Understanding the uncertainty of traffic time prediction impacts on parking lot reservation in logistics centers

Rui Feng, Ankun Ma, Zhijia Jing, Xiaoning Gu, Pengfei Dang and Baozhen Yao ()
Additional contact information
Rui Feng: Dalian University of Technology
Ankun Ma: Dalian University of Technology
Zhijia Jing: Dalian University of Technology
Xiaoning Gu: Dalian University of Technology
Pengfei Dang: Dalian University of Technology
Baozhen Yao: Dalian University of Technology

Annals of Operations Research, 2024, vol. 343, issue 3, No 6, 1045-1067

Abstract: Abstract Accurate travel time information is essential for logistics vehicles to reserve the most suitable parking lot in logistics centers. The purpose of this study is to explore how the uncertainty of traffic time prediction affects parking lot reservation near logistics centers. A hybrid model integrating convolutional long short-term memory network and attention mechanism is proposed to provide the reliable information for travel time prediction intervals. Furthermore, a reliability-based parking lot reservation model is developed by explicitly considering logistics vehicles’ time probability. Several benchmark models are compared with the proposed traffic speed prediction model. The performance of the parking lot reservation model is illustrated by travel behavior questionnaire data and global positioning system data of collected from Beijing, China. The results illustrate that the proposed prediction model exhibits a better accuracy than benchmark models. Moreover, it is found that travel time prediction interval can improve the reliability and stability of travel time, and provide a reliable time information for the parking lot reservation.

Keywords: Parking lot reservation; Travel time prediction interval; Traffic speed; Convolutional long short-term memory; Attention mechanism; Multinomial logit model (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-022-04734-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:343:y:2024:i:3:d:10.1007_s10479-022-04734-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-022-04734-z

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().