摘要
随着“双碳”背景下移动互联网的应用和共享经济的发展,高效、便捷、绿色的汽车共享出行服务越来越受到广大出行者的青睐。一个功能齐全的汽车共享运营管理系统对于降低运营成本、提高运营效率和提升用户满意度至关重要。首先,分析运管系统设计时面临的挑战;其次,基于车联网和大数据架构的开源组件研发了一个端到端的运管系统,集成决策优化及评估框架,能够动态优化用户和车辆的供需匹配问题,提高用户满意度并有效较低运营成本;最后,遵循软件开发生命周期SDLC方法,描述运管系统整体开发过程。运管系统以软件即服务(SaaS)的形式部署在云服务器中,能够有效降低部署成本并提供良好的弹性和扩展性。汽车共享公司可以利用运管系统增强其在出行服务市场中的竞争力,交通规划与运营部门可以接入运管系统来监控汽车共享系统的运行状态。
With the rapid growth of the mobile internet and the sharing economy,efficient,convenient,and environmentally friendly shared car travel services have gained popularity among travelers.A comprehensive and robust carsharing operation management system is essential for reducing costs,enhancing operational efficiency,and delivering excellent user experience.This paper examines the challenges encountered in the design of carsharing operations management systems.Furthermore,an end-to-end management system was implemented using open-source components built on the architecture of the Internet of Vehicles and big data.It integrates a decision optimization and evaluation framework,capable of dynamically optimizing the supply-demand matching problem of users and vehicles,thereby enhancing user satisfaction and effectively reducing operational costs.Finally,this article presents the development process of the operations management system,following the software development lifecycle(SDLC).The system is deployed as a software-as-a-service(SaaS)on cloud servers,offering cost efficiencies,elasticity,and scalability.Consequently,carsharing companies can leverage these transportation management systems to gain a competitive edge in the travel service industry,while transportation planning and operation departments can utilize them to monitor the operational performance of carsharing systems.
作者
侯珏
HOU Jue(The Key Laboratory of Road and Traffic Engineering,Ministry of Education,Tongji University,Shanghai 201804,China;College of Transportation Engineering,Tongji University,Shanghai 201804,China)
出处
《交通与运输》
2023年第6期100-104,共5页
Traffic & Transportation
关键词
汽车共享
大数据
车联网
需求预测
供需匹配
Carsharing systems
Big data
Internet of vehicle
Demand prediction
Supply demand matching