Vehicle driving safety is influenced by many factors, including drivers, vehicles, and road environments. The interactions among them are quite complex. Consequently, existing methods that evaluate ...driving safety perform inadequately because they only consider limited factors and their interactions. As such, it is difficult for kinematics-based and dynamics-based vehicle driving safety assistant systems to adapt to increasingly complex traffic environments. In this paper, we propose a new concept, i.e., the driving safety field. The concept makes use of field theory to represent risk factors owing to drivers, vehicles, road conditions, and other traffic factors. A unified model of the driving safety field is constructed, which includes the following three parts: 1) a potential field, which is determined by nonmoving objects on the roads, such as a stopped vehicle; 2) a kinetic field, which is determined by the moving objects on roads, such as vehicles and pedestrians; and 3) a behavior field, which is determined by the individual characteristics of drivers. Moreover, the applications of the model are proposed, and its application to a typical car-following scenario is illustrated, which evaluates the risks caused by multiple traffic factors. The driving safety field can reveal driver-vehicle-road interactions and their influences on driving safety, as well as predict driving safety trends owing to dynamic changes. In addition, the model can provide a new foundation for establishing driving safety measures and active vehicle control under complex traffic environments.
Mutants of the Arabidopsis thaliana genes, EDM2 (Enhanced Downy Mildew 2), EDM3 (Enhanced Downy Mildew 3) and IBM2 (Increase in Bonsai Methylation 2) are known to show defects in a diverse set of ...defense and developmental processes. For example, they jointly exhibit enhanced levels of basal defense and stunted growth. Here we show that these two phenotypes are functionally connected by their dependency on the salicylic acid biosynthesis gene SID2 and the basal defense regulatory gene PAD4. Stunted growth of edm2, edm3 and ibm2 plants is a consequence of up-regulated basal defense. Constitutively enhanced activity of reactive oxygen species-generating peroxidases, we observed in these mutants, appears also to contribute to both, their enhanced basal defense and their growth retardation phenotypes. Furthermore, we found the histone H3 demethylase gene IBM1, a direct regulatory target of EDM2, EDM3 and IBM2, to be at least partially required for the basal defense and growth-related effects observed in these mutants. We recently reported that EDM2, EDM3 and IBM2 coordinate basal immunity with the timing of the floral transition by gradually reducing the extent of this defense mechanism prior to flowering. Together with these observations, data presented here show that at least some of the diverse phenotypic effects in edm2, edm3 and ibm2 mutants are genetically interlinked and functionally connected. Our new results show that repression of basal immunity by EDM2, EDM3 and IBM2 limits negative impact on growth and development.
Vehicle trajectory prediction helps automated vehicles and advanced driver-assistance systems have a better understanding of traffic environment and perform tasks such as criticality assessment in ...advance. In this study, an integrated vehicle trajectory prediction method is proposed by combining physics- and maneuver-based approaches. These two methods were combined for the reason that the physics-based trajectory prediction method could ensure accuracy in the short term with the consideration of vehicle running dynamic parameters, and the maneuver-based prediction approach has a long-term insight into future trajectories with maneuver estimation. In this study, the interactive multiple model trajectory prediction (IMMTP) method is proposed by combining the two predicting models. The probability of each model in the interactive multiple models could recursively adjust according to the predicting variance of each model. In addition, prediction uncertainty is considered by employing unscented Kalman filters in the physics-based prediction model. To the maneuver-based method, random elements for uncertainty are introduced to the trajectory of each maneuver inferred by using the dynamic Bayesian network. The approach is applied and analyzed in the lane-changing scenario by using naturalistic driving data. Comparison results indicate that IMMTP could achieve a more accurate prediction trajectory with a long prediction horizon.
In addition to decentralized controllers, the information flow among vehicles can significantly affect the dynamics of a platoon. This paper studies the influence of information flow topology on the ...internal stability and scalability of homogeneous vehicular platoons moving in a rigid formation. A linearized vehicle longitudinal dynamic model is derived using the exact feedback linearization technique, which accommodates the inertial delay of powertrain dynamics. Directed graphs are adopted to describe different types of allowable information flow interconnecting vehicles, including both radar-based sensors and vehicle-to-vehicle (V2V) communications. Under linear feedback controllers, a unified internal stability theorem is proved by using the algebraic graph theory and Routh-Hurwitz stability criterion. The theorem explicitly establishes the stabilizing thresholds of linear controller gains for platoons, under a large class of different information flow topologies. Using matrix eigenvalue analysis, the scalability is investigated for platoons under two typical information flow topologies, i.e., 1) the stability margin of platoon decays to zero as 0(1/N 2 ) for bidirectional topology; and 2) the stability margin is always bounded and independent of the platoon size for bidirectional-leader topology. Numerical simulations are used to illustrate the results.
This paper presents an object classification method for vision and light detection and ranging (LIDAR) fusion of autonomous vehicles in the environment. This method is based on convolutional neural ...network (CNN) and image upsampling theory. By creating a point cloud of LIDAR data upsampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is also adopted to guarantee both object classification accuracy and minimal loss. Experimental results are presented and show the effectiveness and efficiency of object classification strategies.
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► PAN nanofibers obtained by electrospinning. ► PAN/PPy core/shell nanofiber membrane was prepared. ► PAN/PPy core/shell nanofiber membrane used for Cr(VI) removal. ► Adsorption ...capacity remained up to 80% within 5 times cycles.
Polyacrylonitrile/polypyrrole (PAN/PPy) core–shell structure nanofibers were prepared via electrospinning followed by in situ polymerization of pyrrole monomer for the removal of hexavalent chromium (Cr(VI)) from aqueous solution. Attenuated total reflections Fourier transform infrared (ATR-FTIR) and X-ray photoelectron spectroscopy (XPS) results confirmed the presence of the polypyrrole (PPy) layer on the surface of PAN nanofibers. The morphology and structure of the core–shell PAN/PPy nanofibers were studied by scanning electron microscopy (SEM) and transmission electron microscope (TEM), and the core–shell structure can be clearly proved from the SEM and TEM images. Adsorption results indicated that the adsorption capacity increased with the initial solution pH decreased. The adsorption equilibrium reached within 30 and 90min as the initial solution concentration increased from 100 to 200mg/L, and the process can be described using the pseudo-second-order model. Isotherm data fitted well to the Langmuir isotherm model. Thermodynamic study revealed that the adsorption process is endothermic and spontaneous in nature. Desorption results showed that the adsorption capacity can remain up to 80% after 5 times usage. The adsorption mechanism was also studied by XPS.
•A novel restaurant recommendation considering group correlations is proposed.•The correlations between customer group and restaurant group are explored.•Probabilistic linguistic term sets are ...utilized to describe the group preferences.•A similarity measurement between customer and group is proposed.•The proposed approach is validated by a case study on TripAdvisor.com.
The increasing practicality of the group identification approach has led to many studies of restaurant recommendations. The success of group identification depends on how to fully aggregate the customer preferences in a group. However, the aggregation approaches towards customer preferences still pose many challenges to current research. For example, aggregation approaches can cause the group as a whole to report high satisfaction, while the satisfaction reported by individuals is low. Therefore, this paper proposes a novel personalized restaurant recommendation approach that combines group correlations and customer preferences. Our model employs the unsupervised means and probabilistic linguistic term set (PLTS) to conduct the group correlations between customer group and restaurant group. The recommendation list is provided by looking for the most similar group that the target customer belongs to. To validate the model, a case study of TripAdvisor.com is implemented. Our results confirm that the proposed restaurant recommendation approach outperforms the other three benchmark models.
This paper presents a novel vehicular adaptive cruise control (ACC) system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical ...control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is synthesized under the framework of model predictive control (MPC) theory. A quadratic cost function is developed that considers the contradictions between minimal tracking error, low fuel consumption and accordance with driver dynamic car-following characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as linear constraints. Employing a constraint softening method to avoid computing infeasibility, an optimal control law is numerically calculated using a quadratic programming algorithm. Detailed simulations with a heavy duty truck show that the developed ACC system provides significant benefits in terms of fuel economy and tracking capability while at the same time also satisfying driver desired car following characteristics.
Portable and multifunctional electronic devices are developing in the trend of being small, flexible, roll‐up, and even wearable, which asks us to develop flexible and micro‐sized energy ...conversion/storage devices. Here, the high performance of a flexible, wire‐shaped, and solid‐state micro‐supercapacitor, which is prepared by twisting a Ni(OH)2‐nanowire fiber‐electrode and an ordered mesoporous carbon fiber‐electrode together with a polymer electrolyte, is demonstrated. This micro‐supercapacitor displays a high specific capacitance of 6.67 mF cm–1 (or 35.67 mF cm–2) and a high specific energy density of 0.01 mWh cm–2 (or 2.16 mWh cm–3), which are about 10–100 times higher than previous reports. Furthermore, its capacitance retention is 70% over 10 000 cycles, indicating perfect cyclic ability. Two wire‐shaped micro‐supercapacitors (0.6 mm in diameter, ≈3 cm in length) in series can successfully operate a red light‐emitting‐diode, indicating promising practical application. Furthermore, synchrotron radiation X‐ray computed microtomography technology is employed to investigate inner structure of the micro‐device, confirming its solid‐state characteristic. This micro‐supercapacitor may bring new design opportunities of device configuration for energy‐storage devices in the future wearable electronic area.
The high performance of a flexible, wire‐shaped, and solid‐state micro‐supercapacitor, which is prepared by twisting a Ni(OH)2‐nanowire fiber‐electrode and an ordered mesoporous carbon fiber‐electrode together with solid‐state polymer electrolyte, is demonstrated.
Many online services allow users to participate in various group activities such as online meeting or group buying, and thus need to provide user groups with services that they are interested. The ...group recommender systems (GRSs) emerge as required and provide personalized services for various online user groups. Data sparsity is an important issue in GRSs, since even fewer group-item interactions are observed. Moreover, the group and the group members have complex and mutual relationships with each other, which exacerbates the difficulty in modeling the preferences of both a group and its members for recommendation. The cross-domain recommender system (CDRS) is a solution to alleviate data sparsity and assist preference modeling by transferring knowledge from a source domain which has relatively dense data to another. The existing CDRSs are usually developed for individual users and cannot be directly applied for group recommendation. To alleviate the data sparsity issue in GRSs, we first study the cross-domain group recommendation problem and propose a h ierarchical a ttention n etwork-based c ross- d omain g roup r ecommendation method, called HAN-CDGR. HAN-CDGR takes the advantage of data from a source domain to benefit recommendation generation for both the individual users and groups in the target domain which has data sparsity and cannot generate accurate recommendation. In HAN-CDGR, a hierarchical attention network is constructed to learn and model individual and group preferences, with consideration of both group members' interactions and dynamic weights and the complex relationships between individuals and groups. Adversarial learning is used to effectively transfer knowledge from a source domain to the target domain. Extensive experiments, which demonstrate the effectiveness and superiority of our proposal, providing accurate recommendation for both individual users and groups, are conducted on three tasks.
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