Optimization and modification of urban transportation network of Qom with environmental considerations using genetic algorithms and GIS
IntroductionTransportation in cities has always been a matter of interest to people. However, following the Industrial Revolution, the unprecedented increase in urbanization and the emergence of various means of transportation, the importance of transportation is greater than ever before. Today, transportation is one of the most important and influential infrastructures and it allows for the development of society while, at the same time, it is under the influence of development; this is the reason why managers and city planners pay close attention to transportation. Despite the focus of transportation planners on accessibility and other dynamic aspects of urban transportation, however, the side effects on the environment have been severely neglected. Stable transportation has economic, social, and environmental factors and stability is achieved by considering all these factors simultaneously. The city of Qom, as an important city for religion and tourism, needs to organize and manage it in a way that does not conflict with other developments or the environment.
Materials and methodsIn order to achieve this, after studying the sources the environmental indicators relating to transportation were found and five important indicators identified. Rating these indicators was done according to location and with GIS mapping of Qom's transportation systems and expert opinions. In order to do this, the map of Qom was entered into a grid and indicators in each grid cell were evaluated separately. The final status of each cell was specified using MATLAB software and a genetic algorithm.
Results and discussionTo be able to achieve an optimal environment requires changes in the road network or changes in user locations that are more sensitive to the pollution caused by transport. The results showed that 30% of grid cells were in a bad condition, 30% in an average condition and 40% in a good condition from the point of view of their environmental situation.
ConclusionThe results for the transport network demonstrated that it can be well optimized and the map shows that transfer of a part of the users, especially in residential areas in the area around the city and with less pollution, resulted in marked changes in the proportion of grid cells. As a consequence, the majority of cells with a score of 3 points (bad) to 1 (good) would change their status so that only 10% of the cells would then be placed in a bad condition in terms of the environment. Thus, transfer of a part of the users from downtown to surrounding areas would be a good strategy for reducing the impacts of pollution from transport.
Environmental Sciences, Volume:14 Issue: 4, 2017
91 - 104
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