Safety-oriented planning of expressway truck service areas based on driver demand

Wenlong Ding, Yunyun Wang, Pengzi Chu, Feng Chen*, Yongchao Song, Ning Zhang, Dong Lin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
8 Downloads (Pure)

Abstract

The rapid development of the economy has promoted the growth of freight transportation. The truck service areas on expressways, as the main places for truck drivers to rest, play an important role in ensuring the driving safety of trucks. If these service areas are constructed densely or provide a plentiful supply of parking areas, they are costly to construct. However, if the distance between two adjacent truck service areas is very large or the number of truck parking spaces in service areas is small, the supply will fail to meet the parking needs of truck drivers. In this situation, the continuous working time of truck drivers will be longer, and this is likely to cause driver fatigue and even traffic accidents. To address these issues, this paper established a non-linear optimization model for truck service area planning of expressways to optimize truck driving safety. An improved genetic algorithm is proposed to solve the model. A case study of a 215.5-kilometers-length section of the Guang-Kun expressway in China was used to demonstrate the effectiveness of the model and algorithm. As validated by this specific case, the proposed model and solution algorithm can provide an optimal plan for the layout of truck service areas that meet the parking needs of truck drivers while minimizing the service loss rate. The research results of this paper can contribute to the construction of truck service areas and the parking management of trucks on expressways.
Original languageEnglish
Article number976495
Number of pages10
JournalFrontiers in public health
Volume10
DOIs
Publication statusPublished - 2 Aug 2022

Bibliographical note

Funding
This study was supported by the National Natural Science
Foundation of China (51978522).

Data Availability Statement

The original contributions presented in the study are
included in the article/Supplementary material, further inquiries
can be directed to the corresponding author/s.

Keywords

  • expressway driving safety
  • truck service areas
  • non-linear optimization model
  • improved genetic algorithm
  • service loss rate

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