第四届中国-中东欧国家（17+1）创新合作大会于2019年10月7日至9日在塞尔维亚共和国首都贝尔格莱德市举办，中国科技部部长王志刚、塞尔维亚创新与技术发展部部长奈纳德·波波维奇等与会国部长级领导，以及国内相关产业协会、创新型企业和科研院校共聚贝尔格莱德，商议中国与中东国家科技创新合作。

银江股份智慧交通研究院副院长徐甲，受中国智能交通协会之邀，代表股份公司和银江研究院出席会议，推介公司最新创新战略与技术产品，并接受塞尔维亚当代科学与数据科学家研究所所长——亚历山大·林克·乔尔杰维奇（以下简称主持人）主持的专题访谈。

访谈中针对AI技术在城市交通治理方面的应用展开深入探讨，对杭州交通信号配时中心的成功案例进行分析。杭州作为银江股份在大型城市交通路网信号配时优化服务探索方面的先行城市，拥有最好的团队和资源，结合AI技术全方位改善城市道路拥堵问题，科技与服务并行，在融合AI技术与交通治理的探索路程中具有深度研究价值。

主持人提出了4个企业在人工智能转型以及应用方面的问题，以下为访谈内容（英文原文与中文翻译）：

Djordjevic：What does an AI-powered organization stand for you and what experience do you and your company have with the topic of AI?

徐甲: Nice to meet you dear host of respect. As you may know, our company, Enjoyor is not an AI startup company, it has over 2 decades’ experience in the ITS construction, software engineering and system integration. During the past 2 decades, many projects of high quality have been settled down and lots of customers have been cultivated to pursue finer services. That means the service has to be more scientific to be able to tackle down their sophisticated realistic problems in a global view and also can be tailored to suit for their unique business processes. Under such background, our company has proposed and started up the AI strategy to meet the costumers’ needs. So our company is exactly the type of companies who is experiencing the AI transformation.As for the experience with AI topic, the most crucial thing we’ve realized is that we should always put the industrial practicality of AI techniques in the first place, which is to know the capability as well as the capability boundary of AI techniques in order to use them properly. Secondly, we should provide affordable AI techniques for the customers, in view of the necessary data and computational power.

Djordjevic:Dear Jia, You come from a country which has 42 cities with more than 2 million people living there. I can’t even imagine how something that we see as an easy fix and normal thing can become so exponentially complicated - just because of the numbers itself. That is why I cannot think better interlocutor for the topic of traffic, transportation and travel services than you.May I ask you to give us an overview of what are the major challenges you are facing and how does AI may solve problems in the transportation sector? Can you also tell us more about some concrete project your company is working on?

徐甲：Indeed, the city I live, Hangzhou has a population of 10 million, and more than 3 million of registered vehicles. The volume of vehicles in transit during daily peak is about 300,000 in average.The complexity of the problem comes from many ways. The scale of the problem is our first challenge. Hangzhou is a provincial capital city, which has a large amount of domestic or international activities and events. Meanwhile Hangzhou is a world-famous tourist city, the West Lake attracts huge amount visitors, the complex scenario caused by these factors is our second challenge. The traffic network we are facing to is consists of about 2000 signalized intersections, a considerable part of them are suffering from large traffic flow, imbalanced demand, and high dynamic in the same time, which is our third challenge. Last but not least, we are facing some engineering challenge, such as multiple source date collection and processing, modelling and managing the traffic channelization.As for the cases that we are using AI to tackled down real problem, I’d like to share with you an example. We use AI technologies in the traffic signal control to eliminate traffic congestion in Hangzhou and Nanchang. This sophisticated process generally includes 5 sections, that is perception, early warning, optimization, implementation, and security check.In the perception section, we use AI techniques to estimate the reliability of the raw data. Then to repair and provide the most reliable and direct date to the following sections. In the early warning section, the crucial thing is to estimate the trend but not the status of the traffic, therefore the predictive AI method. In the optimization section, we use to methods. One is to mimic the traditional manual operation in data analyzing and regulation induction and preparation of schedules, in order to address the general and recurrent problems. The second method is to mimic the traditional manual operation in investigating the traffic status, and adjust the plan to implement temporary control strategies.In the implementation section, we use an unified model in adapting our AI optimization methods to all existing controlling systems in the two cities. And finally in the security check section, we check the generated paraments again if they meet all experience constraints and span of control.The final effect is that we dramatically improved the productivity of operators, and improved traffic signal control performance of the two cities.

Djordjevic:What is your standpoint how does AI can benefit the public and the communities? Now and in lets say 2025, as we mentioned previously?

徐甲:1.The Big Data and AI technologies will assist the planning and construction of the infrastructures in a better way. Intelligentized infrastructure will emerge in a larger number, which would play the role as hub among the vehicles and information terminals of passengers.2.AI-powered platforms will connect all the devices, infrastructures, processing all the data, and to optimize the utilization of the infrastructures. Passengers will have better experience during travelling, feel more convenience.3.Cooperative vehicle and infrastructures will spread in some area. Autonomous vehicle driving technology will be wider applied. Autonomous vehicle driving and shared mobility will combine, in the scene of auto charging and auto scheduling.4. The AI-powered mobility service will be more personal, providing more precise travel guidance, travel reservation, with connecting the shared mobility with intelligent infrastructures.

Djordjevic:Before we go to the questions from the public, I would like to ask you to give one present to our public - in the form of advice. What would be the first step if the company would like to start their AI-powered transformation today? And the second one is why to go into this process today and not tomorrow or in the near future?

徐甲:The first thing is to in-depth understand your business model, data basis and the capability of AI technology, also the capability boundaries as mentioned before.The second one is simple, that is because the productivity. If properly used AI techniques can bring significant productivity in comparison to the traditional methods, as a company, why not immediately?

主持人：您所在的公司——银江股份是如何实现AI驱动的？您和贵公司在实践AI议题时的体验是怎样的？

徐甲：主持人您好，银江股份在智慧交通的工程建设、软件开发和集成等领域有20多年的经验。在过去的20多年里，我们沉淀了大量的优质项目，也培育了相当多的客户，在获得客户信任的同时也对我们的服务提出了更高的要求。具体来说，客户需要我们科学、专业的服务以从全局角度解决城市交通路网复杂的实际问题，并同时能够量身定制方案从而满足各个城市不断变化的道路交通需求。正是在这样的背景下，公司提出并发起了AI驱动战略，以满足客户需求。总体而言，我们的公司正是在经历AI转型与变革的那一类公司。关于推行AI的体验，我想我们最重要的经验就是永远把技术的工业实用性放在第一位，首先要知道AI的能力和该能力的边界是什么，才可能将AI的技术用在合适的地方；其次是要提供客户能够负担的AI技术，包括所需要的数据和算力成本。

主持人：亲爱的徐博士，您所在的国家有42个人口超过两百万的城市。我甚至无法想象这些数字会给现实中的问题带来多少指数级的复杂度，因此我非常想和您来聊一聊关于交通、运输和出行服务的议题。我想请您全面介绍一下AI如何解决交通中的问题，以及面临的主要挑战是什么？最好能向我们多介绍一些夯实的案例？

徐甲：确实，在我所居住的城市——杭州，拥有超过一千万的人口，机动车保有量超过300万辆，日间最大机动车在途量达到约30万辆。除了人口规模这个因素之外还有很多原因导致城市交通治理成为一个难题。杭州是省会城市，有很多国内、国际的大型活动，同时杭州是国际知名的旅游城市，西湖景区闻名遐迩，这些因素带来的复杂场景是第二个挑战。我们所面对的城市路网包含大约2000个信号控制交叉路口，这其中的相当一部分同时具有大流量、不均衡、高动态的特点，这是我们面临的第三个挑战。最后，还有一些工程上的挑战，比如多源数据的采集处理，路口渠化的模型化管理等。关于我们使用AI技术在解决的交通问题，我想举个例子，就是通过交通信号优化管理缓解城市交通拥堵的问题，这个技术在杭州和南昌都得到了应用。这个复杂过程大体上可以分为感知、预警、优化、执行、安全多个环节。感知环节主要在于数据的处理，我们通过AI方法判断数据的可靠性，将直接、可靠的数据传递到后续环节；预警环节重点在于对趋势的判断，而不是状态的判断，我们使用了各种预测方法；优化的环节我们通过两套方法，第一套方法模拟传统人工方式中的分析历史数据、总结规律和制定时刻表计划的过程，处理普遍性的问题；第二套方法模拟传统人工方式中分析实时局势，采取临时策略的过程，处理临时性问题；执行的环节重点在于使用统一模型适配这两个城市所有的信号系统底层设计；安全环节在于再次确认算法生成的方案中所有参数的有效性和控制幅度。最终的效果是我们显著地提高了人工的处理时效和生产力，也改善了上述两个城市的交通信号控制状况。

主持人：你的观点是什么？人工智能如何使公众和社区受益？现在就让我们设想到2025年，就会像我们之前提到的那样了吗？

徐甲：1、 大数据和AI辅助技术会让基础设施的规划设计更加合理，智能化的基础设施将大量涌现，对接那时的交通工具和信息终端；

2、 AI驱动的精细化管控与优化会让基础设施的利用率进一步提高；

3、 车路协同技术将在一些地区推广，自动驾驶技术将得到更多应用；

4、 AI驱动的出行服务将提供更加个性化、更精准的出行指引、出行预约等服务，串联起共享出行工具和智能基础设施；

主持人：如果公司想转型为AI驱动的模式，首先应该做什么事？为什么今天要立即做AI转型，而不是等到明天再做？

徐甲：首先是深度了解自己的业务模型与数据基础，以及如前所述，了解AI方法的能力范围和能力边界。第二个问题很简单，那就是考虑到AI带来的生产力提升。如果正确使用AI技术，与传统方法相比，可以显著提高生产力，降本提效，所以作为一个公司来说，为何要等到明天？