独家专访SCATS系统应用

赛文交通网 智能交通 智慧交管

SCATS系统由澳大利亚新南威尔士干线道路局自20世纪70年代开始研究，并于80年代初投入使用。目前，SCATS系统国内在上海、杭州、宁波、广州、苏州、石家庄、天津、三亚等30个城市26000多个路口使用了该系统。

SCATS系统在全球有三家分销商，ATC、QTC和TYCO。近日，赛文网独家专访了Aldridge Traffic Controllers Pty Ltd （ATC）总工程师Paul Milazzo先生，就SCATS系统与雷达、雷视感知设备的联动应用；系统最新的技术研发动态进行了交流。

（图片来源：ITS Australia）

赛文网：这两年，中国使用了很多新的交通采集设备，我们知道SCATS的控制算法是基于线圈设计的，针对视频和雷达、雷视的采集设备的使用，SCATS是否做了算法调整以应对实际使用需求？

A：SCATS算法最初是以线圈设计为基础的。SCATS系统的核心理念是，根据交通流量的变化来自动调整绿灯的时间，以提高道路的交通效率。

具体而言，当饱和度更高时，表示交通流量较大，车辆之间的时间间隔更短，SCATS系统会相应地增加绿灯时间，以更有效地处理高交通流量。这使得系统能够在各种交通情境下自动适应，确保道路交通的流畅与高效。

线圈在这个过程中发挥关键作用，因为它们提供了实时的车辆间距信息，帮助系统度量饱和度和交通流量状况。这一自适应性原则是SCATS系统的核心，即根据实时数据来智能地调整信号灯以适应不同的交通流量情况，从而提高道路交通效率。

然而，线圈传感器容易受到损坏，这可能对SCATS控制器的正常运行造成不利影响，因为控制器需要可靠的检测数据来进行交通管理。为了弥补线圈存在的潜在不足，SCATS系统采用了替代的检测方法，包括雷达和视频检测。

视频检测在应用上更加成熟，但它也可能受到遮挡等问题的影响，尤其在路口情况下。雷达检测则受到了低速情况下感知问题的困扰，但它是线圈的替代。

针对道路存在遮挡和低速交通问题，SCATS系统已经做出了相应的技术调整。

首先，如果使用线圈传感器并已经收集了足够长时间（至少3个月或最好6个月）的检测器数据，SCATS系统能够利用历史数据来替代当前对数据的需求，尤其是在当前数据不理想的情况下。

其次，SCATS系统引入了传感器替代机制，以解决传感器故障问题。例如，如果某个线圈出现故障，系统可以利用相邻线圈的数据来替代，以确保满足数据需求。

此外，SCATS系统团队已认识到数据融合的重要性，视其为提高系统性能的关键一步。数据融合是将传统传感器和新型传感器数据综合使用的能力，这有助于提供更全面的交通信息，从线圈、雷达到视频等多个数据源，以更好地理解交通状况。

马来西亚的交通控制路口数量可能达到数千个，并且由于维护问题，它们使用了如视频、激光雷达或雷达作为检测。视频检测设备在那里更为成熟和常见，但激光雷达和雷达同样也有效。

在印尼的应用中，似乎视频检测设备更常见，尽管有些地方仍在使用线圈检测技术。如果线圈是100%的检测参考，视频检测设备可能是另一个有效的选择。

赛文网：中国目前积极广泛的鼓励在交通领域的创新，您能分享一下SCATS系统近年来的创新吗？

A：第一项是SCATS Cornerstone，一款支持智能城市建设并支持协同ITS功能的软件。

SCATS Cornerstone是SCATS系统中的一项重要创新，它提供了统一关键的地图信息、车道拓扑结构数据，包括交叉口的物理布局、信号灯的相位和灯态数据。

这些数据标准采用ISO标准，确保了在全球范围内的交通管理系统之间的互操作性。SCATS Cornerstone的价值在于帮助交通管理系统更好地理解路口布局，这对于交通管理系统、建模应用程序以及联网和自动驾驶汽车的有效性能至关重要。

第二项，我们还有一项重要的创新点，即"SCATS Data Insights"，它将在SCATS系统的下一个主要版本中推出。

这个产品旨在使从SCATS系统中提取数据变得更加容易，为用户提供更全面的数据洞察。这将使其他人能够更好地查看、理解、使用这些数据，从而提供更多信息以改进交通管理。

第三项，SCATS系统计划在下一版本中提供云上服务，通过允许专家管理SCATS来支持没有交通工程资源的较小城市。

这一变化将带来多方面的好处。首先，它将为系统提供更多实时数据，从而更好地支持交通管理和车路协同。在国际上，这些数据通常被视为公共数据，允许第三方使用，但在中国，由于法律和共享机制的限制，存在一些障碍。

将交通管理系统迁移到云端的原因是多方面的。

首先，对于小型城市或地区，地区内信号机数量不多，投资角度考虑不需要建设独立的信号控制指挥中心，他们通常也缺乏交通工程专业知识和资源。

然而，这些城市也希望能够受益于像绿波控制等自适应交通控制系统的好处。因此，将系统移到云上的主要目的是降低这些地方对使用人员的技术门槛，使它们能够轻松享受自适应信号系统的优势，而无需自行承担系统管理和维护的复杂性。

此外，云端部署还可以解决人才和专业知识的问题。交通工程并不是一门广泛受欢迎的领域，如今愿意长期从事同一职业的人越来越少，导致交通工程师短缺。

因此，SCATS云计算系统的目标是为用户处理系统的复杂性，提供更便捷的专业服务。这意味着服务提供商可以为客户提供远程信号优化等服务，从而降低了专业技能的门槛，让更多地方受益于先进的交通管理技术。

这项创新已经在墨尔本等地进行了测试和演示，以评估市场对云端交通管理系统的接受度。此外，东南亚地区的小城市对此也表现出了兴趣，进一步证明了将信号控制系统迁移到云端的潜在机会。

第四，在一些亚洲城市，包括中国，非机动车辆在道路上的比例相当大，这对SCATS的算法运作方式构成了挑战。我们考虑将SCATS系统的应用范围扩展到包括行人、自行车和电动车等不同类型的交通工具。这对解决交通的公平性问题至关重要。

此外，开发SCATS的新南威尔士州交通局（TfNSW）将很快发布一个更直观、更基于地图的新用户界面。新的用户界面被称为SCATS控制中心，它提供了一个基于网络的道路网络视图，以及一组高度集成的数据和图形功能，以显示SCATS如何协调通道中的交叉口，提供绿色交通信号。

采访英文原文见下：

The SCATS system has been studied by the New South Wales Main Roads Authority in Australia since the 1970s and was put into use in the early 1980s. At present, the SCATS system has been used at over 26000 intersections in 30 cities in China, including Shanghai, Hangzhou, Ningbo, Guangzhou, Suzhou, Shijiazhuang, Tianjin, and Sanya.

SCATS system has three distributors worldwide, ATC, QTC, and TYCO. Recently, China_7its exclusively interviewed Mr. Paul Milazzo, Chief Engineer of Aldridge Traffic Controllers Pty Ltd (ATC), on the linkage application of SCATS system with radar and lightning perception equipment; The latest technological research and development trends of the system were discussed.

China_7its: In the past two years, China has used many new traffic collection devices. We know that the control algorithm of SCATS is designed based on coils. Has SCATS made algorithm adjustments to meet the actual usage needs of video, radar, and thunder vision collection devices?

A: The SCATS algorithm was initially based on coil design. The core concept of the SCATS system is to automatically adjust the green light time based on changes in traffic flow, in order to improve road traffic efficiency. 

Specifically, when the saturation is higher, it indicates a higher traffic flow and a shorter time interval between vehicles. The SCATS system will correspondingly increase the green light time to more effectively handle high traffic flow. This enables the system to automatically adapt to various traffic scenarios, ensuring smooth and efficient road traffic.

The coils play a crucial role in this process as they provide real-time vehicle spacing information, helping the system measure saturation and traffic flow conditions. This principle of self-adaptability is the core of the SCATS system, which intelligently adjusts signal lights to adapt to different traffic flow situations based on real-time data, thereby improving road traffic efficiency.

However, coil sensors are susceptible to damage, which may have an adverse impact on the normal operation of the SCATS controller, as the controller requires reliable detection data for traffic management. In order to compensate for the potential shortcomings of the coil, the SCATS system has adopted alternative detection methods, including radar and video detection. 

Video detection is more mature in applications, but it may also be affected by issues such as occlusion, especially in intersection situations. Radar detection is plagued by perception issues at low speeds but is an alternative option to coils. 

The SCATS system has made corresponding technical adjustments to address the issues of road obstruction and low-speed traffic.

Firstly, if coil sensors are used and detector data has been collected for a sufficient period of time (at least 3 months or preferably 6 months), the SCATS system can use historical data to replace the current demand for data, especially when the current data is not ideal. 

Secondly, the SCATS system introduces a sensor replacement mechanism to address sensor failure issues. For example, if a coil malfunctions, the system can replace it with data from adjacent coils to ensure that the data requirements are met.

In addition, the SCATS system team has recognized the importance of data fusion as a key step in improving system performance. Data fusion is the ability to integrate traditional and new sensor data, which helps provide more comprehensive traffic information from multiple data sources such as coils, radar, and video to better understand traffic conditions.

The number of traffic control intersections in Malaysia may reach thousands, and due to maintenance issues, they use methods such as video, LiDAR, or radar for detection. Video detection equipment is more mature and common there, but lidar and radar are also effective.

In Indonesian applications, it seems that video detection devices are more common, although coil detection technology is still used in some places. If the coil is a 100% detection reference, video detection equipment may be another effective choice. 

China_7its: China is currently actively and extensively encouraging innovation in the transportation field. Can you share the innovation of SCATS system in recent years?

A: The first item is SCATS Cornerstone, a software that supports the construction of smart cities and support Cooperative ITS functionality.

SCATS Cornerstone is an important innovation in the SCATS system, which provides unified key map information, lane topology data, including the physical layout of intersections, signal phase and light state data. 

These data standards adopt ISO standards to ensure interoperability between traffic management systems worldwide. The value of SCATS Cornerstone is to help the traffic management system better understand the intersection topology (the layout), which is critical to the effective performance of the traffic management system, modeling applications, and networking and autonomous vehicle.

Secondly, we also have an important innovation, namely "SCATS Data Insights", which will be launched in the next major version of the SCATS system. 

This product aims to make extracting data from SCATS systems easier and provide users with more comprehensive data insights. This will enable others to better view, understand, and use this data, thereby providing more information to improve traffic management. 

The third item is that the SCATS system plans to provide cloud based services in the next version to support smaller cities that do not have traffic engineering resources by allowing experts to manage SCATS for these smaller cities.

This change will bring multiple benefits. Firstly, it will provide the system with more real-time data to better support traffic management and vehicle road collaboration. Internationally, these data are usually considered public and allowed to be used by third parties, but in China, there are some obstacles due to legal and sharing mechanisms limitations. 

The reasons for migrating traffic management systems to the cloud are multifaceted.

Firstly, for small cities or regions where there are not many signal machines in the area, there is no need to build independent signal control command centers from an investment perspective. They often lack professional knowledge and resources in transportation engineering.

However, these cities also hope to benefit from the benefits of adaptive traffic control systems such as green wave control. Therefore, the main purpose of moving the system to the cloud is to lower the technical barriers for users in these areas, so that they can easily enjoy the advantages of adaptive signal systems without having to bear the complexity of system management and maintenance on their own.

In addition, cloud deployment can also solve the problem of talent and professional knowledge. Transportation engineering is not a widely popular field, and nowadays fewer and fewer people are willing to work in the same profession for a long period of time, leading to a shortage of transportation engineers.

Therefore, the goal of the SCATS cloud computing system is to provide users with more convenient professional services to handle the complexity of the system. This means that service providers can provide customers with services such as remote signal optimization, thereby lowering the threshold for professional skills and allowing more places to benefit from advanced traffic management technology.

This innovation has been tested and demonstrated in places such as Melbourne to evaluate the market's acceptance of cloud based traffic management systems. In addition, small cities in Southeast Asia have also shown interest in this, further demonstrating the potential opportunity to migrate signal control systems to the cloud. 

Fourthly, in some Asian cities, including China, the proportion of non motorized vehicles on the road is quite high, which poses a challenge to the algorithm operation of SCATS. We are considering expanding the application scope of the SCATS system to include different types of transportation such as pedestrians, bicycles, and electric vehicles. This is crucial for addressing the issue of fairness in transportation,

In addition Transport for New South Wales (TfNSW) who develop SCATS will soon be releasing a new user interface that is more intuitive and map based. The new User Interface is called SCATS Control Centre and provides a web based view of the road network and a highly integrated set of data and graphical features to show how well SCATS is coordinating intersections in a corridor to deliver the Green Wave of Traffic Signals.