A Fast Heuristic for Finding Near-Optimal Groups for Vehicle Platooning in Road Networks

被引:2
|
作者
Steinmetz, Dietrich [1 ]
Burmester, Gerrit [1 ]
Hartmann, Sven [1 ]
机构
[1] Tech Univ Clausthal, Dept Informat, Clausthal Zellerfeld, Germany
来源
DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2017, PT II | 2017年 / 10439卷
关键词
D O I
10.1007/978-3-319-64471-4_32
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Grouping vehicles into platoons with short distance can reduce fuel consumption up to 21% [1] and improve capacity of roads. The Vehicle Platooning Problem deals with route planing to form platoons and therefore minimize the overall costs of all considered vehicles. This article is focused on the subject to find groups with most fuel savings potential in acceptable time. We propose a novel spatial grouping algorithm to determine near-optimal groups. Our approach uses fast geometrical heuristics, consisting of direction-comparison, a modified version of a geometric-median-calculation and a comparison of intersections areas between two vehicles respectively. For evaluations is same-start unlimited ILP (SSU ILP) used to solves the Vehicle Platooning Problem to get the optimal solution. Driving in found platoons saves round about 2% to 3% fuel in average compared to the sum of particular shortest paths of the vehicles. The algorithm is tested in simulations on randomly created vehicles on different graphs with the size of 5.000, 10.000 40.000 and edges and round about 0.5 times nodes respectively. The performance is evaluated and the results are compared to the total possible amount of savings.
引用
收藏
页码:395 / 405
页数:11
相关论文
共 50 条
  • [31] On the hardness of finding near-optimal multicuts in directed acyclic graphs
    Bentz, Cedric
    THEORETICAL COMPUTER SCIENCE, 2011, 412 (39) : 5325 - 5332
  • [32] Finding near-optimal build orientations for shape deposition manufacturing
    Gupta, SK
    Tian, Q
    Weiss, L
    MACHINING IMPOSSIBLE SHAPES, 1999, 18 : 208 - 216
  • [33] Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms
    Acharya, Jayadev
    Diakonikolas, Ilias
    Hegde, Chinmay
    Li, Jerry
    Schmidt, Ludwig
    PODS'15: PROCEEDINGS OF THE 33RD ACM SYMPOSIUM ON PRINCIPLES OF DATABASE SYSTEMS, 2015, : 249 - 263
  • [34] Optimal and Near-Optimal Resource Allocation Algorithms for OFDMA Networks
    Lin, Yuan-Bin
    Chiu, Tai-Hsiang
    Su, Yu T.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2009, 8 (08) : 4066 - 4077
  • [35] A fast near-optimal algorithm for approximation of polygonal curves
    Kolesnikov, A
    Fränti, P
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITON, VOL IV, PROCEEDINGS, 2002, : 335 - 338
  • [36] Fast and Near-Optimal Guidance for Docking to Uncontrolled Spacecraft
    Ventura, Jacopo
    Ciarcia, Marco
    Romano, Marcello
    Walter, Ulrich
    JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2017, 40 (12) : 3138 - 3154
  • [37] Near-optimal dynamic trajectory generation and control of an omnidirectional vehicle
    Kalmár-Nagy, T
    D'Andrea, R
    Ganguly, P
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2004, 46 (01) : 47 - 64
  • [38] Whether to Charge an Electric Vehicle or Not? A Near-Optimal Online Approach
    Deng, Ruilong
    Liang, Hao
    2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [39] Unraveling protein interaction networks with near-optimal efficiency
    Lappe, M
    Holm, L
    NATURE BIOTECHNOLOGY, 2004, 22 (01) : 98 - 103
  • [40] Near-Optimal Location Tracking Using Sensor Networks
    Sharma, Gokarna
    Krishnan, Hari
    Busch, Costas
    Brandt, Steven R.
    PROCEEDINGS OF 2014 IEEE INTERNATIONAL PARALLEL & DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW), 2014, : 738 - 747