A rail transit simulation system for multi-modal energy-efficient routing applications

被引:6
|
作者
Wang, Jinghui [1 ]
Ghanem, Ahmed [2 ]
Rakha, Hesham [2 ]
Du, Jianhe [2 ]
机构
[1] Flo Artificial Intelligence Inc, Oakland, CA USA
[2] Virginia Tech, Transportat Inst, Ctr Sustainable Mobil, 3500 Transportat Res Plaza, Blacksburg, VA 24061 USA
关键词
Eco-routing; energy consumption; multi-modal; rail transit; simulation; smart mobility; FUEL CONSUMPTION MODEL; VEHICLE DYNAMICS MODEL; DIESEL;
D O I
10.1080/15568318.2020.1718809
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The paper develops a continuous rail transit simulator (RailSIM) intended for multi-modal energy-efficient routing applications. RailSIM integrates sophisticated train dynamics and energy models to replicate train motion and energy consumption behavior, respectively. The simulator is calibrated using an off-line optimization procedure to match preprogramed railway schedules by optimizing three model parameters, namely; the segment target speed, the average deceleration level, and the brake force adjustment factor. The objective of the calibration procedure is to match the simulated and actual average running speed for each station-to-station pair. Upon calibration, RailSIM is applied to the Greater Los Angeles area and validated at both the instantaneous and aggregated levels. Results demonstrate that RailSIM is able to produce realistic train dynamics and energy consumption estimates producing a comfortable ride while simultaneously matching the railway schedule. RailSIM is also demonstrated to capture the impact of track gradient on energy outputs. The results also indicate that a perfect match to empirical energy estimates is achieved at an average grade of 1.8%, which is a reasonable approximation of the average track gradient of the testing area. The sensitivity of RailSIM to some of the metro rail parameters is also discussed to account for its applicability to rail transit systems in other cities. Finally, a pilot test of RailSIM implementation in the higher-level multi-modal eco-routing system is performed to demonstrate RailSIM's feasibility of supporting energy-efficient travel.
引用
收藏
页码:187 / 202
页数:16
相关论文
共 50 条
  • [41] A reference architecture for the American Multi-Modal Energy System enterprise
    Thompson, Dakota J.
    Farid, Amro M.
    JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2023, 36
  • [42] Energy-efficient operation of rail vehicles
    Liu, RF
    Golovitcher, IM
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2003, 37 (10) : 917 - 932
  • [43] An Energy Efficient Optimized Control Algorithm for Urban Rail Transit System
    Zhang Hongguang
    Song Mengxiao
    Zhang Minxuan
    PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 10222 - 10226
  • [44] Towards Two-point Neuron-inspired Energy-efficient Multi-modal Open Master Hearing Aid
    Raza, M.
    Adetomi, A.
    Ahmed, K.
    Hussain, A.
    Arslan, T.
    Adeel, A.
    INTERSPEECH 2023, 2023, : 688 - 689
  • [45] An energy-efficient cooperative multicast routing in multi-hop wireless networks for smart medical applications
    Jiang, Dingde
    Li, Wenpan
    Lv, Haibin
    NEUROCOMPUTING, 2017, 220 : 160 - 169
  • [46] Multi-modal Transit Station Planning Method Using Discrete Event System Formalism
    Choi, Jaewoong
    Kim, Bitnal
    Kang, Onyu
    Baek, Seonwha
    Shim, Yonghyun
    Choi, Changbeom
    MODEL DESIGN AND SIMULATION ANALYSIS, 2016, 603 : 49 - 64
  • [47] Integration of a multi-modal transit system for urban areas: A case study of Cochin city
    Sreelekshmi, S.
    Shaheem, S.
    EMERGING TRENDS IN ENGINEERING, SCIENCE AND TECHNOLOGY FOR SOCIETY, ENERGY AND ENVIRONMENT, 2018, : 171 - 178
  • [48] ENERGY EFFICIENT RAIL TRANSIT OPERATION.
    Eash, Ronald W.
    Transportation Research Record, 1978, (662) : 1 - 7
  • [49] An Integrated Approach for Energy-efficient Train Operation Considering Bidirectional Converter in Urban Rail Transit
    Li, Yanyan
    Xun, Jing
    Liu, Hao
    Mi, Jiayu
    Ji, Xiangyu
    2023 IEEE 26TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, ITSC, 2023, : 4663 - 4668
  • [50] Toward energy-efficient urban rail transit with capacity constraints under a public health emergency
    Huang, Kang
    Liao, Feixiong
    Rasouli, Soora
    Gao, Ziyou
    FRONTIERS OF ENGINEERING MANAGEMENT, 2024, : 645 - 660