zhang, X Li, KS Hwang - Information Sciences, 2018 - Elsevier
A robot soccer system is a typical complex time-sequence decision-making system.
Problems of uncertain knowledge representation and complex models always exist in robot …

Application and evaluation of the reinforcement learning approach to eco-driving at intersections under infrastructure-to-vehicle communications

J Shi, F Qiao, Q Li, L Yu, Y Hu - Transportation Research …, 2018 - journals.sagepub.com
Eco-driving behavior is able to improve vehicles' fuel consumption efficiency and minimize
exhaust emissions, especially with the presence of infrastructure-to-vehicle (I2V) …

[HTML][HTML] An extensive review on data mining methods and clustering models for intelligent transportation system

S Anand, P Padmanabham, A Govardhan… - Journal of Intelligent …, 2018 - degruyter.com
Data mining techniques support numerous applications of intelligent transportation systems
(ITSs). This paper critically reviews various data mining techniques for achieving trip …

A data-driven approach for autonomous motion planning and control in off-road driving scenarios

H Rastgoftar, B Zhang, EM Atkins - 2018 Annual american …, 2018 - ieeexplore.ieee.org
This paper presents a novel data-driven approach for vehicle motion planning and control in
off-road driving scenarios. For autonomous off-road driving, environmental conditions impact …

Market-level effects of firm-level adaptation and intermediation in networked markets of fresh foods: A case study in Colombia

G Mejía, C García-Díaz - Agricultural Systems, 2018 - Elsevier
This paper presents a multi-agent simulation that studies market competition in a multi-stage
negotiation with both direct sales and intermediation, in the presence of cost heterogeneity …

Simulating and analyzing the effect on travel behavior of residential relocation and corresponding traffic demand management strategies

H Ding, M Yang, W Wang, C Xu - KSCE Journal of Civil Engineering, 2018 - Springer
Triggered by rapid urban expansion and fast population growth, a progressive residential
relocation has occurred in most cities and its impacts on travel behavior have been …

Personalized optimal bicycle trip planning based on Q-learning algorithm

Y Chen, W Yan, C Li, Y Huang… - 2018 IEEE Wireless …, 2018 - ieeexplore.ieee.org
Traveling by bicycle has become a rising trend recently for its convenience and flexibility,
which calls for considerate bicycle trip planning schemes. While research for traditional trip …

Learning to gather without communication

EME Mhamdi, R Guerraoui, A Maurer… - arXiv preprint arXiv …, 2018 - arxiv.org
A standard belief on emerging collective behavior is that it emerges from simple individual
rules. Most of the mathematical research on such collective behavior starts from imperative …