Abstract
The environment problem is a sustainable hot topic in the field of transportation research. With higher awareness of the environment problem, travelers tend to choose more environment friendly traffic modes and travel routes. However, for motor vehicle drivers, the environmental cost is an implicit cost, which is not easily perceived. With the help of the advanced traveler information system (ATIS), a fresh scheme was proposed to reduce the environmental cost of the transportation network, which incorporates the information of environmental cost into ATIS to guide drivers to choose more environment-friendly routes. To test the validity of the scheme, we adopted the theory of stochastic network user equilibrium to assign two classes of drivers on the transportation network and analyzed the impact on environmental cost after applying this scheme. Mathematically, a mixed stochastic user equilibrium (SUE) model was proposed to analyze this scheme. The corresponding algorithm was also proposed. Both the model and algorithm were tested in the numerical examples. Through the examples, the validity and feasibility of our proposed scheme were also identified. Our research provided some new ideas for traffic planners and managers to reduce environmental costs caused by traffic.
Highlights
The sustainable development of transportation systems is a major concern throughout the world, which is typically characterized in terms of three dimensions, including “economic, environmental, and social” [1]
The International Council on Clean Transportation pointed out that transport consumes approximately 20% of global energy use and it is responsible for about 25% of global energy related carbon dioxide emissions, with 75% of these emissions due to road transport energy use [6,7]
We have considered incorporating environmental cost into advanced traveler information system (ATIS) to guide travelers’ route choice, and to analyze this problem at network level, which fill the gaps in the literature
Summary
The sustainable development of transportation systems is a major concern throughout the world, which is typically characterized in terms of three dimensions, including “economic, environmental, and social” [1]. If the environmental cost can be incorporated into the path finding process in ATIS, the environmental cost of the transportation network may be effectively reduced through providing drivers with green route guidance. It is this idea that motivates our research. The main contributions of our research includes three aspects: (1) We proposed a fresh scheme based on the travelers’ route choice behavior to reduce the environmental cost of the transportation network; (2) We proposed a mixed SUE model and the corresponding algorithm to describe and solve.
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