（一）学科基本情况

  北京交通大学系统科学一级学科由72886必赢官网牵头建设，具有博士和硕士学位授予权，是国家双一流学科，在历次全国一级学科评估中均排名第一或A+，在历次上海软科中国最好学科排名中均位列第一。

  学科特色：

  必赢71886网址登录系统科学学科立足于交通运输系统，利用系统科学的原理和方法，揭示交通运输及相关复杂系统的结构与功能关系、演化和调控规律，寻求复杂交通系统的最优控制方法与管理策略，为交通规划、设计与管理提供科学依据与方法支撑，并向相关复杂系统研究方向辐射扩展。

  历史沿革：

  1998年，获系统分析与集成二级学科硕士学位点授权；2000年，获系统理论二级学科硕士学位点授权；2003年，获系统分析与集成二级学科博士学位授予权；2005年，获系统科学一级学科博士学位授予权。2004年首次参加教育部组织的全国一级学科评估，就取得了与北京师范大学并列排名第一的好成绩（系统科学是北京师范大学的传统优势学科）；在2008/2012年,，系统科学一级学科在全国学科评估中蝉联第一。2016/2020年，系统科学一级学科在全国学科评估中获评A+。2017年，入选国家首批双一流学科建设名单（首轮建设评估获优秀）。2019、2020、2021、2022、2023年，软科中国最好学科排名中位列第一。2022年，再次入选国家双一流学科建设名单。

（二）学科定位与人才培养目标、学科方向与优势特色

  学科定位与目标：

  大力加强“智慧交通”一流学科领域建设，进一步提升学科综合实力。以系统科学为牵引，建设“系统科学+”学科群。优化学科建设资源配置方式，推进学科深度交叉融合，培育新的学科增长点，形成新的前沿学科方向，确保学科在国内的优势地位和国内外的影响力，力争进入世界一流行列，为服务国家重大战略需求作出突出贡献。

  学科方向与优势特色：

  立足行业、理工交叉。基于系统科学理论方法，坚持从复杂交通系统实践中提炼科学问题并将理论成果应用于解决实际问题。形成了优势学科交叉、理工融合、交通特色鲜明的学科建设模式。目前系统科学一级学科设置了如下四个特色鲜明的研究方向：

  （1）系统理论与复杂性

  着重于研究交通系统的基本性质与演化机理。研究道路交通流（涵盖自动驾驶车辆、人工驾驶车辆、非机动车、行人及其混合交通流）的动力学、非线性、混沌、相变、自组织等多种动态复杂特性；研究路网交通流的非线性、相变、多态、自组织等时空复杂特性；研究城市道路网络、轨道网络、多模式交通网络、以及城市群综合交通网络结构与流量的复杂性特征；研究城市交通需求的时空特性与演化机理；研究城市交通系统与空间形态协同演进机理；研究道路交通拥堵与网络交通拥堵的时空演化规律。

  （2）复杂交通系统建模与调控

  强调用整体论和还原论相结合的方法去分析、模拟交通系统，用控制理论去干预和控制交通系统的宏观涌现性行为。研究城市交通网络优化设计、资源配置、交通需求管理的优化模型与算法；研究复杂交通系统协同控制与智能调控的理论及应用；研究自动驾驶车辆、互联车队的控制理论与方法；构建城市多模式综合交通网络模型，研究交通运输系统鲁棒性及相关控制方法；研究数据驱动下的城市交通系统实时优化控制与决策方法以及轨道交通系统的先进控制理论与方法；研究轨道牵引的城市公共交通模式结构优化理论与方法；研究双碳目标导向的交通系统调控理论与方法。

  （3）综合交通系统分析与集成

  以系统理论为基础，以系统分析与集成技术为手段，通过对交通运输系统目标的分解、协调、综合、优化与实施，实现交通运输系统的功能优化。研究基于活动链的交通出行模式辨识、动态出行决策机制，发展混合交通出行行为分析理论；研究交通系统要素、结构与功能之间的关系与相互作用机理；研究城市多模式交通系统中不同模式之间的协同运行理论与方法；研究城市多维交通时空供需的自适应匹配方法；研究城市交通网络的韧性、可靠性分析理论与方法；研究常态与非常态事件下交通能力供给与出行需求耦合互动机制；研究复杂交通运输系统的仿真理论与方法；研究城市综合交通系统状态监测、运行控制与应急管控的集成应用。

  （4）大数据与智能系统

  主要运用系统科学的理论、方法和技术，研究大数据、人工智能、移动互联、自动驾驶、共享出行等新型运行环境下的复杂交通系统的整体性、涌现性、系统性与协同性；研究数据驱动的交通个体或群体自主知识获取与应用、思维与推理、问题决策与学习等理论，探索大规模、多模式、多层次智慧交通系统的推演与决策方法，指导交通大数据分析以及具有自组织与自适应性的交通系统智能行为；以5G、大数据、人工智能、机器学习、物联网等数字化技术为主导，探索自动驾驶、车联网、共享交通等新技术、新业态、新模式，研究大数据汇聚、管理、分析、智能计算与展现等各个环节的相关理论与技术方法。

（三）学科师资队伍情况

  本学科业已形成一个以国家基础科学研究中心、国家创新研究群体和教育部创新团队为基础，由学科首席教授领衔，长江学者特聘教授、杰青、优青、青长等为骨干的高层次师资团队。学科团队共有专任教师44人，其中博士生导师25人（占比56.8%），硕士生导师38人（占比86.4%），45岁以下青年教师30人（占比68.2%），所有教师均具有海外经历。其中国家高层次人才19人次，省部级人才15人次，是必赢71886网址登录高层次人才占比最高的团队。团队先后获评全国党建工作样板支部（2018）、全国教育系统先进集体（2019），第三批全国高校黄大年式教师团队（2023）和北京市优秀研究生指导教师团队（2023）。

（四）学科人才培养目标与培养质量。

  人才培养目标：

  培养数理基础扎实，掌握系统科学基本理论和交通运输工程基础知识，能熟练运用非线性系统理论、复杂性分析与集成等手段对复杂交通系统的建模、控制、优化与决策等进行深入研究，具备较强的理工学科交叉优势，具有较强的知识获取能力、学术鉴别能力、科学研究能力、学术创新能力、良好国际视野和专业实践能力，能够胜任教学、科研及管理工作的高层次创新拔尖人才。

  人才培养质量：

  学科以双一流建设方案和一流研究生教育建设计划为依据，发挥学校优势特色，构建了“优势学科交叉、特色平台支撑”人才培养新模式，相关成果获中国研究生教育协会研究生教育成果一等奖。2018年起，先后依托学校基础学科试点班（交通系统科学方向）和托詹天佑学院形成了系统科学与工程专业本研贯通的人才培养体系。团队已培养出包括长江学者特聘教授、杰青、优青/海外优青、青年长江学者、全国优秀博士学位论文获得者、全国一级学会优秀博士论文获得者等在内的一大批创新拔尖人才。基于此，交通系统科学与工程团队获评2023年度北京市优秀研究生指导教师团队。

（五）学科科研水平及学科平台情况

  科研水平：

  学科科研实力雄厚，水平持续提升。主持承担了国家首个城市交通领域973 计划项目、国家自然科学基金委创新研究群体、国家重点研发计划课题及教育部创新团队等重大科研项目100余项。面向国际科学前沿和交通强国重大战略需求，2022年牵头申报并获批国家自然科学基金委基础科学中心项目“未来城市交通管理”，为国内交通系统领域首个基础科学中心项目，具有重大影响。学科在领域顶级期刊发表论文500余篇，获国家发明专利80余项，出版专著20余部，制订了多项国家、行业标准。成果被国内外众多科技媒体和著名学者予以高度评价并引出了一系列后续研究，多名成员连续多年入选 Elsevier 中国高被引学者，显著提升了我国在本领域的国际学术地位和影响力。相关成果先后获国家 自然科学奖二等奖（2011）、教育部自然科学一等奖（2009/2014/2018）、教育部科技进步一等奖（2009/2022）、其他省部级和一级学会奖励 20余项。本学科近五年来取得的代表性科技成果如下:

  （1）大城市交通网络瓶颈识别与综合管控关键技术。突破了大城市综合交通数库及模型库构建技术难题，创立了大城市交通网络瓶颈识别与一体化需求预测技术，攻克了大城市交通网络综合智能管控技术体系，研发了交通数据融合与存储、网络瓶颈识别与预测、综合智能管控等3大类核心技术产品，形成了大城市交通网络瓶颈识别与综合管控重大技术体系创新，在国内300余个城市以及13个“一带一路”国家得到推广应用，累计产生经济效益62亿元。成果由本学位点教师团队联合易华录、青岛海信、千方科技等单位科研团队共同完成，获教育部高等学校科学研究优秀成果（科学技术）奖一等奖。

  （2）复杂系统输运过程的重构方法、严格可控性理论与实证研究。针对如何通过有限数据来高效推断决定复杂系统演化的全部因素这一国际公认难题，提出了面向复杂系统输运过程的普适性重构方法，实现了对复杂系统相互作用结构和强度的高效重构；针对如何有效识别复杂系统输运过程的关键因素并进行有效调控这一国际公认难题，提出了基于相互作用结构和强度的复杂系统严格可控性理论，能够精确识别任意结构复杂系统输运过程的关键控制因素集；将上述理论和方法成功应用于两类典型的复杂交通系统（城市道路与轨道交通系统）研究中，对两类系统进行了分析、调控及应用研究，显示出理论成果指导复杂输运系统调控实践的重要作用。成果由本学位点教师团队联合北京师范大学、北京航空航天大学等单位科研团队共同完成，获北京市科学技术奖自然科学奖二等奖。

  （3）城市轨道交通在线客流控制。针对大城市轨道交通的高峰时段客流控制问题开展研究，设计了基于实时需求信息的客流控制策略。该成果于2023年发表在《运筹学》（Operations Research）上，并被选为当期的两篇亮点论文（Featured Article）之一。

  （4）驾驶行为对中国未来交通减排的影响。学科团队与浙江大学智能交通研究所、英国帝国理工学院交通研究中心团队合作，针对激进驾驶行为开展标准化建模，量化分析激进驾驶行为所产生的额外排放并预测演化趋势。成果于2023年7月3日发表在《自然-可持续》（Nature Sustainability）上。并受邀通过研究简报（Research Briefing）的形式同步发表期刊亮点论文，题目为“激进驾驶行为对中国交通排放的影响（Impacts of aggressive driving on transport emissions in China）”。期刊编辑评价：“该工作是对已有研究的重要补充，解析了人类日常行为对可持续性的重大影响”。

  学科平台：

  本学科依托“先进轨道交通自主运行”全国重点实验室（原轨道交通控制与安全国家重点实验室）、综合交通运输大数据应用技术交通运输行业重点实验室、综合交通运输理论交通运输行业重点实验室、智慧弹性交通联合实验室、交通系统科学与工程创新引智基地、高速铁路高效运营与安全保障创新引智基地、信息与交通运筹学创新引智基地等科研平台开展相关教学与科研活动。

（六）学科国内外影响力、社会服务与建设成效

  国内外影响：

  经过多年的建设与发展，本学科取得了一系列重要研究成果，并被国内外众多著名学者和主流科技媒体高度评价。成果不仅对系统科学的学科发展具有重要作用，而且具有很强的应用价值，显著提升了学科在本领域的国内外学术地位和学术影响力。先后获国家自然科学二等奖1项、省部级一等奖9 项、其他省部级和一级协会奖励20余项，并有多项成果获国家及北京市领导人批示。学科团队成员担任一系列重要学术兼职。主要包括：管理科学与工程学会理事长、中国系统工程学会等多个学会副理事长、交通+人工智能深度融合委员会主席团主席、国务院系统科学学科评议组召集人等；俄罗斯自然科学院外籍院士，英国IET会士，Trans.Res.B、系统工程理论与实践等30余个重要期刊主编、副主编或编委等。

  社会服务：

  学科团队注重理论研究成果的落地实践、服务社会。与北京市交通发展研究院、易华录、青岛海信、千方科技等单位通力合作，在成果的转化应用、服务社会方面成效显著。

  （1）研发了智慧城轨线网仿真与管控平台，长期应用于北京市城市轨道交通的各种复杂业务场景，为北京市轨道交通的常态化运营、以及疫情下的轨道交通管控提供了科学决策，并在济南、南京、杭州等城市推广应用。

  （2）创建了面向突发事件的交通管控方法，形成的监测-研判-诱导-控制-组织-调度核心方法体系，提升了大城市交通应急处置能力。为交通运营部门、交通运输企业及公众提供了应急信息与辅助决策支持。

  （3）攻克了特殊需求下多方式交通协同组织技术，成果应用于北京市交通委、北京易华录、千方科技等单位，有力支撑了国庆70周年、“一带一路”国际合作高峰论坛、厦门金砖国家峰会、杭州G20峰会、纪念抗战胜利70周年等重大活动期间城市交通系统的平稳运行。

  （4）攻克了数据与模型双驱动的路网运行指数预测等技术难题，与千方科技合作，通过微信公众号向全国发布春节、五一、国庆等重大节假日交通研判报告，在央视《新闻直播间》播出和央视《新闻联播》头条报道。

  建设成效：

  在学科团队的共同努力下，必赢71886网址登录的系统科学一级学科建设成效显著。在已完成的前五轮全国一级学科评估中均排名第一或获评A+，在历次上海软科中国最好学科排名中均位列第一。2012年获评北京市重点一级学科，2017年入学首批国家双一流学科建设名单，并在首轮建设评估中获优，2022年再次入选国家双一流学科建设名单。

Systems Science – A First-Level Discipline at Beijing Jiaotong University

1. Discipline Overview 

The first-level discipline of Systems Science at Beijing Jiaotong University is led by the School of Systems Science. The discipline holds both doctoral and master's degree conferral rights and is recognized as a "Double First-Class" discipline at the national level. It has consistently ranked first or received an A+ rating in past national first-level discipline evaluations and has maintained the top position in ShanghaiRanking’s Best Chinese Subjects Ranking.

Disciplinary Features: 

The Systems Science discipline at Beijing Jiaotong University focuses on transportation systems. By applying the principles and methods of systems science, the discipline seeks to uncover the structural and functional relationships, evolution, and regulatory patterns of transportation and related complex systems. It aims to identify optimal control methods and management strategies for complex transportation systems, thereby providing scientific foundations and methodological support for transportation planning, design, and management. The discipline also extends its research foci to other complex systems.

Historical Development:

In 1998, the university was granted the right to confer master's degrees in the second-level discipline of System Analysis and Integration. In 2000, it received authorization to confer master's degrees in the second-level discipline of Systems Theory. In 2003, it was granted the doctoral degree conferral right for the second-level discipline of System Analysis and Integration. In 2005, it gained the right to confer doctoral degrees in the first-level discipline of Systems Science.

During the first national first-level discipline evaluation organized by the Ministry of Education in 2004, Beijing Jiaotong University tied for first place with Beijing Normal University (where Systems Science is their traditionally strong discipline). The discipline maintained its first-place ranking in the 2008 and 2012 national evaluations. In 2016 and 2020, it received an A+ rating in the national discipline evaluations. In 2017, the discipline was selected in the first round of the national "Double First-Class" initiative. From 2019 to 2023, it ranked first in ShanghaiRanking's "Best Chinese Subjects Ranking". In 2022, the discipline was once again included in the national "Double First-Class" discipline development initiative.

2. Discipline Positioning and Talent Fostering Objectives, Discipline Directions and Advantages

Discipline Positioning and Objectives:

Our objective is to enhance the development of the "Smart Transportation" first-class discipline and grow its comprehensive strength: Leading by Systems Science, to develop a "Systems Science+" cluster of related disciplines; To optimize the allocation of resources for discipline development, promote deep interdisciplinary integration, cultivate new growth points, and establish cutting-edge disciplinary directions. The discipline aims to maintain a leading position domestically while expanding its global influence, and make significant contributions to meeting the country's major strategic needs.

Discipline Directions and Advantages:

The discipline is grounded in the transportation industry and fosters interdisciplinary integration between science and engineering. It involves extracting scientific problems from the practical complexities of transportation systems and applying theoretical outcomes to solve real-world issues. This approach has led to the development of a unique discipline construction model characterized by interdisciplinary collaboration, the integration of science and engineering, and a distinct focus on transportation. Currently, the first-level discipline of Systems Science at Beijing Jiaotong University is structured around four distinct research directions:

1. Systems Theory and Complexity

This direction emphasizes the study of the fundamental properties and evolutionary mechanisms of transportation systems. It investigates various dynamic and complex characteristics, including the dynamics, nonlinearity, chaos, phase transitions, and self-organization of traffic flows (covering autonomous vehicles, human-driven vehicles, non-motorized vehicles, pedestrians, and mixed traffic flows). It explores the spatiotemporal complexity of traffic flows in road networks, as well as the structural and flow complexity of urban road networks, rail networks, multimodal transportation networks, and integrated transport networks in metropolitan areas. Furthermore, research also includes the spatiotemporal characteristics and evolution of urban traffic demand, the co-evolution of urban traffic systems and spatial forms, and the spatiotemporal dynamics of road and network traffic congestion.

2. The Modeling and Regulation of Complex Transportation Systems

This direction focuses on the integration of holistic and reductionist approaches to analyze and simulate transportation systems. It applies control theory to intervene in and regulate the macro-level emergent phenomena of these systems. Research areas include the optimization models and algorithms for urban traffic network design, resource allocation, and traffic demand management; theories and applications of collaborative control and intelligent regulation in complex transportation systems; control theories and methods for autonomous vehicles and connected vehicle fleets; and modeling of multimodal urban transportation networks. Further studies focus on the robustness of transportation systems and related control methods, real-time optimization control and decision-making methods for urban traffic systems driven by data, and advanced control theories for rail transportation systems. Theoretical and methodological studies also explore the optimization of structure in rail-guided urban public transportation modes and traffic system regulation oriented toward carbon neutrality goals.

3. Comprehensive Transportation System Analysis and Integration

Building on systems theory and utilizing system analysis and integration techniques, this direction seeks to optimize the functionality of transportation systems through the decomposition, coordination, integration, optimization, and implementation of transportation system goals. Research areas include travel mode identification based on activity chains, dynamic travel decision-making mechanisms, and the development of theories for analyzing mixed travel behaviors; the exploration of relationship and interaction mechanism between the elements, structure, and function of transportation systems; the study of coordination theories and methods for the multimodal transportation system; the theories and methods for analyzing the resilience and reliability of urban transportation networks. This research direction also explores the adaptive matching of urban transportation supply and demand across spatiotemporal dimensions, as well as the coupling and interaction mechanisms between transportation capacity and travel demand under normal and abnormal events. Additionally, it develops simulation theories and methods for complex transportation systems and investigates the integrated application of state monitoring, operational control, and emergency management within urban transportation systems.

4. Big Data and Intelligent Systems

This direction primarily applies systems science theories, methods, and technologies to study the holistic, emergent, systematic, and synergistic behaviors of complex transportation systems in new operational environments such as big data, artificial intelligence, mobile connectivity, autonomous driving, and shared mobility. Research focuses on data-driven theories of autonomous knowledge acquisition, application, reasoning, decision-making, and learning by individuals or groups in transportation systems. The aim is to explore the modeling and decision-making methods for large-scale, multimodal, and multi-level smart transportation systems, guiding big data analysis in transportation and the intelligent behaviors of self-organizing and adaptive transportation systems. Additionally, this research direction explores new technologies, business models, and paradigms related to autonomous driving, vehicle networking, and shared mobility, with a focus on the theoretical and technical methods involved in the collection, management, analysis, intelligent computation, and presentation of big data, leveraging 5G, big data, AI, machine learning, and IoT technologies.

3. Faculty Composition

The discipline has developed a high-level faculty team, anchored by the National Basic Science Research Center, the National Innovation Research Group, and the Ministry of Education's Innovation Team. The faculty is led by a Chief Professor and includes distinguished scholars such as Changjiang Scholars, National Outstanding Young Scientists, Excellent Young Scientists, and Young Changjiang Scholars, forming the backbone of the team.

The team includes 44 full-time faculty members, with 25 Ph.D. supervisors (56.8%) and 38 master's supervisors (86.4%). Notably, 30 faculty members are under 45 (68.2%), all with international education and research experience. The team includes 19 national high-level talents and 15 provincial or ministerial talents, making it the team with the highest proportion of high-level talent at Beijing Jiaotong University. The team has been awarded several prestigious awards, including the National Model Party Branch for Education (2018), the National Advanced Collective in the Education System (2019), the third batch of the National Huang Danian-Style Faculty Teams (2023), and the Beijing Outstanding Graduate Supervisor Team (2023).

4. Professional Training Objectives and Outcome

Professional Training Objectives:

The objective of the professional training is to develop individuals with a solid foundation in mathematics and physics, who are well-versed in the fundamental theories of systems science and the basic knowledge of transportation engineering. These individuals should be proficient in applying nonlinear systems theory, complexity analysis, and integration techniques to conduct in-depth research on the modeling, control, optimization, and decision-making of complex transportation systems. They should possess strong interdisciplinary strengths in science and engineering, along with exceptional abilities in knowledge acquisition, academic discernment, scientific research, and scholarly innovation. Furthermore, they should have a broad international perspective and professional practical skills, equipping them to excel in high-level roles in teaching, research, and management.

Professional Training Outcome:

Based on the Double First-Class Initiative and the First-Class Graduate Education Program, the discipline has leveraged the university’s unique strengths to develop a new model of talent fostering characterized by interdisciplinary integration and platform support. This approach has won the first prize in graduate education achievements from the China Graduate Education Association. Since 2018, the discipline has developed a talented individual training system integrating undergraduate and graduate education in systems science and engineering, supported by the university's basic discipline pilot classes (with a focus on transportation systems science) and the Jeme Tienyow Honors College. The team has nurtured many top-level innovative talents, including Changjiang Scholars, National Outstanding Young Scientists, Excellent Young Scientists, recipients of the National Excellent Doctoral Dissertation Award, and awardees from national-level academic societies. As a result, the team was named the Beijing Outstanding Graduate Supervisor Team for 2023.

5. Research Outcome and Discipline Platforms

Research Outcome:

The discipline possesses strong research capabilities, with a consistently improving level of academic excellence. It has led over 100 major projects, including the first national 973 Program project in urban transportation, the National Natural Science Foundation of China (NSFC) Innovation Research Group, key projects under the National Key Research and Development Program, and the Ministry of Education Innovation Teams. In 2022, the discipline led the successful application for the NSFC Basic Science Center project "Future Urban Traffic Management", the first of its kind in the domestic transportation field, with significant influence. The discipline has published over 500 papers in top international journals, obtained over 80 national invention patents, authored more than 20 monographs, and developed multiple national and industry standards. Its results have been widely praised by international scholars and scientific media, sparking follow-up research, with many members consistently listed as Elsevier Highly Cited Chinese Scholars, significantly elevating China's academic standing and influence in this field.

The discipline has received numerous awards, including the National Natural Science Award (Second Prize, 2011), the Ministry of Education Natural Science Award (First Prize, 2009/2014/2018), the Ministry of Education Science and Technology Progress Award (First Prize, 2009/2022), and over 20 other provincial and ministerial awards. Key achievements over the past five years include:

1. Key Technologies for Bottleneck Identification and Integrated Control of Metropolitan Traffic Networks

This research tackled challenges in constructing a comprehensive traffic database and model repository for large cities. It developed technologies for bottleneck identification and integrated demand forecasting and overcame the complexities of intelligent control systems for urban traffic networks. The team created core products for data fusion and storage, bottleneck identification and prediction, and integrated intelligent control. These innovations have been applied in over 300 cities across China and 13 countries involved in the Belt and Road Initiative, generating economic benefits of 6.2 billion yuan. This research won the First Prize in the Ministry of Education’s Scientific Research Excellence Award (Science and Technology).

2. Reconstruction Methods, Strict Controllability Theory, and Empirical Research of Complex System Transport Processes

To address the internationally recognized challenge of efficiently inferring all factors that determine the evolution of complex systems from limited data, the team proposed a universal reconstruction method for complex system transport processes. This method enables the efficient reconstruction of the interaction structure and intensity within complex systems. Furthermore, to tackle the challenge of effectively identifying and controlling key factors in complex system transport processes, the study introduced a strict controllability theory based on interaction structure and intensity. This theory allows for the precise identification of the key control factor set in transport processes across systems of any structure. The proposed theory and methods were successfully applied to two typical complex transportation systems—urban road and rail transport systems. These applications demonstrated the significant role of the theoretical findings in guiding practical control measures for complex transport systems. This research was a collaborative effort among the faculty team of this academic discipline, Beijing Normal University, and Beihang University, and it won the Beijing Science and Technology Award for Natural Science (Second Prize).

3. Online Passenger Flow Control in Urban Rail Transit:

The team conducted substantial research on peak-hour passenger flow control in urban rail transit systems, designing control strategies based on real-time demand information. Research outcomes were published in the journal Operations Research in 2023 as one of the featured articles.

4. The Impact of Driving Behavior on Future Traffic Emissions in China:

In collaboration with Zhejiang University’s Intelligent Transportation Research Institute and Imperial College London’s Transportation Research Center, the team focused on conducting standardized modeling of aggressive driving behaviors. This study involved a quantitative analysis of the additional emissions resulting from such behaviors and predicted their evolutionary trends. The findings were published on July 3, 2023, in Nature Sustainability. The team was also invited to publish a highlighted article in the form of a Research Briefing titled “Impacts of Aggressive Driving on Transport Emissions in China.” The journal’s editor commented that “this work is a significant contribution to existing research, providing crucial insights into the substantial impact of human daily behaviors on sustainability.”

Research Platforms:

The discipline's teaching and research activities are supported by key laboratories and platforms, including the National Key Laboratory for Autonomous Operation of Advanced Rail Transit (formerly the State Key Laboratory of Rail Traffic Control and Safety), the Key Laboratory of Big Data Application Technology in Comprehensive Transportation under the Ministry of Transport, the Key Laboratory of Comprehensive Transportation Theory under the Ministry of Transport, the Joint Laboratory for Smart and Resilient Transportation, the Intelligent Transportation Systems and Engineering Talent Base, the Innovation Talent Base for High-Speed Railway Efficient Operation and Safety Assurance, and the Operations Research Base for Information and Transportation.

6. Domestic and International Influence of the Discipline, Social Services, and Achievements

Domestic and International Influence:

Over the years, the discipline has achieved a series of significant research outcomes, which have been highly recognized by renowned scholars and major science and technology media worldwide. These achievements have played a vital role not only in the development of system science as a discipline but also in their strong application value, greatly enhancing the discipline’s academic standing and influence both domestically and internationally. The team has won one National Natural Science Award (Second Prize), nine provincial and ministerial-level First Prizes, and over 20 other provincial and ministerial-level and first-tier association awards. Several of the accomplishments have received directives from national and Beijing city leaders. Team members hold key academic positions, including President of the Management Science and Engineering Society, Vice President of several associations like the China Society for Systems Engineering, Chair of the Transportation + Artificial Intelligence Integration Committee, Convener of the State Council’s Disciplinary Review Group for System Science, Foreign Academician of the Russian Academy of Natural Sciences, Fellow of the UK’s IET, and Editor, Associate Editor, or Editorial Board Member for more than 30 important journals such as Transportation Research Part B and System Engineering - Theory & Practice.

Social Services:

The discipline places strong emphasis on the practical application of theoretical research and serving society. The team has collaborated closely with institutions like the Beijing Transportation Institute, Eastone Technology, Hisense, and Qianfang Technology, yielding significant success in applying research outcomes and contributing to societal development.

1. Developed a smart rail transit network simulation and control platform, which has been applied to complex scenarios in Beijing’s urban rail transit system. This platform has supported decision-making for routine operations and pandemic control of the city's rail transit and has been promoted in cities like Jinan, Nanjing, and Hangzhou.

2. Created traffic control methods for emergency events, establishing a core method system for monitoring, assessment, guidance, control, organization, and scheduling, enhancing urban emergency response capabilities. This system provides emergency information and decision-making support to transportation operators, transportation enterprises, and the public.

3. Successfully developed multi-modal transportation coordination technologies tailored to specific needs. These results have been applied by the Beijing Municipal Commission of Transport, Eastone Technology, and Qianfang Technology, strongly supporting the smooth operation of city traffic systems during major events such as the 70th National Day celebrations, the Belt and Road Forum for International Cooperation, the BRICS Summit in Xiamen, the G20 Summit in Hangzhou, and the 70th Anniversary of the Victory in the War of Resistance against Japanese Aggression.

4. Solved key technological challenges related to road network operation index prediction driven by data and models. In collaboration with Qianfang Technology, released traffic assessment reports during major holidays like the Chinese New Year, Labor Day, and National Day via WeChat, which were featured in the CCTV News Live Room and headlined on CCTV’s News Broadcast.

Achievements:

With collective efforts, the discipline of System Science at Beijing Jiaotong University has achieved remarkable progress. It has ranked first or received an A+ in all five completed rounds of national first-level discipline evaluations and has consistently ranked first in ShanghaiRanking's Best Chinese Subjects Ranking. In 2012, it was rated as a Key First-Level Discipline in Beijing, entered the first batch of National Double First-Class Disciplines in 2017 (receiving an Excellent rating in the first round of evaluations), and was again included in the list of National Double First-Class Disciplines in 2022.