{"title":"基于上海市交通网络和公共交通车辆数据的时间消耗路径模拟器","authors":"","doi":"10.23977/jeis.2023.080305","DOIUrl":null,"url":null,"abstract":"With the rapid growth of every aspect of our society, people's schedule is getting tighter and tighter. Thus, there is a will for the masses to spend less time on road and get the precise time consumption, in order to form a neat schedule with little time being wasted. What we want to construct is a program, which will return the minimized time consumption and the best route. This project centers on the mission of simulate the transport condition of any time and find a rout which costs minimize time to reach the destination. The time we are simulating is not only present, but also for the future. The project can be mainly divided into four parts, including data acquiring, data processing, map building, the usage and comparison of graph algorithms.","PeriodicalId":32534,"journal":{"name":"Journal of Electronics and Information Science","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Path Simulator Focusing on Time Consumption-Based on the Transport Network and the Data of Public Traffic Vehicles in Shanghai\",\"authors\":\"\",\"doi\":\"10.23977/jeis.2023.080305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid growth of every aspect of our society, people's schedule is getting tighter and tighter. Thus, there is a will for the masses to spend less time on road and get the precise time consumption, in order to form a neat schedule with little time being wasted. What we want to construct is a program, which will return the minimized time consumption and the best route. This project centers on the mission of simulate the transport condition of any time and find a rout which costs minimize time to reach the destination. The time we are simulating is not only present, but also for the future. The project can be mainly divided into four parts, including data acquiring, data processing, map building, the usage and comparison of graph algorithms.\",\"PeriodicalId\":32534,\"journal\":{\"name\":\"Journal of Electronics and Information Science\",\"volume\":\"112 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Electronics and Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23977/jeis.2023.080305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electronics and Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23977/jeis.2023.080305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Path Simulator Focusing on Time Consumption-Based on the Transport Network and the Data of Public Traffic Vehicles in Shanghai
With the rapid growth of every aspect of our society, people's schedule is getting tighter and tighter. Thus, there is a will for the masses to spend less time on road and get the precise time consumption, in order to form a neat schedule with little time being wasted. What we want to construct is a program, which will return the minimized time consumption and the best route. This project centers on the mission of simulate the transport condition of any time and find a rout which costs minimize time to reach the destination. The time we are simulating is not only present, but also for the future. The project can be mainly divided into four parts, including data acquiring, data processing, map building, the usage and comparison of graph algorithms.