How Does COVID-19 Affect Traffic on Highway Network: Evidence from Yunnan Province, China

Abstract

The COVID-19 pandemic and antipandemic policies have significantly impacted highway transportation. Many studies have been conducted to quantify these impacts. However, quantitative analysis of the impacts on province-wide traffic in developing countries, such as China, is still inadequate. This paper tried to fill this gap by proposing equations to quantify the traffic variations of overall province-wide traffic and to analyze the intercity bus traffic variation and intercity bus usage, applying the K-means cluster method to conduct the analysis of traffic reductions in regions with different levels of economic development, and using the hypothesis testing for traffic recovery analysis. It is found that passenger vehicle traffic and truck traffic dropped by 59.67% and 68.19% during the outbreak, respectively. The intercity bus traffic on highways declined by 59.8% to 98.6%, and the intercity bus usage dropped by 55.6% on average. For traffic reductions in different regions, the higher the GDP per capita was, the more the traffic was affected by the pandemic. In regions with lower GDP per capita, traffic variations were minor. It is also found that the passenger vehicle traffic went through four stages in 99 days: the Decline Stage, Rapid Recovery Stage, Slow Recovery Stage, and Normal Stage, while truck traffic only experienced the Decline Stage, Rapid Recovery Stage, and Normal Stage and took 51 days to recover to the Normal Stage. In the Rapid Recovery Stage, the recovery rates were 15.6% and 12.9% per week for passenger vehicle traffic and truck traffic, respectively, and the recovery rate was only 2.1% for passenger vehicle traffic in the Slow Recovery Stage. Despite the recovery of traffic volumes, neither passenger-kilometers nor tonne-kilometers of freight in 2020 reached the same level as in 2019. These findings help the understanding of the pandemic’s impacts on highway traffic for researchers and can provide valuable references for decision-makers to develop antipandemic policies.

Transport Risks in the Supply Chains – Post Covid-19 Challenges

“…The discussion of challenges posed by COVID-19 in transport mostly focuses on negative impacts and their mitigation. However, it is worth mentioning some unintended positive effects linked with transportation: reduction of pollution and waste (Erkhembayar et al, 2020;Haque et al, 2021), significant decline in traffic (Li et al, 2022), positive impact on road freight transport turnover (Ho et al, 2021), rapid progress in digitisation and implementation of innovations in the transport sector (Subramanya & Kermanshachi, 2021), and robotisation (Zeng et al, 2020). As a result of COVID-19's multifaced and severe implications, risk management in the supply chain has become an intensively explored area of scientific research.…”

Understanding bike-sharing mobility patterns in response to the COVID-19 pandemic

“…The results showed a non-linear relationship between intercity travel and pandemic mainly due to the change of control policy. The travel pattern analysis on highway network was conducted based on the trajectory information (Li et al, 2022), and the tra c ow pattern was de ned as before pandemic, during pandemic and recovery stage. On the other hand, a few of researches focused on the urban transportation system.…”

A Review of COVID-19-Related Literature on Freight Transport: Impacts, Mitigation Strategies, Recovery Measures, and Future Research Directions

“…Twenty-four studies report the impact of the COVID pandemic on the demand for different freight transport modes, i.e., air, maritime, rail, and road. Six studies examine the impact of COVID-19 on the demand for seaports and waterways transport [6,7,9,37,[39][40][41][42][43]. Tianming, Erokhin, Arskiy and Khudzhatov [9] show that the pandemic breaks the connectivity among seaports in China, Norway, Iceland, Russia, South Korea, and Sweden.…”

“…Gray [32] reports an increasing demand in the agriculture sector for different transportation services, e.g., bulk ocean freight, rail movement, and road trucks. Li, Bai, Hu, Yu and Yan [42] present equations to evaluate the traffic variations of overall provincewide traffic and tested the hypotheses for traffic recovery analysis. The results show that truck traffic dropped by 68.19% during the outbreak and found that the higher the GDP per capita the region has, the more the traffic in the region was affected by the pandemic.…”