Urban ecology and related environmental concerns
M. Moghadami; A. Rasaizadi; M. Askari
Abstract
BACKGROUND AND OBJECTIVES: This research attempted to analyze the negative and positive aspects of Coronavirus: its effect on air quality and traffic volume. The sample city of this research was Tehran and transportation behavior toward the Coronavirus and minor quarantines in specific. METHODS: Six ...
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BACKGROUND AND OBJECTIVES: This research attempted to analyze the negative and positive aspects of Coronavirus: its effect on air quality and traffic volume. The sample city of this research was Tehran and transportation behavior toward the Coronavirus and minor quarantines in specific. METHODS: Six indices were considered for Tehran city in two consecutive years (in quarantine period): carbon mono-oxide, nitrogen dioxide, sulfur dioxide, particulate matters, air quality index, and daily traffic volume, which depart from Tehran city to other destinations. Daily traffic volume changes were examined for four roads separately, and total departed trips were also investigated. This comparison was made graphically and statistically by using the regression model and one-way t-test. FINDING: Results showed that from 20th February to 19th March, the average of produced CO, NO2, and PM10 decreased in 2020 compared to 2019, but other indices related to air pollution were increased in 2020. The average daily traffic in existing roads of Tehran City was declined significantly in 2020. Regression models and a one-way t-test showed that the growth rate of emission production was higher in 2019 compared to 2020. Also, this rate for daily traffic volume was higher from March 20 to April 19 of 2020 compared to 2020. CONCLUSION: The regression model on indices showed valuable results. For instance, the O3 emission slope in the second month reduced from 0.6 to 0.5; however, the exiting traffic of Tehran city reduced by 47 percent that indicates the higher resident population of Tehran city compare to the last year.
Sustainable urban infrastructure
A. Edrisi; A. Nadi; M. Askari
Abstract
BACKGROUND AND OBJECTIVES: After having struck in a major natural disaster like an earthquake, different organizations run about to decrease losses. The lack of accurate demand information is a common problem that all emergency response organizations have to encounter such a crisis. Evaluation of ...
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BACKGROUND AND OBJECTIVES: After having struck in a major natural disaster like an earthquake, different organizations run about to decrease losses. The lack of accurate demand information is a common problem that all emergency response organizations have to encounter such a crisis. Evaluation of the City disaster level is a mean to feed this information to the disaster response operations. The objective of this research is eschedule a group of experts to assess relief demand. These evaluation teams need to be scheduled to minimize the evaluation time. METHODS: This paper aims to formulate the routing and scheduling of the assessment teams so that real demand information for savings and rescue would be available as soon as possible. The simulated annealing algorithm is used to solve the scheduling problem. FINDING: two cost functions, sum of arrival time and max completion time, were evaluated. The latest is found to perform better in evaluation of the teams performance. CONCLUSION:The performance of the approach is tested on several randomly generated networks and synthesized demand data. The results show a 13 % improvement in the total completion time of operation in comparison with previous approaches.
Urban transportation systems and traffic management
A. Rasaizadi; M. Askari
Abstract
The modal split model is one of the steps of the classical four-step travel demand planning. Predictive, descriptive, and prescriptive modal split models are essential to make a balance between travel demand and supply. To calibrate these models, it is necessary to detect and employ influential independent ...
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The modal split model is one of the steps of the classical four-step travel demand planning. Predictive, descriptive, and prescriptive modal split models are essential to make a balance between travel demand and supply. To calibrate these models, it is necessary to detect and employ influential independent variables that are related to characteristics of travel modes, individual and family attributes, zones land use, etc. In previous studies, researchers used the household size, the number of children, and the number of employees as independent variables to show the role of family structure on the modal split. These variables cannot discriminate between different families with different structures. This paper uses the life cycle concept to categorize families based on their structures, and the effectiveness of these new variables on modal split models is examined. For this purpose, five types of family structures are considered that differences between them are based on the age of the family’s children. The Multinomial Logit model is used for mode choice modeling for different trip aims. The mode choice model has been calibrated using the origin-destination data of Qazvin-Iran. Results show the critical role of life cycle dummies in the mode choice models compared to household size, for work, educational, personal, and social- recreational trip aims. Life cycle variables are more active on the work trips mode choice model by estimating 14 significant coefficients, in a 90 percent level of significance. The number of life cycle significant coefficients is decreased to 3 for the shopping trips model.
Sustainable urban infrastructure
A. Edrisi; M. Askari
Abstract
Most cities around the world are in danger of disasters. Among disasters, the earthquake is the most dangerous and ruining one. Iran has been located in the Alpine-Himalayas seismic belt, and because of the significant frequency of severe earthquakes happening all over the country compare to other countries ...
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Most cities around the world are in danger of disasters. Among disasters, the earthquake is the most dangerous and ruining one. Iran has been located in the Alpine-Himalayas seismic belt, and because of the significant frequency of severe earthquakes happening all over the country compare to other countries and the state of the unsecured residential and non-residential buildings in most of the areas, attention to the post-disaster phase is vital. This study aims to locate shelters in some districts and allocate at-risk people of all districts to these shelters. Also, another purpose of this study is the reduction of the allocated budget by the government and reduction of traveled distance by people considering the possibility of link failure due to the earthquake. Allocated budget by the government for shelter construction includes the fixed and marginal cost. Mixed Integer Linear Programming has been used for modeling the suggested method. This method has been applied to the Tehran network, and the Genetic Algorithm has been used for solving the proposed method. The results showed that the leading share of the imposed costs arose from the shelter construction budget. Furthermore, the probability of choosing a district for constructing a shelter has a direct relationship with the at-risk population and the cost of shelter construction in that district. Seven districts have chosen to build shelters with about 400 thousand people capacity. District 16 chosen for constructing the biggest shelter that should serve to up to 123 thousand people and District 5 chosen to construct the smallest shelter that should serve to up to 16 thousand people.
