Bokui Chen

Flux information feedback strategy in intelligent traffic systems

To effectively alleviate the traffic congestion in urban areas, scientists and engineers have put forward intelligent traffic systems. The information feedback strategy, serving as the critical part of intelligent traffic systems, has been treated with growing emphasis. In this paper, we present two new strategies using the flux as feedback information. One is the time flux feedback strategy (TFFS), the other is the space flux feedback strategy (SFFS). We report the simulation results adopting these two feedback strategies together with the other previously reported ones in a two-route scenario with two exits. The result suggests that SFFS, which outperforms the other categories of feedback strategy, not only in terms of the value of vehicle number and average flux but also in terms of convenience of its application to real traffic conditions, is the best.

Real-time information feedback based on a sharp decay weighted function

Abstract Information feedback strategy, serving as the critical part of intelligent traffic systems, has been treated with growing emphasis. In recent years, a variety of feedback strategies have been proposed. Despite the fact that these strategies have been proved to enhance the traffic efficiency, we find that the road capacity has not been saturated and there is still plenty of room for improvement. Based on the analytic approximations, we found the reason why corresponding angle feedback strategy is superior to weighted congestion coefficient feedback strategy. Given that the sharp decay of the weighted coefficient is the key point, we proposed an efficient feedback strategy called the exponential function feedback strategy (EFFS). We applied it to both the symmetrical two-route model with two exits and that with a single exit. The simulation results indicate that, compared with other strategies, EFFS has decided numerical advantages in average flow, a physical quantity used for depicting the road capacity. Even more importantly, EFFS stands out for its convenient application as well as its fitness for modeling the rugged roads.

PIECEWISE FUNCTION FEEDBACK STRATEGY IN INTELLIGENT TRAFFIC SYSTEMS WITH A SPEED LIMIT BOTTLENECK

The road capacity can be greatly improved if an appropriate and effective information feedback strategy is adopted in the traffic system. In this paper, a strategy called piecewise function feedback strategy (PFFS) is introduced and applied into an asymmetrical two-route scenario with a speed limit bottleneck in which the dynamic information can be generated and displayed on the information board to guide road users to make a choice. Meanwhile, the velocity-dependent randomization (VDR) mechanism is adopted which can better reflect the dynamic behavior of vehicles in the system than NS mechanism. Simulation results adopting PFFS have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the previous strategies.

Advanced Algorithms for Local Routing Strategy on Complex Networks.

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Route guidance strategies revisited: Comparison and evaluation in an asymmetric two-route traffic network

To alleviate traffic congestion, a variety of route guidance strategies have been proposed for intelligent transportation systems. A number of strategies are introduced and investigated on a symmetric two-route traffic network over the past decade. To evaluate the strategies in a more general scenario, this paper conducts eight prevalent strategies on an asymmetric two-route traffic network with different slowdown behaviors on alternative routes. The results show that only mean velocity feedback strategy (MVFS) is able to equalize travel time, i.e. approximate user optimality (UO); while the others fail due to incapability of establishing relations between the feedback parameters and travel time. The paper helps better understand these strategies, and suggests MVFS if the authority intends to achieve user optimality.

Correction: Advanced Algorithms for Local Routing Strategy on Complex Networks.

[This corrects the article DOI: 10.1371/journal.pone.0156756.].

SPEED OF LAST VEHICLE FEEDBACK STRATEGY IN INTELLIGENT TRANSPORTATION SYSTEMS

Traffic jam has become a big problem in the development of economy. How to effectively improve the road capacity is becoming the key problem in the research of traffic flow. As the core part of the next generation intelligent transportation systems, the feedback strategy has attracted much attention. In recent years, researchers have proposed many effective strategies. In this paper, a strategy called speed of last vehicle feedback strategy is introduced, and simulated in a two-route scenario with one exit. Result shows that compared with other strategies, this strategy has certain advantages on average flux — a criteria describing traffic capacity of traffic systems. More importantly, the implementation of this strategy is very simple.

Advanced Information Feedback Coupled with an Evolutionary Game in Intelligent Transportation Systems

It has been explored for decades how to alleviate traffic congestions and improve traffic fluxes by optimizing routing strategies in intelligent transportation systems (ITSs). It, however, has still remained as an unresolved issue and an active research topic due to the complexity of real traffic systems. In this study, we propose two concise and efficient feedback strategies, namely mean velocity difference feedback strategy and congestion coefficient difference feedback strategy. Both newly proposed strategies are based upon the time-varying trend in feedback information, which can achieve higher route flux with better stability compared to previous strategies proposed in the literature. In addition to improving feedback strategies, we also investigate information feedback coupled with an evolutionary game in a 1-2-1-lane ITS with dynamic periodic boundary conditions to better mimic the driver behavior at the 2-to-1 lane junction, where the evolutionary snowdrift game is adopted. We propose an improved self-questioning Fermi (SQF) updating mechanism by taking into account the self-play payoff, which shows several advantages compared to the classical Fermi mechanism. Interestingly, our model calculations show that the SQF mechanism can prevent the system from being enmeshed in a globally defective trap, in good agreement with the analytic solutions derived from the mean-field approximation.

Weighted Value Feedback Strategy in Intelligent Two-Route Traffic Systems with a Bottleneck

Information feedback strategies are attracting keen attention recently as the central part of intelligent traffic systems. Various strategies have been put forward by previous researchers and have been applied in the model of symmetrical two-route scenario. In this letter, a novel strategy for scenario with speed-limited bottlenecks is raised, which is called weighted value feedback strategy (WVFS). Combined with three former strategies, we simulated these four into a two-route scenario with a speed-limited bottleneck. The results show that our strategy wins over the other three in effectively enhancing and balancing the vehicle numbers, as well as increasing the average flux on both routes.