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Open AccessArticle

A Distributed Scheme for the Taxi Cruising Route Recommendation Problem Using a Graph Neural Network

by Ying Li, Yongsheng Huang, Zhipeng Liu and Bin Zhang

Electronics 2024, 13(3), 574; https://doi.org/10.3390/electronics13030574 - 31 Jan 2024

Cited by 2 | Viewed by 1807

Despite considerable research efforts being devoted to the taxi cruising route recommendation (TCRR) problem, existing studies still have some shortcomings. To begin with, the competition and collaboration between taxis are not sufficiently taken into account. Furthermore, the TCRR is heavily reliant on potential taxi demand, which is time-variant and difficult to accurately predict due to the underlying spatiotemporal correlation and dynamic traffic patterns. Moreover, the consideration of competition and cooperation among taxis increases the complexity of the TCRR problem, making conventional centralized algorithms computationally expensive. In this paper, we first formulate TCRR as a biobjective optimization problem to balance the collaboration and competition between taxis. Subsequently, we forecast short-term taxi demand using the proposed long-short-term-memory-based graph convolutional network (LSTM-GCN), which considers diverse factors such as road topology, points of interest (POIs), and multiple time-scale features. Lastly, we propose a distributed algorithm based on a Lagrange dual decomposition. The experimental and simulation results demonstrate that our TCRR scheme performs better than any other counterpart, (i) resulting in a

3 %

reduction in idle taxis per hour, (ii) performing four times faster than the centralized algorithms to obtain the optimal solution, and (iii) resulting in a

7 %

increase in average profit. Full article

(This article belongs to the Special Issue Connected and Autonomous Vehicles in Mixed Traffic Systems)

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13 pages, 2131 KB

Open AccessArticle

Distinct Hormone Signalling-Modulation Activities Characterize Two Maize Endosperm-Specific Type-A Response Regulators

by Joaquín Royo, Luís M. Muñiz, Elisa Gómez, Ana M. Añazco-Guenkova and Gregorio Hueros

Plants 2022, 11(15), 1992; https://doi.org/10.3390/plants11151992 - 30 Jul 2022

Cited by 2 | Viewed by 2251

Abstract

ZmTCRR1 and 2 are type-A response regulators expressed in the maize endosperm transfer cells (TC). While type-B response regulators transcriptionally control canonical type-A response regulators, as part of the cytokinin signal transduction mechanism, the ZmTCRRs are regulated by ZmMRP1, a master regulator of TC identity. In addition, the corresponding proteins are not detected in the TC, accumulating in the inner endosperm cells instead. These features suggest these molecules are not involved in classical, cell-autonomous, cytokinin signalling pathways. Using transgenic Arabidopsis plants ectopically expressing these genes, we have shown that ZmTCRR1 and 2 can modulate auxin and cytokinin signalling, respectively. In Arabidopsis, the ectopic expression of ZmTCRR2 blocked, almost completely, cytokinin perception. Given the conservation of these signalling pathways at the molecular level, our results suggest that the ZmTCRRs modulate cytokinin and auxin perception in the inner endosperm cells. Full article

(This article belongs to the Section Plant Molecular Biology)

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