Constant Rate Model Research Articles

Melt embayments record multi-stage magma decompression histories

Over the last decade, the melt embayment has proven its merit as a robust petrological tool capable of recording magma decompression rates for explosive eruptions. However, the models developed and applied to extract this information from embayments have not accounted for the complexity and nonlinearity of magma flow in the conduit. We present Embayment Decompression in Two Stages (EDiTS): a numerical model for extracting magma decompression rates from measured volatile diffusion profiles preserved in crystal-hosted embayments, approximating magma acceleration using two constant-rate decompression paths. This model solves for three unknown parameters: initial (deeper) and final (shallower) decompression rates, as well as the pressure where a transition occurs. We successfully benchmark EDiTS against existing numerical diffusion models, and use controlled multi-stage decompression experiments on natural quartz-hosted embayments to test the ability of our model to recover known decompression paths. We find that EDiTS is able to closely approximate the known two-stage path in the mixed-volatile (H2O + CO2) experiment, while a constant-rate modeling approach is unable to simultaneously fit H2O and CO2 gradients. However, in the H2O-saturated experiment, there is no unique solution to the resulting gradient, with both constant-rate and two-stage models reproducing the measured profile, and EDiTS notably overestimating the known total ascent time by several hours. Using decompression experiments, we show that constant-rate models can provide misleadingly good fits to embayment H2O gradients produced by more complex decompression histories, and thus the measurement and modeling of multiple diffusing species, when available, can provide crucial constraints. We then apply EDiTS to re-evaluate mixed-volatile embayment datasets from explosive silicic arc and caldera-forming eruptions from five volcanic centers (Yellowstone, WY, USA; Bandelier, NM, USA; Long Valley, CA, USA; Taupo, NZ; Mount St. Helens, WA, USA), where all systems contain initial CO2. In contrast to the minutes to hours of total ascent time extracted from embayment volatile profiles using constant-rate models, our two-stage model resolves slower initial ascent times that span several to >10 h. Final ascent rates are 1–2 orders of magnitude faster than the initial extracted rates, in agreement with theoretical conduit flow model predictions. Application of EDiTS to embayments from the May 18th, 1980 eruption of Mount St. Helens results in an initial stage of ascent on the order of hours consistent with the timing of magma arrival at the surface from the seismically-inferred storage region (7–9 km) ~3.5 h after the initial blast, and a final stage of ascent (<1–5 min) in close agreement with time-integrated bubble number densities. Our combined numerical, experimental, and natural results suggest that, with the application of more advanced models, the melt embayment can provide a complete picture of magma decompression timescales from the deep conduit to the surface.

Modelling the Time-varying Transmission of Wild Poliovirus in Pakistan

Aims/Objectives: The efforts to eradicate the wild poliovirus since 1988 have successfully reduced its global prevalence by 99%. However, as of 2024, Pakistan and Afghanistan remain the only two endemic countries facing the virus transmission. This study employs a transmission dynamic model to understand the persistence of wild poliovirus type 1 (WPV1) in Pakistan. Study Design: An ordinary differential equations-based deterministic type of mathematical model was developed. Place and Duration of Study: Department of Epidemiology and Public Health and Institute of Microbiology, University of Agriculture Faisalabad, March 2023 to August 2023. Methodology: We included the number of reported polio cases and the proportion of missed children by supplementary immunization activities (SIAs) across the country from 2017-2022. The model considered both human-human and environment-human virus transmission through sewage contamination and these are represented by time-dependent transmission rate parameters. The parameter estimation was done by model fitting to the reported data of WPV1 cases. The model simulations then predicted the future polio infections in Pakistan. Results: Our analysis identified that the asymptomatic infectious population missed by the SIAs is the major contributor to disease persistence in the country. Moreover, the environment can contribute to virus transmission in areas with poor WASH infrastructure and under-immunized populations. The estimated basic reproduction number through the next-generation matrix method was 1.61 while the estimated effective reproduction number was 0.12. The model showed a better predictive ability than constant transmission rate models. The numerical simulations considering the reduction in the virus-shedding rate by the asymptomatic population resulted in an 85% reduction in future polio cases in Pakistan. Conclusion: The results suggest that endemic virus transmission will continue subject to the current higher vaccination coverage across the country. The model can be further utilized to guide eradication efforts for targeted allocation of preemptive measures.

The Evolution of Body Size in Terrestrial Tetrapods

Body size is a fundamental trait in evolutionary and ecological research, given that it varies allometrically with several relevant features, such as life-history and physiological traits. Although previous studies uncovered many intriguing patterns, finding general principles of body size evolution in vertebrates has been elusive. In this study, we take advantage of recent advances in phylogenetic comparative methods and the availability of large-scale datasets to explore body size evolution in terrestrial vertebrates. Ancestral character estimation and disparity-through-time plots showed considerable variation in body size evolution, both across lineages and over time. In addition, regardless of the corresponding taxon, posterior predictive simulation demonstrated several consistent ways in which body size evolution in those groups departed from constant-rate models, namely: (1) there was considerable rate heterogeneity within each taxon, (2) there was a positive relationship between body size and its rate of evolution (i.e., large-bodied animals evolved faster than small-bodied ones), and (3) faster evolutionary rates near the present. Finally, geographical mapping of body mass and evolutionary rates revealed some similarities across taxa, but no clear latitudinal trends. Overall, these results indicate that there may be general patterns in the body size evolution on large scales in terrestrial vertebrates, with some intriguing taxon-specific differences.

Superflare rate variability on M dwarfs

ABSTRACT M dwarfs are often highly flare productive, and changes in the rate of flaring can potentially affect the radiation and energetic particles an exoplanet is exposed to. Rate variability has been found to be rare on G-type stars, and there has been limited study of the variability of flaring on M dwarfs. Using data from the TESS mission up to Observation Sector 66, we analyse 658 stars ranging from K7 to M5 to test for superflare rate variability by calculating an optimal piecewise constant-rate model for flare occurrence using a Bayesian algorithm and identify 66 stars with rate changes, a larger proportion than our previous study into G-type stars (7 out of 270 stars). We find that rate variability does not depend on the stellar parameters for our sample. We investigate how the flare-frequency distribution for these stars varies and whether this variation affects exoplanet habitability. No stars in our sample provide sufficient UV flux to support prebiotic chemistry. We investigate the phase distributions on the rate variable stars, finding 11 cases of potential phase dependence in flaring across seven stars. We also compare the Bayesian method to another measure of activity, the fraction of flux emitted through flares, and do not observe a consistent relationship between this flaring activity metric and the optimal Bayesian model. We discuss the possible reasons for the discrepancy and identify a problem with the flaring activity metric due to the power-law distribution of the flare events.

Ad Hoc Mesh Network Localization Using Ultra-Wideband for Mobile Robotics.

This article explores the implementation of high-accuracy GPS-denied ad hoc localization. Little research exists on ad hoc ultra-wideband-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots, and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node's field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration ad hoc localization system (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF then fuses the robot's odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts its estimated position to its neighbors to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile ad hoc localization network.

210Pb-dating of recent sediments with the χ-mapping CF and CSAR models. On the attractors

Conventional 210Pb-dating models use assumptions on sedimentary conditions that allow for analytical formulations. The novel χ-mapping models use numerical methods to generate and test a large number (∼106) of potential solvers. Empirical data (excess 210Pb vs. mass depth profile) serve to attract the solver that minimizes the χ function (the attractor), and it has been assumed that it also defines the most likely chronology. This work aims to test this assumption in a deep way. In synthetic and varved sediments, the performance of each solver can be quantified through a parameter ξa accounting for the deviation of the model and the true ages. This work studies the complex relationships between χ and ξa using the constant flux (χ-CF) and the constant sediment accumulation rate (CSAR) models, which operate in a parametric 3D space. The full mapping of the 3D χ function serves to find the absolute minimum, for the graphical representation of the complex topology of the attractors, which is model-specific, and for plotting clouds of chronological lines from solvers with varying χ values. The minimum value of ξa (the best chronology) is achieved for a wide range of χ values, including the region of the absolute minimum. In complex cases, tiny changes in χ can result in quite different chronologies. Alternative attractors that include a reference date and an objective function are studied. The results provide guidelines for strengthening the 210Pb-based chronologies.

Biogeographic Origin of Kurixalus (Anura, Rhacophoridae) on the East Asian Islands and Tempo of Diversification within Kurixalus.

The ancestral area of Kurixalus on the East Asian islands is under dispute, and two hypotheses exist, namely that distribution occurred only on the Asian mainland (scenario of dispersal) and that wide distribution occurred on both the Asian mainland and the East Asian islands (scenario of vicariance). In this study, we conducted biogeographic analyses and estimated the lineage divergence times based on the most complete sampling of species, to achieve a more comprehensive understanding on the origin of Kurixalus on the East Asian islands. Our results revealed that the process of jump dispersal (founder-event speciation) is the crucial process, resulting in the distribution of Kurixalus on the East Asian islands, and supported the model of the Asian mainland origin: that Kurixalus on the East Asian islands originated from the Asian mainland through two long-distance colonization events (jump dispersal), via the model of vicariance of a widespread ancestor on both the Asian mainland and the East Asian islands. Our results indicated that choices of historical biogeography models can have large impacts on biogeographic inference, and the procedure of model selection is very important in biogeographic analysis. The diversification rate of Kurixaus has slightly decreased over time, although the constant-rate model cannot be rejected.

Kinematic motion models based vessel state estimation to support advanced ship predictors

Advanced ship predictors can generally be considered as a vital part of the decision-making process of autonomous ships in the future, where the information on vessel maneuvering behavior can be used as the source of information to estimate current vessel motions and predict future behavior precisely. As a result, the navigation safety of autonomous vessels can be improved. In this paper, vessel maneuvering behavior consists of continuous-time system states of two kinematic motion models—the Curvilinear Motion Model (CMM) and Constant Turn Rate & Acceleration (CTRA) Model. Two state estimation algorithms—the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are implemented on these two models with certain modifications so that they can be compatible with discrete-time measurements. Four scenarios, created by combining different models and algorithms, are implemented using simulated ship maneuvering data from a bridge simulator. These scenarios are then verified through the proposed stability and consistency tests. The simulation results show that the EKF tends to be unstable combined with the CMM. The estimates from the other three scenarios can generally be considered more stable and consistent, unless sudden actions or variations in vessel heading occurred during the simulation. The CTRA is also proven to be more robust compared to the CMM. As a result, a suitable combination of mathematical models and estimation filters can be considered to support advanced ship predictors in future ship navigation.

210Pb-based dating of recent sediments with the χ-mapping version of the Constant Sediment Accumulation Rate (CSAR) model

The 210Pb-based method aims at determining the absolute age of recent sediments on the centennial scale. A family of models assumes that at the sediment-water interface the flux of unsupported 210Pb (210Pbexc), F, relates to its initial activity concentration, Ao, and the mass sedimentation rate, w, as: F=Aow. Additional specific assumptions that allow for analytical formulations of the models are: i) constant Ao (CIC), constant F (CF), and constant F with constant w (CFCS). A model with constant w (CSAR) was suggested for completeness but never used because of the lack of a suitable analytical formulation. The TERESA model assumes random and independent variability for Ao and w, described by normal distributions. It systematically generates a large number (∼105) of potential solutions, whose performance for fitting the empirical 210Pbexc profile is quantified through the χ-function. This work aims to adapt the above methodology to formulate the χ-mapping version of the CSAR model. The performance of the model is evaluated with a set of synthetic and real cores for which an independent chronology is available. CSAR is able to capture the mean sedimentation rate from the 210Pbexc data and provides reliable chronologies and paleorecords of Ao, useful for tracking past changes in sedimentary conditions. CSAR provides an interesting different perspective for researchers working with 210Pb-based dating of recent sediments.

Dynamic Analysis of the Timing of Survey Participation: An Application of Event History Analysis of the Stochastic Process of Response in a Probability-Based Multi-Wave Panel With Computer-Assisted Interview Modes

The response patterns across the fieldwork period are analyzed in the context of a panel study with a sequential mixed-mode design including a self-administered online questionnaire and a computer-assisted telephone interview. Since the timing of participation is modelled as a stochastic process of individuals’ response behaviour, event history analysis is applied to reveal time-constant and time-varying factors that influence this process. Different distributions of panelists’ propensity for taking part in the web-based survey or, alternatively, in the computer-assisted telephone interview can be considered by hazard rate analysis. Piecewise constant rate models and analysis of sub-episodes demonstrate that it is possible to describe the time-related development of response rates by reference to individuals’ characteristics, resources and abilities, as well as panelists’ experience with previous panel waves. Finally, it is shown that exogenous factors, such as a mixed-mode survey design, the incentives offered to participants and the reminders that are sent out, contribute significantly to time-related response after the invitation to participate in a survey with a sequential mixed-mode design. Overall, this contribution calls for a dynamic analysis of response behaviour instead of the categorization of response groups.

Elucidating factors governing MICP biogeochemical processes at macro-scale: A reactive transport model development

Microbial Induced Calcium Carbonate Precipitation (MICP) influenced by biofilm metabolism in the subsurface can be exploited for a variety of engineered applications encompassing geotechnical ground improvement, environmental bioremediation, and hydraulic barriers. A reactive transport model was developed to determine the effects of controlling factors in terms of treatment protocols and experimental methods. Six column tests were calibrated and a range for the key parameters was determined. Fifteen key parameters of MICP reactive transport model were assessed in four categories (microbial activity and attachment, sample preparation, treatment protocol, and experiment dimensions). The results emphasized the effects of three main factors of microbial activity, microbial attachment process, and number of treatment (among all 15 assessed parameters) on the calcium carbonate (CaCO3) precipitation content and distribution. An increase in specific ureolysis rate (Ku) and attachment rate coefficient (Kat) by two orders of magnitude improves average CaCO3 by up to 13% and 6%, respectively with non-uniformity (COV) increase of 16%. Higher flow rates and solution concentrations contribute to more uniform CaCO3 distribution. The constant attachment rate model is useful to yield the CaCO3 precipitation profiles but more accurate models are needed to capture exact distribution. Post-treatment hydraulic conductivity, porosity and attached biomass were assessed.

Estimating Hydraulic Parameters of Aquifers Using Type Curve Analysis of Pumping Tests with Piecewise-Constant Rates

Aquifer hydraulic parameters play a critical role in investigating various groundwater hydrology problems (e.g., groundwater depletion and groundwater transport), and the Theis formula for constant-rate pumping tests is commonly used to estimate them. However, the pumping rate in the field usually varies with time due to some factors, making the classical constant-rate model unsuitable for accurate parameter estimation. To address this issue, we developed a novel dimensionless-form analytical solution for variable-rate pumping tests involving piecewise-constant approximations for variable pumping rates. Analysis of the time–drawdown curves revealed that the first-step type curve was consistent with the Theis curve. However, the curves of subsequent steps deviated from the Theis curve and were associated with the first dimensionless inflection time (t1,D), which depended on the hydraulic conductivity (K) and specific storage (Ss) of the confined aquifers. On this basis, a new type curve method for estimating the aquifer K and Ss was proposed by matching the observed drawdown data with a series of type curves dependent on t1,D. Furthermore, this method can handle recovery drawdown data. We applied this method to a field site in Wuxi City, Jiangsu Province, China, by analyzing the drawdown data from four pumping tests. The hydraulic parameters estimated using this method were in close agreement with those calibrated via PEST. The calibrated K values were further validated by comparing them with lithology-based results. In summary, the geometric means of K and Ss were 6.62 m/d and 3.16 × 10−5 m−1 for the first confined aquifer and 0.92 m/d and 2.34 × 10−4 m−1 for the second confined aquifer.

Exceptional levels of species discovery ameliorate inferences of the biogeography and diversification of an Afrotropical catfish family

Endeavours in species discovery, particularly the characterisation of cryptic species, have been greatly aided by the application of DNA molecular sequence data to phylogenetic reconstruction and inference of evolutionary and biogeographic processes. However, the extent of cryptic and undescribed diversity remains unclear in tropical freshwaters, where biodiversity is declining at alarming rates. To investigate how data on previously undiscovered biodiversity impacts inferences of biogeography and diversification dynamics, we generated a densely sampled species-level family tree of Afrotropical Mochokidae catfishes (220 valid species) that was ca. 70 % complete. This was achieved through extensive continental sampling specifically targeting the genus Chiloglanis a specialist of the relatively unexplored fast-flowing lotic habitat. Applying multiple species-delimitation methods, we report exceptional levels of species discovery for a vertebrate genus, conservatively delimiting a staggering ca. 50 putative new Chiloglanis species, resulting in a near 80 % increase in species richness for the genus. Biogeographic reconstructions of the family identified the Congo Basin as a critical region in the generation of mochokid diversity, and further revealed complex scenarios for the build-up of continental assemblages of the two most species rich mochokid genera, Synodontis and Chiloglanis. While Syndontis showed most divergence events within freshwater ecoregions consistent with largely in situ diversification, Chiloglanis showed much less aggregation of freshwater ecoregions, suggesting dispersal as a key diversification process in this older group. Despite the significant increase in mochokid diversity identified here, diversification rates were best supported by a constant rate model consistent with patterns in many other tropical continental radiations. While our findings highlight fast-flowing lotic freshwaters as potential hotspots for undescribed and cryptic species diversity, a third of all freshwater fishes are currently threatened with extinction, signifying an urgent need to increase exploration of tropical freshwaters to better characterise and conserve its biodiversity.

Compressed Sensing-Based Genetic Markov Localization for Mobile Transmitters

With the strengths of quickness, low cost, and adaptability, unmanned aerial vehicle (UAV) communication is widely utilized in the next-generation wireless network. However, some risks and hidden dangers such as UAV “black flight” disturbances, attacks, and spying incidents lead to the necessity of the real-time supervision of UAVs. A compressed sensing-based genetic Markov localization method is proposed in this paper for two-dimensional trajectory tracking of the mobile transmitter in a finite domain, which consists of three modules: the multi-station sampling module, the reconstruction module, and the localization module. In the multi-station sampling module, multiple stations are deployed to receive the signal transmitted by the UAV using compressed sensing, and the motion model of the mobile transmitter is the constant turn rate and acceleration (CTRA) model. In the reconstruction module, we propose a direct reconstruction method to extract the joint cross-spatial spectrum. In the genetic Markov localization module, we propose a two-step localization method to genetically correct the inaccurate points in the preliminary results and generate the tracking result. Extensive simulations are conducted to verify the effectiveness of the proposed method. The results show that the proposed method is superior to the particle filter method and the Markov Monte Carlo method at all sampling moments. Specifically, when SNR = 15dB, the root-mean-square error (RMSE) of the proposed method is 39% and 60% lower than that of the other two methods, respectively. Moreover, under the premise that the RMSE of the localization result is less than 30 m, the reconstruction module can reduce the running time of the proposed method by 33.3%.

3D Multi-Object Tracking With Adaptive Cubature Kalman Filter for Autonomous Driving

A crucial and challenging issue in autonomous driving is dynamic road environment detection and 3D multi object tracking. In this article, we propose a novel framework for online 3D multi-object tracking to eliminate the influence of inherent uncertainty and unknown biases in point cloud. A constant turn rate and velocity (CTRV) motion model is employed to estimate the future motion state, which are smoothed by a cubature Kalman filter (CKF) algorithm. A new affinity model is introduced to evaluate the similarity between trajectories and candidate detections for accurate and reliable data association which can be formulated as a bipartite matching problem. An adaptive cubature Kalman filter (ACKF) is given to remove the influence of unknown bias and to robustly update the tracked state. Accuracy and speed of the proposed tracking method are evaluated on the KITTI 3D multi-object tracking dataset, showing superior performance than the baselines.

Observed Rate Variations in Superflaring G-type Stars

Flare occurrence on the Sun is highly variable, exhibiting both short-term variation due to the emergence and evolution of active regions, and long-term variation from the solar cycle. On solar-like stars, more energetic stellar flares (superflares) have been observed, and it is of interest to determine whether the observed rates of superflare occurrence exhibit similar variability to solar flares. We analyze 274 G-type stars using data from the Transiting Exoplanet Survey Satellite and identify seven stars which exhibit statistically significant changes in the rate of superflare occurrence by fitting a piecewise constant-rate model with the Bayesian blocks algorithm. We investigate the properties of these stars and their flaring rates, and discuss the possible reasons for the low number of stars with detectable rate variation.

Cryptic diversity impacts model selection and macroevolutionary inferences in diversification analyses.

Species persist in landscapes through ecological dynamics but proliferate at wider spatial scales through evolutionary mechanisms. Disentangling the contribution of each dynamic is challenging, but the increasing use of dated molecular phylogenies opened new perspectives. First, the increasing use of DNA sequences in biodiversity inventory shed light on a substantial amount of cryptic diversity in species-rich ecosystems. Second, explicit diversification models accounting for various eco-evolutionary models are now available. Integrating both advances, we explored diversification trajectories among 10 lineages of freshwater fishes in Sundaland, for which time-calibrated and taxonomically rich phylogenies are available. By fitting diversification models to dated phylogenies and incorporating DNA-based species delimitation methods, the impact of cryptic diversity on diversification model selection and related inferences is explored. Eight clades display constant speciation rate model as the most likely if cryptic diversity is accounted, but nine display a signature of diversification slowdowns when cryptic diversity is ignored. Cryptic diversification occurs during the last 5 Myr for most groups, and palaeoecological models received little support. Most cryptic lineages display restricted range distribution, supporting geographical isolation across homogeneous landscapes as the main driver of diversification. These patterns question the persistence of cryptic diversity and its role during species proliferation.

Variable rate air-assisted spray based on real-time disease spot identification.

Currently, the variable-rate application (VA) of agrochemicals on fruit trees is based on canopy volume and biomass. The canopy volume has a significant relationship with disease resistance and degree of disease incidence. Therefore, this study proposes a VA method that uses deep convolutional neural networks for real-time recognition of disease spots on pear trees. Furthermore, it specifies the limitations and application scenarios of the disease spot recognition. Field performance tests were conducted to verify the performance of the proposed VA system. The results showed a mean average precision, precision, and recall of 87.42%, 83.76%, and 87.23%, respectively. The spot recognition rate was 81.3% when the canopy sampling distance, spot diameter, and canopy porosity were 1.2m, 4-8 mm, and 55.76%, respectively. The results indicate that the proposed VA system saved 51.9% spray volume compared to conventional methods while ensuring quality. Compared to the traditional constant rate model, the proposed VA technology based on real-time disease spot identification can reduce spraying in nondiseased areas, thereby abandoning the previous saturation application practice and significantly reducing pesticide use. © 2022 Society of Chemical Industry.

Multiple-Kernelized-Correlation-Filter-Based Track-Before-Detect Algorithm for Tracking Weak and Extended Target in Marine Radar Systems

This article addresses the problem of tracking weak and extended targets in the clutter for marine radar systems. In the proposal, multiple kernelized correlation filters (MKCFs) incorporate a low-threshold constant false alarm rate and segmentation model under the principle of multiframe track before detect (MF-TBD). By setting the similarity score of the correlation filter as the test statistic, the maximization of the integration over frames can be solved by the essentially exhaustive searching of the MKCF. Since the correlation filter measures the similarity of the intensity distributions in the extended templates, the proposed method can differentiate the weak target from the surrounding clutter and other targets at a close range. Compared to other amplitude-based MF-TBD methods, it performs better in detecting and tracking extended targets in the real-radar data with heavy clutter caused by floating sea ice and the simulations with Rayleigh and $K$-distributed sea clutters.

The obstacle avoidance assistance control of multi-axle distributed heavy vehicles

Based on the artificial potential field theory, a hierarchical obstacle avoidance assisted driving framework is proposed in this paper, in order to solve the obstacle avoidance assisted driving problem of distributed heavy vehicles. Initially, a desired lateral position potential field (DLPPF) that reflects the driver’s driving intention is applied based on the constant turn rate and velocity (CTRV) model. And a real-time obstacle avoidance path can be obtained and further updated through a comprehensive consideration of the safety of obstacle avoidance and the obstacle repulsion potential field (ORPF). In addition, a differential drive assistance steering (DDAS) on the heavy vehicle steering bridge has been adopted to realize avoiding obstacles, and additional yaw moment to the vehicle’s non-steering axle has been utilized to ensure the maneuverability and stability of vehicle. Aiming to solve the lower layer control problem, a variable weight controller based on model predictive control (MPC) is designed to coordinate path tracking performance and dynamics control. Finally, through simulations and comparisons, the effectiveness of the obstacle avoidance strategy is verified.