{"title":"基于活动的智能交通共享出行模型","authors":"San Yeung, H. M. A. Aziz, S. Madria","doi":"10.1109/MDM.2019.00126","DOIUrl":null,"url":null,"abstract":"The shared mobility model of transportation services in cities has gained significant attention due to the proliferation of on-demand ride-sharing applications and the advancement of autonomous driving technologies. In this paper, a new shared mobility model is proposed accommodating the activity attribute of users' trip requests. Our key goal is to determine the minimum fleet size required to satisfy all on-demand requests while minimizing the total travel costs. Since this is an NP-hard problem, the model leverages a set of novel heuristic-based components including the clustering-based formation of ride-sharing groups, carpool-like schedule and ridesharing schedule generation, and clique-based trip integration. All work together to obtain the set of energy-efficient shared route schedules. The proposed model can also be extended for a heterogeneous vehicle fleet configuration (e.g. vehicles of various capacity and functionality) to work for different types of trip activities.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Activity-Based Shared Mobility Model for Smart Transportation\",\"authors\":\"San Yeung, H. M. A. Aziz, S. Madria\",\"doi\":\"10.1109/MDM.2019.00126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The shared mobility model of transportation services in cities has gained significant attention due to the proliferation of on-demand ride-sharing applications and the advancement of autonomous driving technologies. In this paper, a new shared mobility model is proposed accommodating the activity attribute of users' trip requests. Our key goal is to determine the minimum fleet size required to satisfy all on-demand requests while minimizing the total travel costs. Since this is an NP-hard problem, the model leverages a set of novel heuristic-based components including the clustering-based formation of ride-sharing groups, carpool-like schedule and ridesharing schedule generation, and clique-based trip integration. All work together to obtain the set of energy-efficient shared route schedules. The proposed model can also be extended for a heterogeneous vehicle fleet configuration (e.g. vehicles of various capacity and functionality) to work for different types of trip activities.\",\"PeriodicalId\":241426,\"journal\":{\"name\":\"2019 20th IEEE International Conference on Mobile Data Management (MDM)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 20th IEEE International Conference on Mobile Data Management (MDM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MDM.2019.00126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDM.2019.00126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Activity-Based Shared Mobility Model for Smart Transportation
The shared mobility model of transportation services in cities has gained significant attention due to the proliferation of on-demand ride-sharing applications and the advancement of autonomous driving technologies. In this paper, a new shared mobility model is proposed accommodating the activity attribute of users' trip requests. Our key goal is to determine the minimum fleet size required to satisfy all on-demand requests while minimizing the total travel costs. Since this is an NP-hard problem, the model leverages a set of novel heuristic-based components including the clustering-based formation of ride-sharing groups, carpool-like schedule and ridesharing schedule generation, and clique-based trip integration. All work together to obtain the set of energy-efficient shared route schedules. The proposed model can also be extended for a heterogeneous vehicle fleet configuration (e.g. vehicles of various capacity and functionality) to work for different types of trip activities.