A dynamic and deadline-oriented road pricing mechanism for urban traffic management

J Jin, X Zhu, B Wu, J Zhang… - Tsinghua Science and …, 2021 - ieeexplore.ieee.org
Road pricing is an urban traffic management mechanism to reduce traffic congestion.
Currently, most of the road pricing systems based on predefined charging tolls fail to …

Pay your trip for traffic congestion: Dynamic pricing in traffic-aware road networks

L Chen, S Shang, B Yao, J Li - Proceedings of the AAAI Conference on …, 2020 - aaai.org
Pricing is essential in optimizing transportation resource allocation. Congestion pricing is
widely used to reduce urban traffic congestion. We propose and investigate a novel …

Deep reinforcement learning algorithm for dynamic pricing of express lanes with multiple access locations

V Pandey, E Wang, SD Boyles - Transportation Research Part C: Emerging …, 2020 - Elsevier
This article develops a deep reinforcement learning (Deep-RL) framework for dynamic
pricing on managed lanes with multiple access locations and heterogeneity in travelers' …

Ctrl: Cooperative traffic tolling via reinforcement learning

Y Wang, H Jin, G Zheng - Proceedings of the 31st ACM International …, 2022 - dl.acm.org
People have been working long to tackle the traffic congestion problem. Among the different
measures, traffic tolling has been recognized as an effective way to mitigate citywide …

[PDF][PDF] Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks.

W Qiu, H Chen, B An - IJCAI, 2019 - ijcai.org
Over the past decades, Electronic Toll Collection (ETC) systems have been proved the
capability of alleviating traffic congestion in urban areas. Dynamic Electronic Toll Collection …

Dwara: A deep learning-based dynamic toll pricing scheme for intelligent transportation systems

A Shukla, P Bhattacharya, S Tanwar… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
In Internet-of-Vehicles (IoV) ecosystems, intelligent toll gates (ITGs) connect nearby
metropolitan cities through smart highways. At ITGs, existing solutions integrate blockchain …

Online learning for traffic routing under unknown preferences

D Jalota, K Gopalakrishnan, N Azizan, R Johari… - arXiv preprint arXiv …, 2022 - arxiv.org
In transportation networks, users typically choose routes in a decentralized and self-
interested manner to minimize their individual travel costs, which, in practice, often results in …

Optimal dynamic pricing strategies for high-occupancy/toll lanes

Y Lou, Y Yin, JA Laval - Transportation Research Part C: Emerging …, 2011 - Elsevier
This paper proposes a self-learning approach to determine optimal pricing strategies for
high-occupancy/toll lane operations. The approach learns recursively motorists' willingness …

Proactive and robust dynamic pricing strategies for high-occupancy-toll (HOT) lanes

D Michalaka, Y Lou, Y Yin - 2011 - trid.trb.org
Congestion pricing has been promoted by economists and transportation researchers as
one of the most efficient means to mitigate traffic congestion. When tolls implemented on …

A bi-level framework for pricing of high-occupancy toll lanes

K Jang, MK Song, K Choi, DK Kim - Transport, 2014 - Taylor & Francis
As a freeway operational management strategy, High-Occupancy Toll (HOT) lanes have
been deployed to manage the demand for High-Occupancy Vehicle (HOV) lanes by …