{"title":"基于agent的土地利用/运输综合模型中的交通噪声反馈","authors":"Nico Kuehnel, Dominik Ziemke, R. Moeckel","doi":"10.5198/JTLU.2021.1852","DOIUrl":null,"url":null,"abstract":"Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.","PeriodicalId":47271,"journal":{"name":"Journal of Transport and Land Use","volume":"14 1","pages":"325–344-325–344"},"PeriodicalIF":1.6000,"publicationDate":"2021-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Traffic noise feedback in agent-based Integrated Land-Use/Transport Models\",\"authors\":\"Nico Kuehnel, Dominik Ziemke, R. Moeckel\",\"doi\":\"10.5198/JTLU.2021.1852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.\",\"PeriodicalId\":47271,\"journal\":{\"name\":\"Journal of Transport and Land Use\",\"volume\":\"14 1\",\"pages\":\"325–344-325–344\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2021-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Transport and Land Use\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.5198/JTLU.2021.1852\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transport and Land Use","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5198/JTLU.2021.1852","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Traffic noise feedback in agent-based Integrated Land-Use/Transport Models
Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.
期刊介绍:
The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.