Advanced information feedback strategy in intelligent two-route traffic flow systems

被引:18
作者
Dong ChuanFei [1 ,2 ,3 ]
Ma Xu [1 ,2 ,4 ]
Wang BingHong [1 ,2 ,5 ,6 ]
机构
[1] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China
[2] Univ Sci & Technol China, Ctr Nonlinear Sci, Hefei 230026, Peoples R China
[3] Georgia Inst Technol, Sch Earth & Atmospher Sci, Atlanta, GA 30332 USA
[4] Syracuse Univ, Dept Phys, Syracuse, NY 13244 USA
[5] Shanghai Univ Sci & Technol, Res Ctr Complex Syst Sci, Shanghai 200093, Peoples R China
[6] Shanghai Acad Syst Sci, Shanghai 200093, Peoples R China
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
vehicle number feedback strategy; two-route selecting traffic flow; intelligent vehicle; cellular automaton model; CELLULAR-AUTOMATON MODEL; CONGESTION; TRANSITION; DYNAMICS; PHYSICS;
D O I
10.1007/s11432-010-4070-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we study dynamics of traffic flow with real-time information. The influence of a feedback strategy named vehicle number feedback strategy (VNFS) is introduced, in which we only calculate the vehicle number of first 500 route sites from the entrance. Moreover, the two-route traffic system has only one entrance and one exit, which is different from those in the previous work. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow, and simulation results by adopting this optimal information feedback strategy have demonstrated higher efficiency in controlling spatial distribution of traffic patterns than the other three information feedback strategies, i.e., TTFS, MVFS and CCFS.
引用
收藏
页码:2265 / 2271
页数:7
相关论文
共 26 条
[1]   DOES PROVIDING INFORMATION TO DRIVERS REDUCE TRAFFIC CONGESTION [J].
ARNOTT, R ;
DEPALMA, A ;
LINDSEY, R .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 1991, 25 (05) :309-318
[2]   DYNAMIC NETWORK MODELS AND DRIVER INFORMATION-SYSTEMS [J].
BENAKIVA, M ;
DEPALMA, A ;
KAYSI, I .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 1991, 25 (05) :251-266
[3]   SELF-ORGANIZATION AND A DYNAMIC TRANSITION IN TRAFFIC-FLOW MODELS [J].
BIHAM, O ;
MIDDLETON, AA ;
LEVINE, D .
PHYSICAL REVIEW A, 1992, 46 (10) :R6124-R6127
[4]   Statistical physics of vehicular traffic and some related systems [J].
Chowdhury, D ;
Santen, L ;
Schadschneider, A .
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2000, 329 (4-6) :199-329
[5]   Weighted congestion coefficient feedback in intelligent transportation systems [J].
Dong Chuan-Fei ;
Ma Xu ;
Wang Bing-Hong .
PHYSICS LETTERS A, 2010, 374 (11-12) :1326-1331
[6]   Packet delay analysis on IEEE 802.11 DCF under finite load traffic in multi-hop ad hoc networks [J].
Dong LinFang ;
Shu YanTai ;
Chen HaiMing ;
Ma MaoDe .
SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES, 2008, 51 (04) :408-416
[7]   DYNAMIC NETWORK TRAFFIC ASSIGNMENT CONSIDERED AS A CONTINUOUS-TIME OPTIMAL-CONTROL PROBLEM [J].
FRIESZ, TL ;
LUQUE, J ;
TOBIN, RL ;
WIE, BW .
OPERATIONS RESEARCH, 1989, 37 (06) :893-901
[8]   Intelligent decision-making in a two-route traffic flow model [J].
Fu Chuan-Ji ;
Wang Bing-Hong ;
Yin Chuan-Yang ;
Gao Kun .
ACTA PHYSICA SINICA, 2006, 55 (08) :4032-4038
[9]   Gas-kinetic-based traffic model explaining observed hysteretic phase transition [J].
Helbing, D ;
Treiber, M .
PHYSICAL REVIEW LETTERS, 1998, 81 (14) :3042-3045
[10]   Traffic and related self-driven many-particle systems [J].
Helbing, D .
REVIEWS OF MODERN PHYSICS, 2001, 73 (04) :1067-1141