Transportation Research Part C-emerging Technologies

Transportation Research Part C-emerging Technologies

交通运输研究 C 部分——新兴技术

  • 1区 中科院分区
  • Q1 JCR分区

期刊简介

《Transportation Research Part C-emerging Technologies》是由Elsevier Ltd出版社于1993年创办的英文国际期刊(ISSN: 0968-090X,E-ISSN: 1879-2359),该期刊长期致力于运输科技领域的创新研究,主要研究方向为工程技术-运输科技。作为SCIE收录期刊(JCR分区 Q1,中科院 1区),本刊采用OA未开放获取模式(OA占比0.0354...%),以发表运输科技领域等方向的原创性研究为核心(研究类文章占比99.42%%)。凭借严格的同行评审与高效编辑流程,期刊年载文量精选控制在343篇,确保学术质量与前沿性。成果覆盖Web of Science、Scopus等国际权威数据库,为学者提供推动工程技术领域高水平交流平台。

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投稿提示

Transportation Research Part C-emerging Technologies审稿周期约为 约12.0个月 约14.5周。该刊近年未被列入国际预警名单,年发文量约343篇,录用竞争适中,主题需确保紧密契合工程技术前沿。投稿策略提示:避开学术会议旺季投稿以缩短周期,语言建议专业润色提升可读性。

  • 工程技术 大类学科
  • English 出版语言
  • 是否预警
  • SCIE 期刊收录
  • 343 发文量

中科院分区

中科院 SCI 期刊分区 2023年12月升级版

Top期刊 综述期刊 大类学科 小类学科
工程技术
1区
TRANSPORTATION SCIENCE & TECHNOLOGY 运输科技
1区

中科院 SCI 期刊分区 2022年12月升级版

Top期刊 综述期刊 大类学科 小类学科
工程技术
1区
TRANSPORTATION SCIENCE & TECHNOLOGY 运输科技
1区

JCR分区

按JIF指标学科分区 收录子集 分区 排名 百分位
学科:TRANSPORTATION SCIENCE & TECHNOLOGY SCIE Q1 7 / 72

91%

按JCI指标学科分区 收录子集 分区 排名 百分位
学科:TRANSPORTATION SCIENCE & TECHNOLOGY SCIE Q1 8 / 72

89.58%

CiteScore

CiteScore SJR SNIP CiteScore 排名
CiteScore:15.8 SJR:2.86 SNIP:2.724
学科类别 分区 排名 百分位
大类:Engineering 小类:Automotive Engineering Q1 2 / 125

98%

大类:Engineering 小类:Civil and Structural Engineering Q1 7 / 379

98%

大类:Engineering 小类:Management Science and Operations Research Q1 6 / 207

97%

大类:Engineering 小类:Transportation Q1 9 / 141

93%

期刊发文

  • A new framework for mixed-user dynamic traffic assignment considering delay and accessibility to information

    Author: Hoang, Nam H.; Panda, Manoj; Vu, Hai L.; Ngoduy, Dong; Lo, Hong K.

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 146, Issue , pp. -. DOI: 10.1016/j.trc.2022.103977

  • A simulation-based metro train scheduling optimization incorporating multimodal coordination and flexible routing plans

    Author: Wang, Xingrong; Lv, Ying; Sun, Huijun; Xu, Guangtong; Qu, Yunchao; Wu, Jianjun

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 146, Issue , pp. -. DOI: 10.1016/j.trc.2022.103964

  • Real-time detection of abnormal driving behavior based on long short-term memory network and regression residuals

    Author: Ma, Yongfeng; Xie, Zhuopeng; Chen, Shuyan; Qiao, Fengxiang; Li, Zeyang

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 146, Issue , pp. -. DOI: 10.1016/j.trc.2022.103983

  • Improving short-term bike sharing demand forecast through an irregular convolutional neural network

    Author: Li, Xinyu; Xu, Yang; Zhang, Xiaohu; Shi, Wenzhong; Yue, Yang; Li, Qingquan

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 147, Issue , pp. -. DOI: 10.1016/j.trc.2022.103984

  • Analysis of the impact of maximum platoon size of CAVs on mixed traffic flow: An analytical and simulation method

    Author: Yao, Zhihong; Wu, Yunxia; Wang, Yi; Zhao, Bin; Jiang, Yangsheng

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 147, Issue , pp. -. DOI: 10.1016/j.trc.2022.103989

  • Coordinated lane-changing scheduling of multilane CAV platoons in heterogeneous scenarios

    Author: Liu, Qingquan; Lin, Xi; Li, Meng; Li, Li; He, Fang

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 147, Issue , pp. -. DOI: 10.1016/j.trc.2022.103992

  • A framework for strategic online en-route operations: Integrating traffic flow and strategic conflict managements

    Author: Liu, Ziang; Xiao, Gang; Mao, Jizhi

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 147, Issue , pp. -. DOI: 10.1016/j.trc.2022.103996

  • Network-level signal predictive control with real-time routing information

    Author: Lin, Shichao; Dai, Jingchen; Li, Ruimin

    Journal: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2023; Vol. 147, Issue , pp. -. DOI: 10.1016/j.trc.2022.104007