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Vehicle platoons were recently proposed to reduce energy consumption and emissions. However, the majority of platooning studies have focused on pure connected automated vehicle (CAV) environments with limited insights into energy consumption and emissions. This paper quantifies fuel consumption and emissions by studying the microscopic movements of CAVs and human driving vehicles (HDVs) in mixed traffic flows. With an extended cellular automaton model, a four-lane mixed traffic flow of CAVs and HDVs is investigated in detail. The results have shown that ad hoc platoon formation can lead to frequent acceleration and lane changing, resulting in more fuel consumption and emission. With a dedicated CAV lane (DCL) strategy, the interference of CAVs and HDVs is greatly reduced, thereby improving the fuel economy and emission reduction. The findings can benefit the organization of vehicle platoons in the persisting mixed traffic flow environment.

With the development of urban rail transit systems, the operation and management of the system faces various problems, among which the unreasonably long waiting time at transfer stations during the first train period is a major challenge for metro companies. To address this problem, some cities (e.g. Guangzhou, Hefei) are operating inter-regional trains to reduce the waiting time of passengers. With this motivation, we study the first train timetable synchronization problem with multiple departure stations. The problem is first formulated as a mixed integer nonlinear programming (MINLP) model. By using auxiliary intermediate variables, the nonlinear model is reformulated as a mixed integer linear programming (MILP) model, which can be solved directly by the commercial solver COPT. A real-world example of the Hefei urban rail transit network is applied to test the effectiveness of the proposed model. By adjusting the first ordinary train start service times and operating 12 additional inter-regional trains on 2 bidirectional lines, the total transfer waiting time and the number of long waiting time directions decreased by 39.09% and 56.25%, respectively.

In the last two decades, network science has blossomed and influenced various fields, such as statistical physics, computer science, biology and sociology, from the perspective of the heterogeneous interaction patterns of components composing the complex systems. As a paradigm for random and semi-random connectivity, percolation model plays a key role in the development of network science and its applications. On the one hand, the concepts and analytical methods, such as the emergence of the giant cluster, the finite-size scaling, and the mean-field method, which are intimately related to the percolation theory, are employed to quantify and solve some core problems of networks. On the other hand, the insights into the percolation theory also facilitate the understanding of networked systems, such as robustness, epidemic spreading, vital node identification, and community detection. Meanwhile, network science also brings some new issues to the percolation theory itself, such as percolation of strong heterogeneous systems, topological transition of networks beyond pairwise interactions, and emergence of a giant cluster with mutual connections. So far, the percolation theory has already percolated into the researches of structure analysis and dynamic modeling in network science. Understanding the percolation theory should help the study of many fields in network science, including the still opening questions in the frontiers of networks, such as networks beyond pairwise interactions, temporal networks, and network of networks. The intention of this paper is to offer an overview of these applications, as well as the basic theory of percolation transition on network systems., 88 pages,19 figures, 5 tables

In urban traffic systems, alleviating traffic congestion originated from left-turn/U-turn lanes at highly demanded intersections plays an important role in enhancing the traffic efficiency. For a typical intersection, the layout with double left-turn (DLT) lanes is a relatively common geometric feature. However, the effect of DLT scheme on the performance of the entire traffic system is not clear. This paper compares the performance of urban traffic system with different lane function schemes with extended cellular automaton (CA) model considering the car-following, lane-changing, intersection-traversing and route-choice behavior of vehicles. Using the flow-density relation, three macroscopic parameters (average trip completion rate, average traffic flow and average velocity) are examined to evaluate the system performance. With the wide application of DLT scheme, the vehicles can be distributed more evenly among the lanes. As a result, the traffic flow and the trip completion rate will be higher, especially at high density. Case studies of realistic Hefei city network and Sioux Falls networks are also carried out. The results show that the performance of traffic network will be better if more intersections adopt the DLT scheme.

The study of traffic dynamics on couple networks is important for the design and management of many real systems. In this paper, an efficient routing strategy on coupled spatial networks is proposed, considering both traffic characteristics and network topology information. With the routing strategy, the traffic capacity can be greatly improved in both scenarios of identical and heterogeneous node capacity allocation. Heterogeneous allocation strategy of node delivery capacity performs better than identical capacity allocation strategy. The study can help to improve the performance of real-world multi-modal traffic systems.

Enhancing traffic flow plays an important role in the traffic management of urban arterial networks. The policy of prohibiting left-turn (PLT) at selected highly demanded intersections has been adopted as an attempt to increase the efficiency at these intersections. In this paper, we study the impact of PLT by mathematical analysis and simulations based on the cellular automaton model. Using the flow-density relation, three system performance indexes are examined: the average trip completion rate, the average traffic flow, and the average velocity of vehicles. Different route guidance strategies, including the shortest path and the quickest path, are investigated. We show that when left turn is prohibited, vehicles are distributed more homogeneously in the road network, and the system performs better and reaches a higher capacity. We also derive a critical length of link, above which the benefit of PLT will decrease.

Solar selective absorbing coatings that absorb solar irradiation and emit infrared radiation have a significant impact on the thermal efficiency of the receivers. The spectrum parameters heat transfer model and the non-ideal coating curve model are established. The cutoff wavelength of coatings is comprehensively optimized, and the effect of the optical properties of the coating on overall performance is analyzed. Results show that the optimal cutoff wavelength rises with the solar irradiation flux but decreases with increased absorber temperature. Sensitivity analysis results of the coating optical properties indicates that the thermal efficiency significantly decreases with increasing slope width. The change range of the thermal efficiency at the temperature of 200 °C is ±0.1%, resulting from a ±1 μm variation in slope width, whereas the range at 600 °C is ±6.5%. Spectral absorptivity analysis shows that the coating absorptivity has nearly same positive influence on thermal efficiency under different temperatures and irradiation fluxes, whereas emissivity analysis reveals an evidently different negative effect on the receiver performance. Finally, the annual optimal cutoff wavelength decreases with increasing temperature but increases with solar irradiation. The optimal cutoff wavelength decreases from 2.23 μm at 200 °C to 0.78 μm at 600 °C in Phoenix.

When traffic control is demand-responsive, a bottleneck can have a queue-length-dependent capacity. Motivated by this fact, we studied the morning commute problem in which the bottleneck capacity increases from s1 to s2 as the queue length exceeds a threshold D1 and decreases back to s1 as the queue length reduces and becomes smaller than another threshold D2 (D2 ≤ D1). It has been found that multiple equilibria exist when D2

With the development of the Internet and mobile phone technology, it is much easier to access ridesharing information via mobile applications. In this paper, the relationship between the demand of ridesharing passengers (RPs), ridesharing drivers (RDs) and solo drivers (SDs) in a ridesharing compensation scheme is studied by a stochastic ridesharing user equilibrium (SRUE), which contains a mode choice model and a route choice model. The mode choice model and the route choice model influence each other. The SRUE is first expressed as a fixed-point problem mathematically. Six possible states of OD pairs are discussed. Then the existence of SRUE is proved. The method of successive weighted averages is adopted to solve the problem. It is found that there will be a higher demand of ridesharing passengers for journeys with longer travel time. Moreover, with the increase of the ridesharing compensation, the demand of ridesharing passengers is not always decreasing, and the demand of ridesharing drivers is not always increasing.

Recent researches indicate that real network systems are often coupled together by shared links or interconnecting nodes, through which different networks can communicate with each other. Therefore, both intra-traffic and inter-traffic coexist in these systems. In this paper, we study such kind of hybrid traffic flow considering three coupling mechanisms: (i) assortative coupling, (ii) disassortative coupling, and (ii) the newly proposed anti-assortative coupling. The results show that the anti-assortative coupling can achieve higher traffic capacity, especially when the inter-traffic level is high. The traffic capacity of system exhibits non-monotonic behavior with the coupling strength. With the anti-assortative coupling mechanism, the system capacity can be improved at an optimized coupling strength of β ≈ 0 . 3 . We further propose an index called effective betweenness, based on which the traffic capacity of such coupled systems can be theoretically predicted.

To investigate the car-following behavior under high speed driving conditions, we performed a set of 11-car-platoon experiments on Hefei airport highway. The formation and growth of oscillations have been analyzed and compared with that in low speed situations. It was found that there is considerable heterogeneity for the same driver over different runs of the experiment. This intra-driver heterogeneity was quantitatively depicted by a new index and incorporated in an enhanced two-dimensional intelligent driver model. Using both the new high-speed and the previous low-speed experimental data, the new and three existing models were calibrated. Simulation results show that the enhanced model outperforms the three existing car-following models that do not take into account this intra-driver heterogeneity in reproducing the essential features of the traffic in the experiments.

The structure of interconnected systems and its impact on the system dynamics is a much-studied cross-disciplinary topic. Although various critical phenomena have been found in different models, study of the connections between different percolation transitions is still lacking. Here we propose a unified framework to study the origins of the discontinuous transitions of the percolation process on interacting networks. The model evolves in generations with the result of the present percolation depending on the previous state, and thus is history-dependent. Both theoretical analysis and Monte Carlo simulations reveal that the nature of the transition remains the same at finite generations but exhibits an abrupt change for the infinite generation. We use brain functional correlation and morphological similarity data to show that our model also provides a general method to explore the network structure and can contribute to many practical applications, such as detecting the abnormal structures of human brain networks., We propose a unified framework for studying the origin of the discontinuous transitions of the percolation process on interacting networks,whichalsohas wide practical applications in network science.

In this paper, the impact of holding an umbrella on the uni- and bi-directional flow has been investigated via experiment and modeling. In experiments, pedestrians walk clockwise/anti-clockwise in a ring-shaped corridor under the normal situation and holding umbrella situation. In the unidirectional flow, the flow rate under the holding umbrella situation decreases from 0.1 to 0.25 ped/s/m when compared to the normal situation. In the holding umbrella situation, the bidirectional flow rate even reduces to 0.2 ped/s/m in contrast to the unidirectional flow. In the bidirectional flow, pedestrians segregate into two opposite moving streams very quickly under the normal situation and have right-walking preference. Under the holding umbrella situation, spontaneous lane formation also occurs. However, pedestrians can easily separate into three or four lanes. Moreover, the merge of lanes is observed, and clockwise/anti-clockwise pedestrians are not always in the inner/outer lane. The simulation results b...

Traffic instability is an important but undesirable feature of traffic flow. This paper reports our experimental and empirical studies on traffic flow instability. We have carried out a large scale experiment to study the car-following behavior in a 51-car-platoon. The experiment has reproduced the phenomena and confirmed the findings in our previous 25-car-platoon experiment, i.e., standard deviation of vehicle speeds increases in a concave way along the platoon. Based on our experimental results, we argue that traffic speed rather than vehicle spacing (or density) might be a better indicator of traffic instability, because vehicles can have different spacing under the same speed. For these drivers, there exists a critical speed between 30 km/h and 40 km/h, above which the standard deviation of car velocity is almost saturated (flat) along the 51-car-platoon, indicating that the traffic flow is likely to be stable. In contrast, below this critical speed, traffic flow is unstable and can lead to the formation of traffic jams. Traffic data from the Nanjing Airport Highway support the experimental observation of existence of a critical speed. Based on these findings, we propose an alternative mechanism of traffic instability: the competition between stochastic factors and the so-called speed adaptation effect, which can better explain the concave growth of speed standard deviation in traffic flow.

In this paper, we study the application of perimeter flow control by simulation of cellular automaton model on urban traffic system. We find that the relation of traffic flow and vehicle density (Macroscopic Fundamental Diagram, MFD) will have different shapes for the core area and the peripheral area. The MFD shows free-flow state, saturate flow state and congestion state. But the magnitude of maximal flow and the position for congestion transition are different for the whole system and the core area. We suggest to realize the perimeter control strategy by assigning a special prohibiting phase to the perimeter traffic lights for the roads entering the core area. The strategy is controlled by two critical densities ρ 1 and ρ 2, which are determined by the MFD of the core area. Simulations show that both the average arrival rate and the average flow will be greatly improved with the perimeter flow control strategy. In addition, the perimeter flow control strategy can increase the critical density of traffic congestion. The probability of system-wide gridlock will decrease, and the system can perform well under both close and open boundary conditions. All the results indicate that the perimeter flow control strategy can effectively improve the performance of the traffic system.

Pre-signal is an additional traffic light proposed in traffic system to improve the left-turning efficiency of intersections. The efficiency of pre-signals in a networked environment will be affected by the coordination of pre-signals and the intersection traffic lights. In this paper, we study the implementation of pre-signal in a Manhattan-like urban traffic system based on a microscopic cellular automaton model. The pre-signals are located before the normal traffic lights, and have two phases (left-turning phase and through phase) for the aim of segregating left-turning and through vehicles into separate sets of lanes. We propose a reliable method to coordinate the intersection traffic light period and phases with the pre-signal period and phases. Simulation results show that the pre-signals can improve the performance of the system, for both closed and open boundaries. The macroscopic fundamental diagram of the system shows a much higher traffic flow for a wide range of densities. Moreover, the effect of pre-signal area length also needs to be considered in a networked environment. We find that the optimal length of pre-signal area should be determined by the number of vehicles passing the traffic light in a left-turning phase at the intersection. The results can help the implementation and application of pre-signal in real traffic system.

Metallic nanoparticles have unique optical properties such as localized surface plasmon resonance (LSPR) effect, which can be used to improve the energy absorption and photocatalytic properties of semiconductor bases. In this paper, we construct a model to study the influence of Ag or Au nanoparticles (cubes or spheres) on the solar energy absorption and photocatalytic properties of nitrogen doped TiO 2 (or N-TiO 2 ). Effects of specific nanoparticle coupling parameters, such as particle shape, size, doping period (metal–metal distance) and separation distance (metal–semiconductor distance), on the properties of N-TiO 2 are studied in detail. We show that the photocurrent improvement can be optimized by setting suitable geometric parameters. In particular, the separation distance between metallic nanoparticles and N-TiO 2 D should be around 6–7 nm, and the period of doping P should be around 360 nm. The silver cubes with edge length L = 120 n m show the best performance. The results can help the design of solar energy materials, in which metallic nanoparticles may play an important role.

Cycling is a popular and sustainable mode of transportation. However, few studies have examined experimental and modeling studies on bicycle flow dynamics. In particular, for wide roads, the characteristics of high-density regimes in the fundamental diagram have not been well addressed, and the emergence of stop-and-go waves has not been fully understood. This study experimentally investigated bicycle flow dynamics on wide roads, using two types of 3-m-wide track. Different riding behaviors, namely, free riding, following, and overtaking, were analyzed. The bicycle flow dynamics were found to be essentially the same on the two tracks: (i) The bicycle flow rate remained nearly constant across a wide range of densities, in marked contrast to the single-file bicycle flow, which exhibited a unimodal fundamental diagram. By studying the weight density of the radial and lateral locations of cyclists, we argue that this behavior arises from the formation of more lanes with increase in global density. The newly formed lanes prevented the flow rate from decreasing. (ii) When the density exceeded 0.5 bicycles/m2, the flow rate began to decrease, and stop-and-go traffic emerged. Based on these behavioral observations, we propose an improved heuristic-based model to simulate bicycle flow on roads of different radii and explicitly account for the centrifugal effect of bicycles. The calibration and validation results demonstrate that the proposed model can reproduce the traffic dynamics of bicycle flow.

In a real traffic system, information feedback has already been proven to be a good way to alleviate traffic jams. However, due to the massive traffic information of real system, the procedure is often difficult in practice. In this paper, we study the effects of the amount of feedback information based on a cellular automaton model of urban traffic. What we found most interesting is that when providing the traffic information of a part of a road to travelers, the performance of the system will be better than that providing the road's full traffic information. From this basis, we can provide more effective routing strategy with less information. We demonstrate that only providing the traffic information of about first half road from upstream to downstream can maximize the traffic capacity of the system. We also give an explanation for these phenomena by studying the distribution pattern of vehicles and the detailed turning environment at the intersections. The effects of the traffic light period are also provided.

Cycling has been advocated by many governments because it is a healthy and green transportation mode and it helps mitigate traffic congestion. However, compared with vast amounts of works on vehicle flow and pedestrian flow, the bicycle flow study currently lags behind. We have carried out experimental studies on bicycle flow on a 146 meters long circular road and on an on-ramp system. We present the fundamental diagram of bicycle flow and the trajectories of each bicycle on the circular road. We have analyzed the spatiotemporal evolution of bicycle flow and found that jams spontaneously form above a critical density of approximately 0.37 bicycles/m. For the on-ramp system, no capacity drop has been observed. The similarity and difference between bicycle flow and vehicle flow has been discussed. We propose a cellular automaton model of bicycle flow, and the simulation results are in agreement with the experiments.

This paper studies a bidirectional multilane driven diffusive system with two type of particles. Phase separation phenomenon emerges in the system. In particular, a novel dual phase separation could be observed under certain circumstance. Mean field analysis has been carried out, which indicates that occurrence of phase separation might be related to minimization of system current. Specifically, the occurrence of dual phase separation is due to (i) existence of a local minimum in the fundamental diagram of flow rate J versus density ρ and (ii) ∂ J / ∂ ρ | ρ = 1 0 . Our findings offer sights to understand deeply dynamic features of multilane transportation system, especially phase separation of nonequilibrium state systems.

In this paper, the impact of vision on the uni- and bi-directional flow has been investigated via experiment and modeling. In the experiments, pedestrians are asked to walk clockwise/anti-clockwise in a ring-shaped corridor under view-limited condition and normal view condition. As expected, the flow rate under the view-limited condition decreases comparing with that under the normal view condition, no matter in uni- or bi-directional flow. In bidirectional flow, pedestrians segregate into two opposite moving streams very quickly under the normal view condition, and clockwise/anti-clockwise walking pedestrians are always in the inner/outer ring due to right-walking preference. In the first set of experiment, spontaneous lane formation has not occurred under the view-limited condition. Pedestrian flow does not evolve into stationary state. Local congestion occurs and dissipates from time to time. However, in the later sets of experiments, spontaneous lane formation has re-occurred. This is because participants learned from the experience and adapted right-walking preference to avoid collision. To model the flow dynamics, an improved force-based model has been proposed. The driving force has been modified. The right-walking preference has been taken into account. The fact that pedestrians cannot judge the moving direction accurately under limited-view condition has been considered. Simulation results are in good agreement with the experimental ones.

Urban traffic system is important for the convenience and efficiency of people’s daily life. The understanding of inter-relations between urban street network and traffic flow can help the planning process of urban systems. Based on cellular automata modeling, this paper studies the influence of aspect ratio of a rectangular urban network on the dynamics of traffic system. The performance of road network is examined with the Macroscopic Fundamental Diagram (MFD). The maximal arrival rate and the critical density of congestion of MFD are investigated as two main indicators for system performance. Under the closed boundary condition, the square network shows the maximum arrival rate, but with a relatively lower critical density of congestion. With the increase of aspect ratio, the arrival rate decreases, while the critical congestion density increases. The phenomena can be explained by the vehicle distribution in the network, the left-turning and U-turning demand, and the average travel distance.

Multiplex networks have been proposed as an effective abstract of real complex systems, ranging from multi-modal urban transportation systems to communication systems. In this paper, we investigate a traffic-driven epidemic model in multiplex networks, and derive a theoretical approach to accurately predict the epidemic threshold of each layer. Our results show that the multiplex structure can produce different effects on the epidemic threshold of layers. Interestingly, one important finding is that the epidemic can be completely suppressed in a certain layer. This phenomenon occurs only when the connectivity of layers is very different, and the traffic flow is heterogeneously distributed over the layers. Therefore, epidemic spreading becomes quite distinct among the layers with different amounts of traffic flow. By using mean-field analysis, an explicit expression is derived to detect this traffic-induced epidemic suppression phenomenon. The accuracy of theoretical prediction is assessed in Erdős–Rényi and scale-free multiplex networks.

Traffic breakdown to global gridlock occurring in congested traffic network makes the serious traffic congestion even much worse. This paper has proposed to use Network Operation Reliability (NOR) to quantitatively depict the probabilistic feature of traffic breakdown to global gridlock. The Nagel–Schreckenberg cellular automaton model has been used to simulate the traffic flow in a Manhattan-like urban network. A simple adaptive traffic light strategy has been proposed. It has been shown that if vehicles choose to use geometric shortest path, the adaptive traffic signals are able to remarkably enhance the NOR and sometimes the average velocity and the arrival rate as well. The vehicle distribution has been investigated, which has heuristically explained the enhancement of the NOR. A simple perimeter control strategy has been shown to fail to enhance the NOR. Finally, we show that if the time shortest path information could be provided and updated timely, then the NOR can be remarkably enhanced but the adaptive traffic signals have only trivial effect on NOR.

We study in this paper the structure of traffic under hypercongestion, which is a controversial issue between traditional two-phase traffic theory and Kerner’s three-phase theory. By analyzing video traffic data from a section of the Nanjing Airport Highway, it is found that traffic states inside hypercongestion are not homogeneous, which contradicts the existence of a “Homogeneous Congested Traffic” state claimed in two-phase traffic theory. Analysis of vehicle trajectories and velocities obtained from an experimental car-following study with a platoon of 25 vehicles also confirms the above findings. Furthermore, it is also found from the video traffic data that the structure of hypercongested traffic varies only slightly with location, which might be due to small jams inside hypercongested traffic merging into larger ones slowly and/or larger jams sometimes breaking into small ones. Finally, the implications of our observations on traffic modeling have been discussed.

We have carried out car-following experiments with a 25-car-platoon on an open road section to study the relation between a car’s speed and its spacing under various traffic conditions, in the hope to resolve a controversy surrounding this fundamental relation of vehicular traffic. In this paper we extend our previous analysis of these experiments, and report new experimental findings. In particular, we reveal that the platoon length (hence the average spacing within a platoon) might be significantly different even if the average velocity of the platoon is essentially the same. The findings further demonstrate that the traffic states span a 2D region in the speed-spacing (or density) plane. The common practice of using a single speed-spacing curve to model vehicular traffic ignores the variability and imprecision of human driving and is therefore inadequate. We have proposed a car-following model based on a mechanism that in certain ranges of speed and spacing, drivers are insensitive to the changes in spacing when the velocity differences between cars are small. It was shown that the model can reproduce the experimental results well.