[HTML][HTML] How machine learning informs ride-hailing services: A survey
In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …
urban transportation system, which not only provide significant ease for residents' travel …
How generative adversarial networks promote the development of intelligent transportation systems: A survey
In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
The vehicle dispatching system is one of the most critical problems in online ride-hailing
platforms, which requires adapting the operation and management strategy to the dynamics …
platforms, which requires adapting the operation and management strategy to the dynamics …
[HTML][HTML] Multivariate time-series blood donation/demand forecasting for resilient supply chain management during COVID-19 pandemic
M Shokouhifar, M Ranjbarimesan - Cleaner Logistics and Supply Chain, 2022 - Elsevier
COVID-19 has caused negative impacts on blood supply chain management, due to
uncertain supply/demand and logistical disruptions. In the early weeks following the COVID …
uncertain supply/demand and logistical disruptions. In the early weeks following the COVID …
[HTML][HTML] GOPS: A general optimal control problem solver for autonomous driving and industrial control applications
Solving optimal control problems serves as the basic demand of industrial control tasks.
Existing methods like model predictive control often suffer from heavy online computational …
Existing methods like model predictive control often suffer from heavy online computational …
A graph neural network (GNN)-based approach for real-time estimation of traffic speed in sustainable smart cities
Planning effective routes and monitoring vehicle traffic are essential for creating sustainable
smart cities. Accurate speed prediction is a key component of these efforts, as it aids in …
smart cities. Accurate speed prediction is a key component of these efforts, as it aids in …
A two-stage chance constrained stochastic programming model for emergency supply distribution considering dynamic uncertainty
This paper presents a comprehensive approach to addressing the challenges of designing a
reliable emergency logistics network under the dynamic uncertainty of natural disasters. The …
reliable emergency logistics network under the dynamic uncertainty of natural disasters. The …
[HTML][HTML] Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review
Abstract Automatic Identification System (AIS) data holds immense research value in the
maritime industry because of its massive scale and the ability to reveal the spatial–temporal …
maritime industry because of its massive scale and the ability to reveal the spatial–temporal …
Car-following models for human-driven vehicles and autonomous vehicles: A systematic review
The focus of car-following models is to analyze the microscopic characteristics of traffic
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
[HTML][HTML] Road condition monitoring using unsupervised learning based bus trajectory processing
The road infrastructure maintenance is crucial for hassle-free transportation. The proposed
work leverages the dense connectivity of public transportation buses for road condition …
work leverages the dense connectivity of public transportation buses for road condition …