Abstract
In recent years, the prohibition of trucks which could cause environmental pollution on urban roads has become widespread in China. However, some truck restriction policies might lead to a reduction in logistics transportation efficiency. With the help of big data, technology companies have developed many truck applications, such as HCB, truck home, and truck help, to provide the drivers available traffic information. In this context, this paper put forward a truck path optimization model considering environmental impact (TPOM-EI), which is solved by a heuristic algorithm—ant colony optimization (ACO) algorithm. Most previous studies focused on unilateral benefits rather than overall benefits; this paper aims to propose a path optimization model based on real-time minimization of social and transportation costs. Finally, data of Xiqing Economic and Technological Development Zone in Tianjin city (XQ-EDZ) have been used to demonstrate the applicability of the proposed algorithm. The results show that logistics truck path has a huge impact on social costs, and real-time activities in various areas will also change the path of a truck. This research will also help logistics truck drivers to choose the best route in real time.
Highlights
With the rapid development of economy and the explosive growth of urban population in China, urban problems such as traffic congestion and environmental pollution have become increasingly serious, affecting the people’s lives and the sustainable development of cities
Teo et al [4] have studied the environmental benefits of charging an exhaust emission penalty policy for highemission trucks, and the results showed that this policy increased exhaust emissions
Most researchers have tended to minimize the traffic congestion and environmental pollution caused by logistics trucks with unilateral benefits rather than overall, which led to a reduction in logistics transportation efficiency [5,6,7,8,9]
Summary
With the rapid development of economy and the explosive growth of urban population in China, urban problems such as traffic congestion and environmental pollution have become increasingly serious, affecting the people’s lives and the sustainable development of cities. In order to solve these problems, traffic management department tried to limit the run paths of trucks, especially high-emission trucks, to reduce traffic congestion and environmental pollution. Most researchers have tended to minimize the traffic congestion and environmental pollution caused by logistics trucks with unilateral benefits rather than overall, which led to a reduction in logistics transportation efficiency [5,6,7,8,9]. Trucks are gradually connected to the Internet with the help of big data and Internet of ings technology, and some software such as “truck home” for truck navigation has appeared It would provide practical application scenarios for our research
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