Physica A 391 (2012) 2730–2739 Contents lists available at SciVerse ScienceDirect Physica A journal homepage: www.elsevier.com/locate/physa A comprehensive study of advanced information feedbacks in real-time intelligent traffic systems Bokui Chen a,* , Yanbo Xie a , Wei Tong a , Chuanfei Dong b , Dongmei Shi a , Binghong Wang a,c a Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China b Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109, USA c The Research Center for Complex System Science, University of Shanghai for Science and Technology and Shanghai Academy of System Science, Shanghai 200093, China article info Article history: Received 18 September 2011 Received in revised form 12 December 2011 Available online 27 December 2011 Keywords: Vacancy length information feedback strategy NS model Two-route scenario Intelligent traffic systems abstract In the intelligent transportation system, an effective feedback strategy is of crucial importance to the improvement of traffic condition and transport capability. Based on the seven previously introduced feedback strategies, a new one is introduced, called vacancy length feedback strategy (VLFS). The simulation results in the symmetrical two-route scenario with two exits suggest that VLFS is the optimal one among all the feedback strategies. It outperforms others in terms of the value, stability, average flux and balance of the vehicle number, and also exceeds others for the convenience of its application in the real traffic condition. The later simulation results in the asymmetrical two-route scenario with one exit also prove that VLFS is the best. Crown Copyright © 2012 Published by Elsevier B.V. All rights reserved. 1. Introduction Transport network and Internet are getting more and more close to our daily life with the development of economy and living conditions. Following is the deterioration of the phenomenon of congestion. Many physicists have applied physics concepts and analytical methods to solve these difficult problems [1–4]. In recent years, study focuses on the research of strategies, such as routing strategies in network and information feedback strategies in intelligent traffic systems. In terms of routing strategies, Wang et al. proposed two routing strategies based on local static and dynamic information [5,6]. In order to solve the cascading failures and traffic congestion in the network, Yang et al. proposed weighted routing strategy in 2009 [7]. As to the feedback information strategy in intelligent traffic system, there are more research findings [8–18]. Intelligent transportation system is a novel one dimensional urban traffic system. To improve the transportation capacity and avoid the congestion, we need to present the feedback information of traffic conditions. Take a two-route scenario as an example; we set a board at the entrance displaying the traffic condition of the routes to instruct the drivers for selection. Therefore, to design a reasonable and efficient feedback information is the pivotal problem. In recent years, some information feedbacks have been presented to investigate in the symmetrical two-route scenario. Wahle et al. first investigated the two-route scenario with travel time feedback strategy (TTFS) [11]. Subsequently, Lee et al. studied the effect of a different type of information feedback, named mean velocity feedback strategy (MVFS) [12], i.e. instantaneous average velocity. Then Wang et al. proposed a third type of information feedback, called congestion coefficient feedback strategy (CCFS) [13]. All the three strategies mentioned above were simulated in the symmetrical two-route scenario with two exits, and Wang et al. demonstrated that CCFS is the best. Recently, Dong et al. proposed four straightforward and concise methods, called prediction feedback strategy (PFS) [14,15], vehicle number feedback strategy (VNFS) [16], weighted congestion coefficient * Corresponding author. 0378-4371/$ – see front matter Crown Copyright © 2012 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.physa.2011.12.032