"十五五"期间，随着世纪工程平陆运河的建设，以及六大科技创新工程的集中落地，中国正加速完善现 代化综合交通运输体系，向全面建成交通强国目标稳步迈进。 中国交通多项排名世界第一：拥有全球最大的高速铁路网、高速公路网和邮政快递网，每一天约1.8亿 人次跨区域出行，每一秒有6000个快件进入寄递渠道。 从交通大国到2035年基本建成交通强国，"十五五"阶段是实现这一战略目标的关键时期。 交通运输部党组书记、部长刘伟近期在《求是》杂志撰文指出，完善现代化综合交通运输体系，是"十 五五"及今后一个时期推动交通运输高质量发展、加快建设交通强国的重大任务。它是以交通运输现代 化服务保障中国式现代化的战略任务，也是做强国内大循环、构建新发展格局的基础支撑；是培育发展 新质生产力、推动高质量发展的重要举措，也是满足人民群众对美好生活向往、促进全体人民共同富裕 的必然要求。 何为完善现代化综合交通运输体系？《财经》研究认为，安全、便捷、高效、绿色、经济是五大关键 词，它不仅是修路架桥，促进区域协同发展，更是通过前瞻性的布局与创新，为科技创新与实体经济高 质量发展铺设"快车道"。 具体而言，国家综合立体交通网要加快完善，铁路、公路 ...

2025.11. 24 本文字数：1867，阅读时长大约3分钟 作者 | 第一财经 李秀中 在"新运河时代"来临之际，作为"千河之省"的四川，也将全力突破水运瓶颈，三年内将投资210亿 元，贯通联通长江、嘉陵江、岷江和金沙江等境内主要河流，实现内畅外联的水运体系。 11月23日，四川发布《"畅通一条江"航运振兴发展集中攻坚三年行动方案（2025—2027年）》 （下称《行动方案》），到2027年，打通航道"卡点""堵点"取得突破，长江等级提升、嘉陵江提 效、岷江畅通、金沙江联通、渠江和涪江有序改造取得显著成效，实现"双提升、三增长、一降 低"。 四川全省现有通航河流176条，通航湖库147个，通航里程1.05万公里，位居全国第四，西部第一， 四级及以上航道里程达到1892 公里。全省现有港口18个，生产性码头泊位403 个，港口货物吞吐 能力10391万吨、集装箱吞吐能力250万标箱。 但是，四川省内河水运发展滞后、大而不强。水路货运量仅占全社会货运量的2.95%，较湖北省 （全国第６位）低22.6%、较江西省（全国第９位）低 3.9% 、较重庆市（全国第12位）低 13.4%。在综合交通运输中的地位不断弱化 ...

● 虽为 " 千河之省 " ，但内河水运却 " 大而不强 " ，水路货运量仅占全社会货运总量的 3.56% 四川虽为"千河之省"，但内河水运却呈现"大而不强"的特点，水路货运量仅占全社会货运总量的 3.56%，较同处长江上游的重庆低14.7%，较长江中游的湖北低23.8%。为补齐水运短板，今年四川提出 实施"畅通一条江"航运振兴发展行动。四川省航务海事管理事务中心相关负责人表示，此次《方案》的 出台，是对行动的进一步部署。下一步，四川将拓宽融资渠道，通过超长期特别国债、地方政府专项债 券及银行贷款等加强对符合条件水运项目和船舶建造的支持；加大"以电养航"支持力度，支持航道建设 养护；研究惠企政策，通过资源补偿、优化服务等惠企政策，吸引产业沿江布局。 （四川日报全媒体记者寇敏芳） 根据《方案》，四川将开展攻坚整江贯通联通、推动航道通行提效、推进港口整合集约、加快运输提质 增效、支撑高质量发展五大重点任务。其中，攻坚整江贯通联通方面，推动长江等级提升、嘉陵江提 效、岷江畅通、金沙江联通、渠江和涪江有序改造；推动航道通行提效方面，完善航道运行监测设施， 确保维护水深达标，完善调度运行，提升通航要素保障水平，强化水、 ...

在"新运河时代"来临之际，作为"千河之省"的四川，也将全力突破水运瓶颈，三年内将投资210亿元， 贯通联通长江、嘉陵江、岷江和金沙江等境内主要河流，实现内畅外联的水运体系。 11月23日，四川发布《"畅通一条江"航运振兴发展集中攻坚三年行动方案（2025—2027年）》（下称 《行动方案》），到2027年，打通航道"卡点""堵点"取得突破，长江等级提升、嘉陵江提效、岷江畅 通、金沙江联通、渠江和涪江有序改造取得显著成效，实现"双提升、三增长、一降低"。 四川全省现有通航河流176条，通航湖库147个，通航里程1.05万公里，位居全国第四，西部第一，四级 及以上航道里程达到1892 公里。全省现有港口18个，生产性码头泊位403 个，港口货物吞吐能力10391 万吨、集装箱吞吐能力250万标箱。 但是，四川省内河水运发展滞后、大而不强。水路货运量仅占全社会货运量的2.95%，较湖北省（全国 第６位）低22.6%、较江西省（全国第９位）低 3.9% 、较重庆市（全国第12位）低13.4%。在综合交通 运输中的地位不断弱化，已成为建设交通强省的明显短板。 不仅如此，航道通达通畅不足。高等级航道比例较低，里程占比仅为 ...

近日，记者在阜阳颍州港采访时，听到杨峰的手机不时响起，作为安徽阜阳颍州港务有限公司的总 经理，最近这两年，如何借着江淮运河的东风拓展业务，是他的重要工作之一。 这一切，随着引江济淮这一"世纪工程"的推进，迎来了重大转机。 颍州港位于沙颍河畔，作为淮河最大支流，沙颍河是皖北、豫东重要的水运通道。 "以前这边送货到长江，要先往南进入淮河，再向东经洪泽湖到京杭大运河，然后再往南从扬州进 入长江。如果是出海，从扬州顺流而下，总体运费还可以。但如果是到长江中上游，就要向西逆流而 上，相当于绕了一个大圈，水运费用就太高了。"杨峰说。 长期以来，受航道限制，阜阳水运相对式微，服务范围有限，服务形式也比较单一。以颍州港为 例，此前只能运送建材、粮食等大宗散杂货，对地方经济社会发展助力有限。 安徽，别称江淮大地，长江、淮河一南一北穿境而过，但因中部江淮分水岭的存在，两大水系在安 徽境内始终隔岭相望、各自奔流。 2016年12月29日，引江济淮工程正式开工建设，该工程集供水、航运、生态综合效益于一身，贯通 后成为与京杭大运河平行的江淮第二通道，也被称为江淮运河。 2023年9月16日，江淮运河航道全线开通试运行，安徽水运历史被重 ...

Core Insights - The integration of artificial intelligence (AI) in transportation is transforming operational precision, reliability, and efficiency, as highlighted by the recent implementation guidelines from the Ministry of Transport and six other departments, aiming for a comprehensive smart transportation network by 2030 [1][2] Group 1: Implementation and Goals - The guidelines outline 16 specific tasks across four areas, focusing on technology supply and scenario empowerment, with a goal of achieving self-controlled key technologies and leading global standards by 2030 [1][2] - The establishment of a comprehensive transportation model is emphasized, which includes high-quality datasets, algorithm libraries, and toolchains to support the industry's intelligent transformation [2][3] Group 2: Efficiency Improvements - The implementation of smart traffic management systems is projected to enhance the efficiency of demonstration corridors by approximately 20% and improve emergency response efficiency by around 30% [3][4] - The digital transformation of transportation infrastructure is supported by AI through big data analysis and high-precision modeling, covering over 60,000 kilometers of demonstration corridors [3][4] Group 3: Application Scenarios - The guidelines deploy seven key areas for intelligent applications, including combined auxiliary driving, smart railways, and intelligent shipping, which will provide extensive testing grounds for new technologies and products [4][5] - The development of automated ports and intelligent navigation systems is accelerating, with 52 automated terminals established and applications in over ten domestic and international ports [4][5] Group 4: Infrastructure Support - The guidelines stress the importance of new infrastructure in supporting AI integration, focusing on computing power, data, and network capabilities [6][7] - The establishment of a comprehensive transportation big data center is prioritized to enhance data sharing and the creation of high-quality datasets, which are essential for AI model training and application [7]

Core Viewpoint - The integration of artificial intelligence (AI) with transportation is transforming production and lifestyle, enhancing precision, reliability, and efficiency in traffic management and infrastructure development [1] Group 1: Implementation and Goals - The Ministry of Transport and six other departments issued implementation opinions on "AI + Transportation," outlining 16 specific tasks across four areas, aiming for a fully advanced intelligent transportation network by 2030 with self-controlled core technologies [1][2] - The goal includes achieving a 20% increase in traffic efficiency and a 30% improvement in emergency response efficiency through intelligent monitoring and management systems [3] Group 2: Technological Development - The focus is on application technology breakthroughs, innovation in intelligent products, and the construction of a comprehensive transportation model, which will support the intelligent transformation of the industry [2] - The establishment of a transportation big model, which includes high-quality datasets and algorithm libraries, is crucial for promoting technological sharing and collaborative innovation [2] Group 3: Application Scenarios - The implementation opinions cover seven key areas for intelligent applications, including combined auxiliary driving, smart railways, and intelligent shipping, providing ample testing grounds for new technologies and products [4] - In the water transport sector, 52 automated terminals have been established, and intelligent systems are being applied in over ten domestic and international ports [4] Group 4: Infrastructure Support - The integration of AI in transportation relies on robust infrastructure, with specific deployments in computing power, data, and network capabilities to ensure effective support for intelligent systems [7] - The construction of a comprehensive transportation big data center is underway to enhance data sharing and the creation of high-quality datasets, which are essential for AI model training and application [7]

Core Viewpoint - The implementation of "Artificial Intelligence + Transportation" aims to enhance the efficiency and safety of transportation systems, with a comprehensive smart integrated transportation network expected to be fully advanced by 2030, featuring self-controlled key technologies and a leading global level [1][2]. Group 1: Key Initiatives and Goals - The recent policy document outlines 16 specific tasks across four areas, focusing on technology supply and scenario empowerment to drive the integration of AI in transportation [1][2]. - The establishment of a comprehensive transportation big model is emphasized, which will support the intelligent transformation of the industry by providing unified model capabilities [2][3]. Group 2: Technological Advancements - The integration of AI in transportation is expected to improve the efficiency of demonstration corridors by approximately 20% and emergency response efficiency by about 30% through advanced monitoring and control models [3]. - The digital transformation of transportation infrastructure is being supported by AI, with over 60,000 kilometers of demonstration corridors established, covering major national transportation networks [3]. Group 3: Application Scenarios - The policy identifies seven key areas for intelligent application, including combined auxiliary driving, smart railways, and intelligent shipping, which will provide rich testing grounds for new technologies and products [4][5]. - Significant advancements in water transport include the establishment of 52 automated terminals and the application of intelligent operating systems in over ten ports [4]. Group 4: Infrastructure Support - The policy outlines specific measures to enhance support in computing power, data, and network infrastructure, which are crucial for the deep integration of AI in transportation [6]. - A focus on building a comprehensive transportation big data center is highlighted, aiming to facilitate data sharing and the creation of high-quality datasets to enhance decision-making processes [6].

Core Viewpoint - The integration of artificial intelligence (AI) with transportation is transforming production and lifestyle, enhancing precision, reliability, and efficiency in traffic management and infrastructure development [1][2]. Group 1: Implementation and Goals - The Ministry of Transport and six other departments issued implementation opinions on "AI + Transportation," outlining 16 specific tasks across four areas, aiming for a fully advanced intelligent transportation network by 2030, with key technologies being self-controlled and at the forefront globally [1][2]. - The focus is on application technology breakthroughs, innovation in smart products, and the construction of a comprehensive transportation model to support the intelligent transformation of the industry [2][3]. Group 2: Efficiency Improvements - The integration of AI is expected to enhance the efficiency of demonstration corridors by approximately 20% and improve emergency response efficiency by around 30% through advanced traffic management models [3][4]. - In 20 demonstration areas for digital transformation, the total mileage of demonstration corridors exceeds 60,000 kilometers, covering major components of the national comprehensive transportation network [3][4]. Group 3: Application Scenarios - The implementation opinions cover seven key areas for intelligent applications, including combined auxiliary driving, smart railways, and intelligent shipping, providing ample testing grounds for new technologies and products [4][5]. - The development of automated ports and intelligent navigation systems is accelerating, with 52 automated terminals established and applications in over ten domestic and international ports [4][5]. Group 4: Infrastructure Support - The successful integration of AI in transportation relies on robust infrastructure, with specific deployments in computing power, data, and network capabilities to support the industry [7][8]. - The establishment of a comprehensive transportation big data center is underway to enhance data sharing and the creation of high-quality datasets, which are essential for AI model training and application [7][8].

Core Viewpoint - Sichuan has rectified 44,755 prominent ecological and environmental issues, reflecting a systematic approach to ecological protection over the past decade [1] Group 1: Environmental Rectification Efforts - Sichuan has undergone three rounds of central ecological environmental protection inspections since 2017, achieving full coverage of 21 cities [2] - The province has implemented a dynamic verification system to address public concerns, leading to significant improvements in issues such as solid waste encroachment and illegal dumping [2] - Specific examples include the cleanup of 194,800 cubic meters of waste in Ya'an and the establishment of a comprehensive river and lake supervision system [2][3] Group 2: Industrial Upgrading and Green Development - Sichuan is integrating environmental rectification with industrial green upgrades, optimizing industrial structures and transportation systems [4] - The province has eliminated over 670 outdated brick and tile production lines and reduced the number of restricted enterprises by over 30% compared to 2023 [4] - The industrial added value in the first half of the year grew by 7.3%, with green and low-carbon industries contributing over 30% [4] Group 3: Transportation Sector Developments - The transportation sector has seen growth in freight volumes, with rail and water transport increasing by 3.2% and 21.7% respectively [5] - Sichuan plans to pilot zero-carbon industrial parks and optimize the layout of hydrogen refueling and battery swapping stations to promote green logistics [5] - The province aims to create a new governance model that aligns ecological protection with high-quality economic development [5]