【中国科学报速递】城市移动管理与政策创新研讨会在京举行

发布时间:2019-07-15 16:31:52


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      为深入开展国家自然科学基金与欧洲城市化联合研究计划合作研究项目“城市公共管理与服务革新:新型的城市移动管理与政策(UPASS)”,近日,该项目组联合大数据驱动的管理与决策研究重大计划重点项目“大数据环境下汽车共享出行管理优化与智能服务”项目组,共同在北京组织召开了城市移动管理与政策创新研讨会(IUMMP),50 余位交通领域学者和研究人员参加。会上,香港科技大学教授杨海围绕近年来兴起的共享出行,详细介绍了近两年来涉及网约车市场的运营与管理的前沿性研究,为解决当前共享出行市场发展中的实际问题提供了有效途径。美国得克萨斯大学奥斯汀分校教授Chandra Bhat 围绕当前自动驾驶技术的快速发展和未来自动驾驶车辆的应用,探讨了技术转型时代的出行行为和移动治理问题。国立新加坡大学刘杨介绍了电动共享汽车充电设施部署和车辆管理的组合优化问题的研究进展。(李惠钰)


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China Science Daily ExpressWorkshop on innovation in urban mobility management and policy takes place in Beijing

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To deepen the conduct of the cooperative research program “Urban public administration and service innovation: new-type urban mobility management and policy” (U-PASS) funded by the National Natural Science Foundation of China (NSFC) and Joint Programming Initiative Urban Europe (JPI UE), the program team recently held the Workshop on Innovation in Urban Mobility Management and Policy (IUMMP) in Beijing in collaboration with the project team of the key project “carpooling management optimization and smart services” under the major program of big data-driven management and decision research, involving over 50 scholars and researchers in the transportation field. At the meeting, Prof. Yang Hai from Hong Kong University of Science and Technology detailed the frontier research involving the operation and management of online ride-hailing market in the past two years encompassing the rise of rideshare in recent years, providing an effective approach to resolving the actual problems with the development of the rideshare market. Prof. Chandra Bhat from University of Texas-Austin explored the issues of travel behavior and mobility management in the era of technological transformation, encompassing the rapid development of the current autopilot technology and the application of future self-driving vehicles. Liu Yang from the National University of Singapore presented the latest research findings on deployment of charging facilities for electric shared cars and combinatorial optimization issues with vehicle management. (Li Huiyu).