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从智能交通到社会交通
linchaogao 2014-8-22 13:52
社会交通概念是王飞跃教授新近提出的一种理念 ,从表面来看的话即将社会 + 交通两种概念相融合,而社会的概念又是广泛的,其涉及到整个人类社会的生活方方面面。政治、经济、文化、能源、交通等领域,而交通问题无疑是社会交通理念的核心。 从历史发展的角度上来看,社会的概念起初对应于团体和圈子,也就是一种共同体的集合。社会根据生产方式划分为农耕社会和工商社会;根据制度划分为社会主义社会,封建主义社会,资本主义社会;根据群体划分为上流社会,中产阶级,黑社会等概念,而从范围和空间上来看,又分为东方社会和西方社会。从这些划分上可以看出来: 社会在自发形成过程中使得其拥有适合自身系统运行的结构形态和组织形态。只是因为其所划分的标准和角度不同。 社会是一个复杂系统的典型案例。复杂系统是可以简化的。 就像MIT授 leiserson 所言:复杂的问题简单化,有必要复杂的时候再复杂。就像印度圣雄甘地所言:“简单是宇宙的精髓”。并不是说这个系统的运行规律到底有多少千丝万缕的关系,所有芸芸众生的背后都有“道”的存在,即一种生存运行规律。而只要抓住了这些规律的主体我们就可以很好的解决所要面临的问题。 社会是人的社会,人是社会的人。在一定程度上,社会问题的所有问题基本上都是人所引起了,当然除了一些无法预测的自然灾害除外。而只要将人这个对象研究透了,所有的社会问题都会迎刃而解,或者说不能迎刃而解也可以规避风险,将破坏性降低到最低水平。 交通问题是社会问题的一个集中爆发点,也是一个重灾区。 通过调研发现,引起交通拥堵的客观因素无外乎有以下几点: a. 行车量过大导致路网承载能力不够(参考海尔路路段调研报告); b. 道路信号灯和导向线设置上没有考虑行车总体通行量,采用引鸩止渴的方式舒缓了部分路段的交通压力而导致其他路段的车辆堵塞(参考调研报告南京路段分析); c. 在没有实际考察的基础上直接鲁莽的将所有路段规定为可以左行,直接导致该直行的无法直行,该转弯的没法转弯(参考山东路路段调研报告); d. 人行道与交通灯不匹配导致行人无法通过,车辆让也不是,进也不是(参考同安路,绍兴路路段调研报告); e. 商场区域,或者说旅游区与机动车行驶道路划分不明确,导致行人和车辆混杂,影响整体运行速度(参考李沧区李村商圈调研报告); 以上 6 点为影响交通拥堵的主要几点,当然还有林林总总很多小的问题,这里不再赘述。如果遵从透过现象看本质的思想,这几大点背后都是一个字在作祟:人。 对于一个交通系统来说,构成一个城市交通体系的整体因素无外乎三点:路网;出行点;出行者,这三者中路网是固定不变的,城市整体每天出行方式也是固定的(当然不考虑节假日等),而这三者之间的最难以把握的就是人的行为( human behavior ) , 因为人是出行的主体,也是车辆运行的主体,亦是交通规则制定者的主体。所以说,人的因素( human factor )是所有交通问题的关键点,也是交通拥堵( traffic congestion )的主观因素,外因永远不是导致问题出现的根本原因,内因才是,而交通问题的内因就是人。 所以我认为社会交通概念的提出应该有以下等式: SocialTransportation = Social Computing + ITS +Human factor; 其中的社会计算可以看作是量化社会的一种,即将整体的实际( real time )交通状况搬移到计算机上,仿真模拟真实的世界,具体的技术细节请可以参考王飞跃老师 blog, 而 ITS(intelligent transportation system) —智能交通可以看作是是一种硬件的组合: 信号灯、诱导屏、违法抓拍行为和 app 智能通报系统,而社会交通的等式的最后一点,也是问题的关键点,或者说可以串接起来社会计算和智能交通系统的主题就是 human factor ,前面的不管是社会计算理论还是 ITS 硬件设施其服务的对象仍旧是人,人的出行时间,地点,方式, OD ( origin-destination )都是所有问题的关键点,怎样最好的做到 “ 以人为本 ” ,即以方便、快捷的方式达到一个个体的目的是我们所要研究问题的焦点,也是社会交通理念提出来的最关键点。 目前来说社会交通概念的提出国内外比较稀少,应用的话就更是凤毛麟角。像国内比较流行的滴滴打车,国外的 Uber 和 bandwagon 等打车 app 都是侧重于更好的服务于人,这都是抓住了问题的关键,总体来看其主要是借助于 (mobiledevice) ,但由于手机 GPS 定位精度的限制,不是所有的打车服务都能做到点对点的准确服务。同时根据调研发现,不是所有的滴滴打车司机都愿意点对点的去寻找一个乘客,因为他们可以在路上不断的碰到要求乘车的乘客,对于 OD 距离比较近的乘客出租车司机也是不愿意接单的,原因同上。这些原因直接导致不能做到更好的以人为本,所以说,滴滴打车服务的应用远景并不看好。 但怎样才能真切的做到以人为本呢?继而做到整个城市交通顺畅呢? 既然主体 — 人的目的很简单:方便,快捷的达到目的地,我们是否可以将整个城市的运行主体 —— 机动车,根据其目的的不同划分为不同的结构要求,城市运行的机动车无非就是上班族(路线比较固定),旅游组(路线比较固定),背包客(路线不固定)以及其他各种成分的人,在整个城市路网系统开始运行之前(当然不能做到抽刀断水),运用 ITS 对于即将输入的各种成分进行统计,根据成分 OD 的不同进行整体的预测,随后布置路线,对于整个城市的另外一个主体 — 公交车,出租车,私家车等进行路线的整体动态规划,不断调整系统路线布局(当然需要借助于 ITS 硬件设备),力求使每一辆车每一个人都能尽快通过这种智能交通达到其所要到的目的地,每一次个体的运输结束就是对城市路网的一次释放,就像内存塞满程序会死机一样,好的算法能使的整个路网系统时刻保持畅通状态。当然从经济学的角度来看就是资源的有效利用,空闲资源的合理配置。 从智能交通到社会交通是从工程领域到人文领域的过度,筚路蓝缕 以启山林。希望在这块新的领域能和各位一起探索未来,真正做到社会交通的以人为本。 交流邮箱:linchaogao@163.com IEEE Transactions on Intelligent Transportation Systems, Vol.15, No.2, pp457-462 Scanning the Issue and Beyond: ITS with Complete Traffic Control linchaogao@163.com
个人分类: ITS|3991 次阅读|0 个评论
主编引语:全面交通控制(No. 2)与社会交通(No. 3)
热度 1 王飞跃 2014-6-1 14:06
IEEE Transactions on Intelligent Transportation Systems, Vol.15, No.2, pp457-462 Scanning the Issue and Beyond: ITS with Complete Traffic Control ITS with Complete Traffic Control In the past few years, I often chug through the Beijing metropolitan area at an average around 10 to 15 miles an hou r, slower than in most of other major cities around the world. I still remember that one day in the Spring of 2012, it took me exact 2 hours to drive a distance that normally would need less than 20 minutes to complete, and I missed my appointment. While sitting in my car on congested roads or at crowd intersections, I often recalled a project I had for my 1999 class “SIE 658: Advanced Topics in Robotics and Automation ”, it was about the total and complete traffic regulation for achieving zero fatality by automatic control of each individual vehicles using dual GPS in a transportation network. The project was called “ Future Traffic Control without Traffic Lights”,a little futuristic before Google’s autonomous vehicles take over our roads. Now I think we can achieve a “soft” version of such total and complete traffic control by integrating computer vision, cell phones, variable message systems (VMS), and new connected vehicular technology. In Tucson, Arizona, a city I have lived and worked for over 20 years, many automated speed camera systems have been installed among selected sites for the purpose of decreasing speeding violations and reducing collisions. However,I believe this technology, combined with VMS and in-vehicle warning or display devices, can be used to develop In Situ segment traffic controllers and regional traffic controllers: that is, in additional to safety consideration, using cameras to identify vehicles, their speeds and moving behaviors for the purpose of traffic control,monitoring and regulating by laws. In this way, we can plan and manage the speed of vehicles and their driving behaviors along a segment of a road or among a region of a road network, just like we can control the traffic flow at road intersections through traffic light controllers. Geometrically, this is a generalization of intersection traffic controllers as point control to camera-based segment or regional traffic controllers as line or area control. The complete or total traffic control provides a realistic mechanism for rapid implementation of some new and exciting methods and techniques in communication and controlfor traffic management. Especially, the concept from the emerging new network technology, so called software-defined networking (SDN) , and the ACP-based parallel control and management of complex systems that I have introduced a decade ago. In SDN, network administrators are able to manage network services through abstraction or virtualization of lower level communication functionality by decoupling the system that makes decisions about where trafficis sent (the control plane ) from the underlying systems that forward traffic to the selected destination (the data plane ). As claimed by the Open Networking Foundation’s white paper, “Software-Defined Networking: The New Norm for Networks”, through such decoupling enterprises and carriers gain unprecedented programmability, automation, and network control, enabling them to build highly scalable, flexible networks that readily adapt to changing business needs. I believe the idea of complete traffic control provides the basis for the concept of Software-Defined Traffic Networking (SDTN), which is a direct implementation of Artificial Transportation Systems in my ACP approach. This combination might enabletraffic network users or customers obtain the similar benefits or even more as those offered by SDN for communication. As a matter of fact, SDN provides only part of the AC functionality, no steps in P are involved so far, which leads to a closed-loop network management for better performance, as described in the ACP parallel systems approach. I believe this extension could make our traffic networks more effective, less pollution . F EI -Y UE W ANG , Editor-in-Chief IEEE Transactions on Intelligent Transportation Systems, Vol.15, No.3, pp909-914 Scanning the Issue and Beyond: Real-Time Social Transportation with Online Social Signals Social Transportation Overa decade ago, I introduced the term “ social computing ” as a new direction for computational social studies; two years ago, we published the first monograph on social computing; and today, I’m glad to say, social computing has emerged as a major research direction worldwide. Now I would like to coin another term— social transportation —to describe another emerging field of research, development, and application forintelligent transportation systems. In my musings on the term, I wasn’t sure if there was already any research activity in this direction, so I did a cursory search in Google and found that journalists were already using the term in news reports. Specifically, I found two articles that cited “social transportation”, one titled “The Future of Social Transportation: Bandwagon Is Helping You Share Cab Rides”, a story about a ride-sharing app called Bandwagon for mass carpool in New York City (especially for trips to airports JFK and LaGuardia). Bandwagon aims through the app to coax the city’s taxi system into a future of “modular transportation”, making it“more social, more efficient, more like transit”, and facilitating a shift to thinking of the “car as part of a larger transportation network” in which“anyone can catch a cab-share at any time and from any corner”, with the ultimate aim of making our society “easier and less expensive to be carless.“And another: “Social Transportation for Seniors”, on “reconnecting senior residents of North Richland hills, Texas with the community by providing free transportation to leisure and social activities.” Both are related to my own thoughts, but I was surprised to find that stories and news about ridesharing app pioneer Uber did not use term “social transportation” before. Also, despite Uber - and Bandwagon -like apps mushrooming in China now,the term “social transportation” has not appeared there. As for academic research, no one has mentioned social transportation, at least according to Google and Baidu. By the way, I also searched term “social traffic”, and was surprised that the top items were about data traffic of social websites, nothing about real world traffic flows on the road! However muted its Internet presen c e, social transportation has existed and developed without a name for quite a while. To me, traffic analysis and forecasting using data from mobile phones and social media are just the typical examples of social transportation research. Social transportation should emphasize real-time computing and embedded applications in transportation systems with on-line and interactive big data, this is how the field differentiates from works in the sociology of transportation, which are off-lineand usually historical. Social transportation has the potential to rapidly become an important and independent field of research in transportation, we can do this by focusing in five areas, 1) traffic or transportation analytics with big data and social signals using data mining, machine learning, and natural language processing methods; 2) crowdsourcing mechanisms for transportation based social media, social networking, and the Internet of Things (IoT) or even the Internet of Everything , especially the coming vehicles to vehicles, websites, people, infrastructures communication; 3) new services beyond location-based services (LBS), such as transportation knowledge automation, especially decision-based services (DBS) or task-based services (TBS) that collecting required information in real time for transportation decisions or tasks, and information or intelligence-based services (IBS) or knowledge-based services (KBS) that recommending agents or organizations who might find the identified intelligence or knowledge useful for solving traffic problems or improving the transportation performance; 4) web-based agent technology for transportation control and management, such as software robots or web surrogates for traffic monitoring, safe driving, vehicular heath and energy management, at this point, the effort should be directed in developing various smart apps that collect social traffic data and link people to traffic and cars in real time; 5) real applications and feedback for more research and development. This year I have graduated my first PhD candidat e in social transportation, and I hope within the next few years we will dedicate more papers, special issues, books,and conferences in this important field. More than 100 years ago, we started the march towards an Auto Society, and we have since become so successful that many nations, first in the US and now in China,have become “nations on wheels”. Today, we now face the consequences of this modern revolution – many large cities around the world experience traffic congestion and pollution, we need to fix these problems, and I hope the emerging field of SocialTransportation willbe a big help in this effort. F EI -Y UE W ANG , Editor-in-Chief
个人分类: 科研记事|10514 次阅读|2 个评论

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