Abstract
With the increase of vehicle activities and adverse weather under the background of modernization and global warming, more attention should be paid to vehicle emissions reduction in such circumstances for environmental protection and sustainable transportation. Different from some typical measures, e.g., relevant government policies, improvement of vehicle hardware technologies, and optimization of traffic management, this paper develop a new method based on emergency path optimization to evaluate and reduce pollutant emissions of logistic transportation under adverse weather. Firstly, we establish a calculation model of pollutant emissions (LT-PE model) to calculate the amount of vehicle pollutant emissions produced under adverse weather. Then, a co-evolving path optimization (CEPO) method-based ripple-spreading algorithm is proposed in order to reduce pollutant emissions. To validate the effectiveness of the proposed method, this paper selects fruit logistics transportation affected by typhoon in China’s Hainan Island as a case study. The results show that total vehicle pollutant emissions from the fruit transportation of 35 farms under the typhoon are 28.1% more than when there is no typhoon. The proposed method can reduce pollutant emissions by 21.2% compared with the traditional methods under typhoon.
Highlights
The development of international trade and e-commerce has promoted the rapid growth of industrial production and people’s consumption, which has driven up the logistics industry in recent decades all over world [1]
Carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), and particulate matter (PM) from vehicle emissions contribute a high proportion of atmospheric pollutants [8,9,10,11,12,13,14]
Haze-fog by PM2.5 has become a big concern of public health nowadays, and recent research has shown that CO and NOx from vehicle emissions are related to increased incidence of asthma and lung cancers [2,13]
Summary
The development of international trade and e-commerce has promoted the rapid growth of industrial production and people’s consumption, which has driven up the logistics industry in recent decades all over world [1]. As with the eco-driving method, we are mainly concerned with the path optimization of multiple vehicles of long distance cargo transport for drivers within a large geographical region to reduce vehicle emission under adverse weather. The emergency path optimized in this paper cannot only ensure travelling safety, but more importantly, it can help to reduce vehicle pollutants emission Adverse weather such as rainstorm, snow, or fog make route conditions more complicated than usual, e.g., wet/ice surface, high wind, and cause route network to change, so path planning under normal weather is a static path optimization (SPO) problem. We will modify the CEPO method to develop a new, effective pollutant emission reduction method for multiple vehicles of long-distance cargo transport under adverse weather.
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