In the upcoming decades, connected vehicles will join regular vehicles to appear on roads, and the characteristics of traffic flow will be changed accordingly. To model the heterogeneous traffic ...mixing regular and connected vehicles, a generic car-following framework is first proposed in this paper. A linear stability condition is theoretically derived, which indicates that the stability of the heterogeneous traffic is closely related to the penetration rate and the spatial distribution of connected vehicles. The generic car-following framework is applied by taking the Intelligent Driver Model as an example, and it is shown that connected vehicles can obviously enhance the stability of traffic flow and improve traffic efficiency in particular when traffic is in congestion. Moreover, a driver assistance strategy based on distributed feedback control is developed for connected vehicles, and the simulation results show that the proposed driver assistance strategy performs satisfactorily in stabilizing traffic as well as improving traffic efficiency.
•Two lane-changing (LC) stages are integratedly modeled using deep learning approaches.•LC decisions are modeled based on deep relief network.•LC implementation is modeled based on long short-term ...memory neural network.•High accuracy of predicting a whole LC process is achieved.•The most important factor associated with LC decisions is found.
Lane-changing (LC), which is one of the basic driving behavior, largely impacts on traffic efficiency and safety. Modeling an LC process is challenging due to the complexity and uncertainty of driving behavior. To address this issue, this paper proposes a data-driven LC model based on deep learning models. Deep belief network (DBN) and long short-term memory (LSTM) neural network are employed to model the LC process that is composed of LC decisions (LCD) and LC implementation (LCI). The empirical LC data provided by Next Generation Simulation project (NGSIM) is utilized to train and test the proposed DBN-based LCD model and LSTM-based LCI model. The results indicate that the proposed data-driven model is able to accurately predict the LC process of a vehicle. The sensitivity analysis shows that the most important factor associated with LCD is the relative position of the preceding vehicle in the target lane. This may be the first work that comprehensively models LC using deep learning approaches.
To address sustainable development issues of urban traffic, electric buses will join traditional bus system, and the scheduling of bus fleet should be adjusted due to the distinct features of ...electric buses. To this end, this paper develops a Multi-objective Bi-level programming model to collaboratively optimize the vehicle scheduling and charging scheduling of the mixed bus fleet under the operating conditions of a single depot. The upper level determines the vehicle scheduling to minimize the operating cost and carbon emissions under the constraints of connecting time between trips and the limited driving range of electric buses. The lower level is a charging scheduling problem that considers the charging time and the limited driving distance constraint to minimize the charging cost. The proposed model is solved with an integrated heuristic algorithm. The vehicle scheduling problem is addressed with the iterative neighborhood search algorithm based on simulated annealing, while the charging scheduling problem is solved with a greedy dynamic selection strategy based on the approach of multi-stage decision. Finally, case study is carried out based on a mixed bus fleet in Beijing, and the results validate the availability of the proposed model and solution algorithm.
Cu2O microparticles with controllable crystal planes and relatively high stability have been recognized as a good platform to understand the mechanism of the electrocatalytic CO2 reduction reaction ...(CO2RR). Herein, we demonstrate that the in situ generated Cu2O/Cu interface plays a key role in determining the selectivity of methane formation, rather than the initial crystal plane of the reconstructed Cu2O microparticles. Experimental results indicate that the methane evolution is dominated on all three different crystal planes with similar Tafel slopes and long‐term stabilities. Density functional theory (DFT) calculations further reveal that *CO is protonated via a similar bridge configuration at the Cu2O/Cu interface, regardless of the initial crystal planes of Cu2O. The Gibbs free energy changes (ΔG) of *CHO on different reconstructed Cu2O planes are close and more negative than that of *OCCOH, indicating the methane formation is more favorable than ethylene on all Cu2O crystal planes.
The in‐depth mechanism of electrocatalytic CO2 reduction on in situ reconstructed Cu2O microparticles is still ambiguous. Now strong evidence shows that the Cu2O/Cu interface plays a key role in determining the selectivity of methane production rather than the initial crystal planes of the Cu2O microparticles.
Electrocatalytic CN coupling between carbon dioxide and nitrate has emerged to meet the comprehensive demands of carbon footprint closing, valorization of waste, and sustainable manufacture of urea. ...However, the identification of catalytic active sites and the design of efficient electrocatalysts remain a challenge. Herein, the synthesis of urea catalyzed by copper single atoms decorated on a CeO2 support (denoted as Cu1–CeO2) is reported. The catalyst exhibits an average urea yield rate of 52.84 mmol h−1 gcat.−1 at −1.6 V versus reversible hydrogen electrode. Operando X‐ray absorption spectra demonstrate the reconstitution of copper single atoms (Cu1) to clusters (Cu4) during electrolysis. These electrochemically reconstituted Cu4 clusters are real active sites for electrocatalytic urea synthesis. Favorable CN coupling reactions and urea formation on Cu4 are validated using operando synchrotron‐radiation Fourier transform infrared spectroscopy and theoretical calculations. Dynamic and reversible transformations of clusters to single‐atom configurations occur when the applied potential is switched to an open‐circuit potential, endowing the catalyst with superior structural and electrochemical stabilities.
Electrocatalytic CN coupling between carbon dioxide and nitrate emerges to meet comprehensive demands of carbon footprint closing, valorization of waste, and sustainable manufacture of urea. Herein, the urea synthesis catalyzed by Cu1–CeO2 is reported. The dynamic reversible reconstitution of the catalyst configuration is monitored using operando X‐ray absorption spectra and the Cu4 clusters are real active sites for electrocatalytic urea synthesis. Transform of clusters back to single‐atom configurations occurs when the applied potential is switched to an open‐circuit potential, endowing the catalyst with superior structural and electrochemical stabilities.
Four new indole-diterpenoids, named penerpenes K-N (
-
), along with twelve known ones (
-
), were isolated from the fermentation broth produced by adding L-tryptophan to the culture medium of the ...marine-derived fungus
sp. KFD28. The structures of the new compounds were elucidated extensively by 1D and 2D NMR, HRESIMS data spectroscopic analyses and ECD calculations. Compound
represents the second example of paxilline-type indole diterpene bearing a 1,3-dioxepane ring. Three compounds (
,
and
) were cytotoxic to cancer cell lines, of which compound
was the most active and showed cytotoxic activity against the human liver cancer cell line BeL-7402 with an IC
value of 5.3 μM. Moreover, six compounds (
,
,
,
,
, and
) showed antibacterial activities against
ATCC 6538 and
ATCC 6633.
A speed perturbation model is proposed in this paper for the heterogeneous platoon to measure the interaction between vehicles and investigate the propagation laws of perturbations. Then, a ratio is ...defined to quantify the relationship between the communicating information impact (CII) and the car-following behaviour impact (CFI). A modified IDM is employed to evaluate the role of communicating information in perturbation propagation. Results show that communicating information can suppress the amplification of perturbation. Under the stable environment, the interaction between vehicles decreases with frequency. There is a critical frequency
$ {\omega _c} $
ω
c
(value of 0.55 in this case) that distinguishes the relationship between the CII and CFI. When the frequency is smaller than
$ {\omega _c} $
ω
c
, the CFI is larger than CII; otherwise, the CII dominates the interactions between vehicles. Under the unstable environment, the interaction between vehicles increases first and decreases then, where the vehicles are mainly affected by the car-following behaviours.
Shear-sliding mode (mode II) fracture of rocks is a vital failure form in deep underground engineering. To gain deep insight into the anisotropic shear fracture behaviors of a typical shale under ...high normal stress conditions, a series of direct shear tests were conducted on double-notched specimens in three typical bedding orientations (i.e., the arrester, divider, short-transverse orientations) and under five normal stresses. The mode II fracture toughness (
K
IIc
) is found to exhibit a significant 3D anisotropy. The maximum
K
IIc
is obtained in the divider orientation, followed by those in the arrester and short-transverse orientations. In contrast, the 3D anisotropy in the critical mode II energy release rate (
G
IIc
) is not as significant as that in
K
IIc
, and
G
IIc
in the arrester orientation is quite close to that in the divider orientation. The anisotropy in the prepeak input energy accumulated during shearing is found to be exactly consistent with that in
G
IIc
, which has not been noted before. Furthermore, the anisotropies in the mode II fracture resistances will, unexpectedly, not be weakened by the high normal stress. Owing to the layered structures, tensile cracks are involved during the mode II fracture process, resulting in the formation of rough fracture surfaces.
Due to the interactions among adjacent roads in urban road networks, traffic congestion gradually propagates to neigboring roads, resulting in regional congestion. To develop advanced regional ...traffic control strategies, it is necessary to clearly understand the characteristics of regional congestion evolution. To this end, this paper proposes a data-driven approach to mine the spatiotemporal associations of regional traffic congestion. By introducing both time and space attributes, the intra-transaction spatiotemporal Apriori (IntraT-ST-Apriori) algorithm is developed to address the static features of regional traffic congestion; while the inter-transaction spatiotemporal Apriori (InterT-ST-Apriori) algorithm is developed to capture the dynamic characteristics of regional traffic congestion. Case studies are carried out for the urban road network in Tianjin, China, based on empirical data. The results indicate that the Intra-ST-Apriori algorithm can excavate the underlying associations of regional traffic congestion. Furthermore, the congestion propagation trajectories can be clearly revealed based on the InterT-ST-Apriori algorithm. It is expected that the proposed approach can support the regional traffic management and control, significantly relieving traffic congestion.
The increase of air travel puts tremendous burden on airline companies. A time saving boarding strategy is required to improve the utilization of airplane boarding time and explore flexible time ...management strategies. Firstly, an improved boarding strategy is introduced by assigning individual passengers to seats based on the number of luggage they carry. Passengers with the most luggage board onto the plane first. To test the behavior of boarding strategies under different conditions, a sophisticated simulation environment based on cellular automata model is designed. Simulation results indicate that the improved boarding strategy shows an excellent efficiency and robustness comparing with other strategies.
•An airplane boarding model is proposed based on cellular automata.•The improved strategy is designed based on luggage property.•The improved strategy avoids seat interference and reduces aisle interference.•The improved strategy increases parallel boarding ability.•Simulation results reveal differences among various strategies.
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