Multi-Task Weakly Supervised Learning for Origin–Destination Travel Time Estimation
Travel time estimation from GPS trips is of great importance to order duration, ridesharing,
taxi dispatching, etc. However, the dense trajectory is not always available due to the …
taxi dispatching, etc. However, the dense trajectory is not always available due to the …
Dynamic Tolling in Arc-based Traffic Assignment Models
Tolling in traffic networks offers a popular measure to minimize overall congestion. Existing
toll designs primarily focus on congestion in route-based traffic assignment models (TAMs) …
toll designs primarily focus on congestion in route-based traffic assignment models (TAMs) …
[PDF][PDF] A Learning Approach to Complex Contagion Influence Maximization
Influence maximization (IM) aims to find a set of seed nodes in a social network that
maximizes the influence spread. While most IM problems focus on classical influence …
maximizes the influence spread. While most IM problems focus on classical influence …
Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems
Y Rui, Y Zhao, W Lu, C Wang - Sensors, 2023 - mdpi.com
The deployment of Electronic Toll Collection (ETC) gantry systems marks a transformative
advancement in the journey toward an interconnected and intelligent highway traffic …
advancement in the journey toward an interconnected and intelligent highway traffic …
A Data-driven Pricing Scheme for Optimal Routing through Artificial Currencies
D van de Sanden, M Schoukens, M Salazar - IFAC-PapersOnLine, 2023 - Elsevier
Mobility systems often suffer from a high price of anarchy due to the uncontrolled behavior of
selfish users. This may result in societal costs that are significantly higher compared to what …
selfish users. This may result in societal costs that are significantly higher compared to what …
Algorithm Design for Safe and Efficient Societal-Scale Navigation
CY Chiu - 2023 - escholarship.org
In modern urban centers, traffic networks increasingly experience higher densities of both
human-operated and self-driving vehicles. Unfortunately, high traffic loads can increase the …
human-operated and self-driving vehicles. Unfortunately, high traffic loads can increase the …
[PDF][PDF] RouteChoiceEnv: a Route Choice Library for Multiagent Reinforcement Learning
ABSTRACT Multiagent Reinforcement Learning (MARL) has been successfully applied as a
framework for solving distributed traffic optimization problems. Route choice is a challenging …
framework for solving distributed traffic optimization problems. Route choice is a challenging …