Sérgio Pedro Duarte, António Lobo, Joana Ribeiro, João Valente Neves, António Couto, Sara Ferreira
{"title":"道路基础设施管理的多层次决策方法","authors":"Sérgio Pedro Duarte, António Lobo, Joana Ribeiro, João Valente Neves, António Couto, Sara Ferreira","doi":"10.1080/12460125.2023.2263675","DOIUrl":null,"url":null,"abstract":"ABSTRACTThe design of effective road safety countermeasures requires a network diagnosis supported by data. Moreover, infrastructures need to be ready for the introduction of vehicle-to-infrastructure communications to support technologies, as truck platooning. Ascendi, a motorway concessionaire, developed an action plan to decrease crash frequency and casualties that rests in data recorded by automatic vehicle counting devices. To have a good network representation, new equipment will provide more data, thus enhancing the selection of countermeasures. We developed a multilevel decision-support approach to define equipment location. The process stages correspond to three levels of analysis: (1) clustering for road segment classification (network level); (2) quantification of the devices to install ensuring similar coverage (concession level); (3) device allocation according to geographical and cost criteria (segment level). An iterative and participatory process involving Ascendi resulted in a proposal for adding 43 devices to the existing 72, increasing the network coverage to 39%.KEYWORDS: Cluster analysismultilevel decisiondecision-makingdata collectionroad safetyVision Zero AcknowledgmentsThe authors acknowledge Ascendi’s support in the development of the decision-making process.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData not available due to commercial restrictions.Additional informationFundingThis work is financially supported by national funds through the FCT/MCTES (PIDDAC), under the project PTDC/ECI-TRA/4672/2020.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"45 1","pages":"0"},"PeriodicalIF":2.8000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multilevel decision-making approach for road infrastructure management\",\"authors\":\"Sérgio Pedro Duarte, António Lobo, Joana Ribeiro, João Valente Neves, António Couto, Sara Ferreira\",\"doi\":\"10.1080/12460125.2023.2263675\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTThe design of effective road safety countermeasures requires a network diagnosis supported by data. Moreover, infrastructures need to be ready for the introduction of vehicle-to-infrastructure communications to support technologies, as truck platooning. Ascendi, a motorway concessionaire, developed an action plan to decrease crash frequency and casualties that rests in data recorded by automatic vehicle counting devices. To have a good network representation, new equipment will provide more data, thus enhancing the selection of countermeasures. We developed a multilevel decision-support approach to define equipment location. The process stages correspond to three levels of analysis: (1) clustering for road segment classification (network level); (2) quantification of the devices to install ensuring similar coverage (concession level); (3) device allocation according to geographical and cost criteria (segment level). An iterative and participatory process involving Ascendi resulted in a proposal for adding 43 devices to the existing 72, increasing the network coverage to 39%.KEYWORDS: Cluster analysismultilevel decisiondecision-makingdata collectionroad safetyVision Zero AcknowledgmentsThe authors acknowledge Ascendi’s support in the development of the decision-making process.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData not available due to commercial restrictions.Additional informationFundingThis work is financially supported by national funds through the FCT/MCTES (PIDDAC), under the project PTDC/ECI-TRA/4672/2020.\",\"PeriodicalId\":45565,\"journal\":{\"name\":\"Journal of Decision Systems\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2023-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Decision Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/12460125.2023.2263675\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Decision Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/12460125.2023.2263675","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
A multilevel decision-making approach for road infrastructure management
ABSTRACTThe design of effective road safety countermeasures requires a network diagnosis supported by data. Moreover, infrastructures need to be ready for the introduction of vehicle-to-infrastructure communications to support technologies, as truck platooning. Ascendi, a motorway concessionaire, developed an action plan to decrease crash frequency and casualties that rests in data recorded by automatic vehicle counting devices. To have a good network representation, new equipment will provide more data, thus enhancing the selection of countermeasures. We developed a multilevel decision-support approach to define equipment location. The process stages correspond to three levels of analysis: (1) clustering for road segment classification (network level); (2) quantification of the devices to install ensuring similar coverage (concession level); (3) device allocation according to geographical and cost criteria (segment level). An iterative and participatory process involving Ascendi resulted in a proposal for adding 43 devices to the existing 72, increasing the network coverage to 39%.KEYWORDS: Cluster analysismultilevel decisiondecision-makingdata collectionroad safetyVision Zero AcknowledgmentsThe authors acknowledge Ascendi’s support in the development of the decision-making process.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData not available due to commercial restrictions.Additional informationFundingThis work is financially supported by national funds through the FCT/MCTES (PIDDAC), under the project PTDC/ECI-TRA/4672/2020.