Logistics Sprawl and Artificial Intelligence Revolving Urban Freight Transport DOI
Manal El Yadari, Fouad Jawab,

Imane Moufad

et al.

Advances in logistics, operations, and management science book series, Journal Year: 2024, Volume and Issue: unknown, P. 191 - 244

Published: Dec. 20, 2024

Artificial intelligence has made great strides in various fields, especially improving logistics operations and freight transportation. This chapter aims to highlight the importance of applying AI manage sprawl phenomenon. The research focused on analyzing impact use performance urban transport under sprawling conditions. To achieve this, authors carried out a literature review explore different categories including machine learning, deep natural language processing, visual data reinforcement learning (RL), specialized algorithms, optimise activities within context.

Language: Английский

Explainable artificial intelligence in transport Logistics: Risk analysis for road accidents DOI
Ismail Abdulrashid, Reza Zanjirani Farahani,

Shamkhal Mammadov

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 186, P. 103563 - 103563

Published: April 30, 2024

Language: Английский

Citations

13

Inferring freeway traffic volume with spatial interaction enhanced betweenness centrality DOI Creative Commons
Beibei Zhang, Shifen Cheng, Peixiao Wang

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2024, Volume and Issue: 129, P. 103818 - 103818

Published: April 6, 2024

Freeway traffic volume is strongly correlated with the intensity of regional socioeconomic spatial interactions and road network structure. Although existing studies have proposed indicators betweenness centrality (BC) integrated into interactions, socio-economic drivers freeway formation been neglected. More importantly, not established a non-linear response relationship among BC, city volume, which severely limits comprehensive quantification role flow drivers. Therefore, this study proposes inference method that integrates interaction to enhance BC. First, factors origin destination cities are incorporated BC indicator create an enhanced (ODBC), quantifies strength between cities. Second, machine learning approach used develop ODBC accurately infer volume. Finally, utilizing SHapley additive explanation approach, vectors intercity quantified. Experiments conducted on data from toll stations demonstrate surpasses baseline based weighted by considering only potential or attractiveness, improvement in R2 14%, 4.2%, 4%, maximum reduction RMSE 40%, 24.5%, 26%. The yields higher accuracy for unknown segments easily interpretable.

Language: Английский

Citations

6

Quantifying city freight mobility segregation associated with truck multi-tours behavior DOI
Yitao Yang, Yan Chen,

Ying-Yue Lv

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 113, P. 105699 - 105699

Published: Aug. 3, 2024

Language: Английский

Citations

4

Prediction greenhouse gas emissions from road freight flow in South Korea for sustainable transportation planning DOI Creative Commons
Hoseok Nam, Jihye Byun, Hyungseok Nam

et al.

Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41937 - e41937

Published: Jan. 1, 2025

Road freight modeling was conducted to project flow and greenhouse gas (GHG) emissions in 16 administrative regions of South Korea through 2050. Origin-destination matrices were constructed using a gravity model for each region. The covered seven product categories both inter-regional intra-regional transportation validated 2017 data. total future is projected increase from 1399 million tons 2019 1701 by 2035. However, after peaking 2035, it expected decline 1618 2050, indicating that population will impact demand, causing reduction despite continued economic growth. GHG are slightly decrease 19.0 kgCO2eq. 2025 18.6 followed steeper 15.5 This attributed long-term reductions emission factors. Changes between 2050 be more pronounced within five the capital extended areas, which account approximately 50.3 % due concentration. As result, these contribute 26.5 potential. minimum growth rates required maintain same volume as 2035 estimated at 5 2040, 13 2045, 26

Language: Английский

Citations

0

Assessing the resilience of urban truck transport networks under the COVID-19 pandemic: A case study of China DOI
Yitao Yang, Erjian Liu, Yan Chen

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 197, P. 104087 - 104087

Published: March 20, 2025

Language: Английский

Citations

0

Identifying the critical features influencing warehouse rental prices and their nonlinear associations: A spatial machine learning approach DOI
Nannan He, Sijing Liu, Xinyu Cao

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 197, P. 104092 - 104092

Published: March 28, 2025

Language: Английский

Citations

0

Deep Learning Empowered Intermodal Path Optimization in Logistics: Deep Shortest Approach DOI Open Access
Safi̇ye Turgay,

Mert Kadem Omeroglu,

S.S. Erdogan

et al.

WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS, Journal Year: 2025, Volume and Issue: 22, P. 832 - 844

Published: May 2, 2025

This is particularly important in logistics, where path planning critical for adequate transport and distribution processes. That why classical approaches like Dijkstra’s algorithm have been essential, though they are too weak to handle the complications typical of actual logistics networks. To this end, paper proposes a new framework called DeepShortest, which improves optimization process using deep learning methods. DeepShortest uses neural network training flexibility complexity various logistical contexts. Thus, successfully implements within base deliver high result finding shortest most effective paths transporting goods through global chains. In paper, DEEP Define strategy describes how methodologies cast into component approach. addition, real-world case studies substantiate effectiveness advantage compared with previous methods, generally providing stepped-up route performance resource management. an innovative approach solving problems creative solution issues today’s supply chain. With their capacity work areas conditions change often suggest optimal delivery vehicles, presents itself as invaluable that could drastically transform worldwide.

Language: Английский

Citations

0

Spatiotemporal dynamics and determining factors of intercity mobility: A comparison between holidays and non-holidays in China DOI
Weijie Yu,

De Wen Zhao,

Xuedong Hua

et al.

Cities, Journal Year: 2024, Volume and Issue: 153, P. 105306 - 105306

Published: July 27, 2024

Language: Английский

Citations

3

On the calibration and improvement of human mobility models in intercity transportation system DOI
Weijie Yu, Haosong Wen, Wei Wang

et al.

Physica A Statistical Mechanics and its Applications, Journal Year: 2024, Volume and Issue: unknown, P. 130116 - 130116

Published: Sept. 1, 2024

Language: Английский

Citations

3

Applying masked language model for transport mode choice behavior prediction DOI

Ying Yang,

Wei Zhang, Hongyi Lin

et al.

Transportation Research Part A Policy and Practice, Journal Year: 2024, Volume and Issue: 184, P. 104074 - 104074

Published: April 23, 2024

Language: Английский

Citations

2