Browse Topic: Logistics

Items (6,918)
In commercially available electric motorcycles, there is a notable shift in the cooling method, moving from air cooling to water cooling, and in the winding method, moving from concentrated winding to distributed winding, as the output increases. This shift occurs around 8 to 10 kW. However, there is a paucity of empirical investigations examining these combinations to ascertain their optimality. In order to verify this trend, a verification model has been constructed which allows for the comparison of the capacity and weight of the motor and cooling system according to the vehicle’s required output and thermal performance. A comparison and verification of the combinations of winding methods (concentrated winding or segment conductor distribution winding) and cooling systems (water-cooled or air-cooled) was conducted using the model that had been constructed. In the motor designed for this study, when the maximum output of the vehicle was 35 kW or less (European A2 license), the total
Otaki, RyotaTsuchiya, TeruyukiSakai, YuYamauchi, TakuyaShimizu, Tsukasa
The EU currently has very ambitious plans for the electrification of vehicles, particularly in the field of urban logistics. For example, the so-called “Transport White Paper” [1] aims to achieve essentially CO2-free logistics in major urban centers by 2030, while “Europe on the move” [2] has presented a series of legislative initiatives. The Strategic Research and Innovation Agenda for Transport proposes research priorities and actions to deploy innovative solutions, with a particular focus on the electrification of transport. Numerous advancements in electromobility have led to a growing number of vehicles available in various areas, particularly in urban logistics. New concepts like cargo bikes and micro-vehicles are being developed, but they cannot fully replace traditional light commercial vehicles. While some electrified options exist, they are often modified versions of existing platforms with internal combustion engines swapped for electric drives. The research work in this
Königshofer, ThomasTromayer, JürgenSchacht, Hans-JürgenWang, Eric
Topology optimization (TO) in electrochemical systems has recently attracted many researchers. Previous studies suggested minimal performance differences between 2D and 3D designs, indicating that 2D models suffice to enhance performance, especially in unidirectional flow scenarios. A later study found that the concentration distribution in an optimized 2D flow system differed from that in a unidirectional flow system. We posited that pulsating flow could further enhance the performance of such systems. First, we initiated TO for a diffusion-reaction system in a steady state. The optimized structure obtained from this process served as the foundation for subsequent investigations involving a pulsating flow source in convection-diffusion-reaction systems. We introduced two different systems with distinct flow natures: one characterized by a flow nature of 1D and the other by a flow nature of 2D. The results demonstrated that the optimized structure with a heterogeneous distribution
Long, MenglyAlizadeh, MehrzadSun, PengfeiCharoen-amornkitt, PatcharawatSuzuki, TakahiroTsushima, Shohji
The relation between the multiple auto-ignition in the premixed charge with fuel concentration distribution and associated pressure wave are numerically investigated. This study assumes that the auto-ignition phenomenon in the end-gas of PCCI combustion, a next-generation combustion method which is expected to achieve both low fuel consumption and low emissions at a high level. Detailed numerical analysis considering the elementary chemical reactions of the compressible reacting fluid flow described in the one-dimensional coordinate system with high spatial and time resolution was performed to clarify the detailed phenomena of the onset of the multiple auto-ignition and the pressure wave propagation in the gas.
Iizumi, KotaYoshida, Kenji
In order to rapidly achieve the goal of global net-zero carbon emissions, ammonia (NH3) has been deemed as a potential alternative fuel, and reforming partial ammonia to hydrogen using engine exhaust waste heat is a promising technology which can improve the combustion performance and reduce the emission of ammonia-fueled engines. However, so far, comprehensive research on the correlation between the reforming characteristic for accessible engineering applications of ammonia catalytic decomposition is not abundant. Moreover, relevant experimental studies are far from sufficient. In this paper, we conducted the experiments of catalytic decomposition of ammonia into hydrogen based on a fixed-bed reactor with Ru-Al2O3 catalysts to study the effects of reaction temperature, gas hour space velocity (GHSV) and reaction pressure on the decomposition characteristics. At the same time, energy flow analysis was carried out to explore the effects of various reaction conditions on system
Li, ZeLi, TieChen, RunLi, ShiyanZhou, XinyiWang, Ning
In Automobile manufacturing, maintaining the Quality of parts supplied by vendor is crucial & challenging. This paper introduces a digital tool designed to monitor trends for critical parameters of these parts in real-time. Utilizing Statistical Process Control (SPC) graphs, the tool continuously tracks Quality trend for critical parts and process parameters, predicting potential issues for proactive improvements even before parts are supplied. The tool integrates data from all Supplier partners across value chain into a single ecosystem, providing a comprehensive view of their performance and the parts they supply. Suppliers input data into a digital application, which is then analyzed in the cloud using SPC techniques to generate potential alerts for improvement. These alerts are automatically sent to both Suppliers and relevant personnel at the OEM, enabling proactive measures to address any Quality deviations. 100% data is visualized in an integrated dashboard which acts as a
Sahoo, PriyabrataGarg, IshanRawat, SudhanshuNarula, RahulGupta, AnkitBindra, RiteshRao, Akkinapalli VNGarg, Vipin
As a crucial tool for lunar exploration, lunar rovers are highly susceptible to instability due to the rugged lunar terrain, making control of driving stability essential during operation. This study focuses on a six-wheel lunar rover and develops a torque distribution strategy to improve the handling stability of the lunar rover. Based on a layered control structure, firstly, the approach establishes a two-degree-of-freedom single-track model with front and rear axle steering at the state reference layer to compute the desired yaw rate and mass center sideslip angle. Secondly, in the desired torque decision layer, a sliding mode control-based strategy is used to calculate the desired total driving torque. Thirdly, in the torque distribution layer, the optimal control distribution is adopted to carry out two initial distributions and redistribution of the drive torque planned by the upper layer, to improve the yaw stability of the six-wheeled lunar rover. Finally, a multi-body dynamics
Liu, PengchengZhang, KaidiShi, JunweiYang, WenmiaoZhang, YunqingWu, Jinglai
This study experimentally investigates the liquid jet breakup process in a vaporizer of a microturbine combustion chamber under equivalent operating conditions, including temperature and air mass flow rate. A high-speed camera experimental system, coupled with an image processing code, was developed to analyze the jet breakup length. The fuel jet is centrally positioned in a vaporizer with an inner diameter of 8mm. Airflow enters the vaporizer at controlled pressures, while thermal conditions are maintained between 298 K and 373 K using a PID-controlled heating system. The liquid is supplied through a jet with a 0.4 mm inner diameter, with a range of Reynolds numbers (Reliq = 2300÷3400), and aerodynamic Weber numbers (Weg = 4÷10), corresponding to the membrane and/or fiber breakup modes of the liquid jet. Based on the results of jet breakup length, a new model has been developed to complement flow regimes by low Weber and Reynolds numbers. The analysis of droplet size distribution
Ha, NguyenQuan, NguyenManh, VuPham, Phuong Xuan
Battery cell aging and loss of capacity are some of the many challenges facing the widespread implementation of electrification in mobility. One of the factors contributing to cell aging is the dissimilarities of individual cells connected in a module. This paper reports the results of several aging experiments using a mini-module consisting of seven 5 Ah 21700 lithium-ion battery cells connected in parallel. The aging cycle comprised a constant current-constant voltage charge cycle at a 0.7C C-rate, followed by a 0.2C constant current discharge, spanning the useful voltage range from minimum to maximum according to the cell manufacturer. Charge and discharge events were separated by one-hour rest periods and were repeated for four weeks. Weekly reference performance tests were executed to measure static capacity, pulse power capability and resistance at different states of charge. All diagnostics were normalized with respect to their starting numbers to achieve a percentage change
Swarts, AndreSalvi, Swapnil S.Juarez Robles, Daniel
Growth in the EV market is resulting in an unprecedented increase of electrical load from EV charging at the household level. This has led to concern about electric utilities’ ability to upgrade electrical distribution infrastructure at an affordable cost and sufficient speed to keep up with EV sales. Adoption of EVs in the California market has outpaced the national average and offers early insight for other regions of the United States. The Sacramento Municipal Utility District (SMUD) partnered with two grid-edge Distributed Energy Resource Management System (DERMS) providers, the OVGIP (recently incorporated as ChargeScape, a joint venture of Ford, BMW, Honda, and Nissan) and Optiwatt, to deliver a vehicle telematics-based active managed charging pilot. The pilot program, launched in Summer 2022 enrolled approximately 1,200 EVs over two years including Tesla, Ford, BMW, and GM vehicles. The goal of this pilot program was to evaluate the business case for managed charging to mitigate
Liddell, ChelseaSchaefer, WalterDreffs, KoraMoul, JacobKay, CarolAswani, Deepak
The automotive aerodynamic development relies on wind tunnel testing and Computational Fluid Dynamics (CFD), where the former provides reliable values to be used for fuel economy calculations, and the latter enables the investigation of flow features responsible for improvement/degradation of the average large-scale performances in terms of aerodynamic coefficients. The abovementioned procedure overlooks a crucial factor however: natural wind. The speed and the direction of natural wind encountered while driving alters the vehicle’s effective yaw angle. Such condition implies that the minimization of the drag coefficient at zero-yaw, commonly performed through wind tunnel and CFD simulations in an industrial context, may not yield real-world optimal shapes. While it is possible to reproduce natural wind-like conditions in a wind tunnel using flaps, for example, the input signal to the flap system must be available beforehand, and such key element is the focus of the present research
Nucera, FortunatoOnishi, YasuyukiMetka, Matt
This study introduces an innovative torque vectoring control strategy designed to enhance ride comfort in autonomous electric vehicles. The approach seamlessly integrates steering and rear axle force control within a model predictive control (MPC) framework, enabling real-time optimization of comfort and handling performance. The proposed control method is applied to a two-rear-motor vehicle model, where the MPC algorithm adjusts steering angles and tire forces to minimize discomfort caused by yaw rate and lateral acceleration. Simulation results from a lane-change scenario demonstrate significant improvements in comfort metrics compared to conventional torque vectoring control strategies. The findings highlight the ability of the proposed method to significantly enhance ride comfort without compromising vehicle dynamics. This integrated and adaptive control strategy offers a promising solution for improving passenger satisfaction in autonomous electric vehicles, with potential
Zhao, BolinLou, BaichuanHe, XianqiXue, WanyingLv, Chen
Distributed electric vehicles, equipped with independent motors at each wheel, offer significant advantages in flexibility, torque distribution, and precise dynamic control. These features contribute to notable improvements in vehicle maneuverability and stability. To further elevate the overall performance of vehicles, particularly in terms of handling, stability, and comfort, this paper introduces an coordinated control strategies for longitudinal, lateral, and vertical motion of distributed electric vehicles. Firstly, a full-vehicle dynamics model is developed, encompassing interactions between longitudinal, lateral, and vertical forces, providing a robust framework for analyzing and understanding the intricate dynamic behaviors of the vehicle under various operating conditions. Secondly, a vehicle motion controller based on Model Predictive Control is designed. This controller employs a sophisticated multi-objective optimization algorithm to manage and coordinate several critical
Jia, JinchaoYue, YangSun, AoboLiu, Xiao-ang
With the advancement of intelligent transportation and smart logistics systems, tractor semi-trailers have gradually become one of the primary modes of transport due to their substantial cargo capacity. However, the growing number of tractor semi-trailers has raised significant traffic safety concerns. Due to their significant spring mass and strong body strength, accidents involving tractor semitrailers often result in severe consequences. Active collision avoidance control strategies provide assurance for vehicle safety. However, existing research predominantly focuses on passenger cars and small commercial vehicles. Research specifically addressing tractor semi-trailers, which have longer bodies and more complex dynamic characteristics, is relatively sparse. Therefore, this paper proposes a collision risk assessment-based longitudinal collision avoidance control strategy for tractor semi-trailers with slip ratio control. Firstly, the paper introduces the braking characteristics and
Yan, YangZheng, HongyuZhang, Yuzhou
The research object of this project is the anti-slip and lateral stability control technique for a distributed three-axis drive vehicle. What differs from the traditional four-motor power system layout is that the third axle has two motors, while the second axle only has one motor. Compared with the traditional design, this layout can reduce dependence on battery performance and maintain motor operation in a high-efficiency range by switching between different operating modes. For example, when driving at high speeds, only the motor on the second axle works, which can improve motor efficiency. When accelerating or climbing, all motors work to provide a large power output. In the research, the vehicle model was first established in Simulink, and then co-simulated with TruckSim. The drive anti-slip control first identified the optimal slip rate for the road, and then used the sliding mode control to determine the driving torque for each wheel, achieving good control effects under various
Shen, RuitengZheng, HongyuKaku, ChuyoZong, Changfu
This paper presents a new regression model-based method for accurate predictions of stiffness of different glass laminate constructions with a point-load bending test setup. Numerical FEA models have been developed and validated with experimental data, then used to provide training data required for the statistical model. The multi-variable regression method considered six input variables of total glass thickness, thickness ratio of glass plies as well as high-order terms. Highly asymmetrical, hybrid laminates combining a relatively thick soda-lime glass (SLG) ply joined with a relatively thin Corning® Gorilla® Glass (GG) ply were analyzed and compared to standard symmetrical SLG-SLG constructions or a monolithic SLG with the same total glass thickness. Both stiffness of the asymmetrical laminates and the improvement percentage over the standard symmetrical design can be predicted through the model with high precision.
Yu, ChaoCleary, ThomasJoubaud, Laurentkister, EvanFisher, W Keith
One challenge for autonomous vehicle (AV) control is the variation in road roughness which can lead to deviations from the intended course or loss of road contact while steering. The aim of this work is to develop a real-time road roughness estimation system using a Bayesian-based calibration routine that takes in axle accelerations from the vehicle and predicts the current road roughness of the terrain. The Bayesian-based calibration method has the advantage of providing posterior distributions and thus giving a quantifiable estimate of the confidence in the prediction that can be used to adjust the control algorithm based on desired risk posture. Within the calibration routine, a Gaussian process model is first used as a surrogate for a simulated half-vehicle model which takes vehicle velocity and road surface roughness (GD) to output the axle acceleration. Then the calibration step takes in the observed axle acceleration and vehicle velocity and calibrates the Gaussian process model
Lewis, EdwinaParameshwaran, AdityaRedmond, LauraWang, Yue
A methodology for optimizing natural properties of a powertrain for an electric vehicle has been presented. A model with six-degree-of-freedom was proposed utilizing ADAMS, and the natural frequencies and energy distribution of the powertrain are estimated using the proposed model. The calculated natural frequencies and energy distribution shown that the initial design of mount stiffness does not meet requirements of natural frequency and decoupling ratio, and vibration isolation standards. To overcome the limitations of conventional optimization techniques, a non-dominated sorting genetic algorithm (NSGA) was adopted for the enhancement optimization the mounts parameters. The optimization objectives included the refinement of the decoupling rates and frequency distribution at all mounting directions. Stiffness parameters of the mounts were optimized via the NSGA. The optimized results confirmed significant improvements for powertrain natural characteristics. This study presented an
Jin, YangLi, DeweiZhao, YangXiao, LeiGuo, Yiming
Fatigue design is invariably of prior concern for the automotive industry, no matter of the evolution of the mobility market: at first because carmakers must stay compliant with general structural integrity requirements for reliability, notably applicable to the chassis system, then due to the endless competition for lightweighting in order to mitigate product costs and/or enhance vehicle efficiency. In the past, this key performance was often tackled by basic reference load cases, making use of the simplest signal content, e.g. sinus functions, to practice constant amplitude loads on test rigs and for computations, respectively. Nowadays, full time series coming from proving ground measurements, or any corresponding virtual road load data computations, may be applied to feed complex vehicle computations for virtual assessment and complex test facilities for final approval, under variable amplitude loads. In between, the concept of load spectra (i.e. distribution of amplitudes with
Facchinetti, Matteo LucaTjhung, TanaJaffre lng, SébastienDatta, SandipHayat lng, RomainGuo, Mingchao
Comprehensive requirements generation is a critical stage of the design process. Requirements are used to bound the design space and to guide the selection and evaluation of various solutions. Requirements can be categorized as either functional, defining things that the solution must do (such as produce a certain amount of horsepower), or non-functional, defining desirable qualities of the solution (such as weigh less than a particular value). Functional requirements are relatively easy to define and are often associated with particular components or subsystems within the design. As such, they can be the main focus of academic design instruction and therefore the design projects undertaken by novice designers. However, non-functional requirements (NFRs) capture important characteristics of the design solution and should not be ignored. Because of their nature, they are also difficult to assign to a particular subset of components or subsystem within the system. In this study, a group
Sutton, MeredithAnbuvanan, AadithanCastanier, Matthew P.Turner, CameronKurz, Mary E.
Using SolidWorks software's precision capabilities, an initial 3D digital model of the tire changer was constructed and then imported into Ansys for static structural analysis. By applying different meshing forms to the bow-shaped component of the tire changer and executing an exhaustive array of load simulation solutions, the total deformation and distribution of maximum principal stress of the bow-shaped component were obtained, enabling an assessment of its stress distribution and structural response under operating conditions. According to the results of the solution calculations, the total deformation and maximum principal stress distribution obtained from the hexahedral-dominated meshing method were nearly identical to those from the surface meshing method. Based on the finite element analysis results, structural optimization design was carried out on the initial 3D model of the tire changer, mainly through the reinforcement and local hollow design to achieve the increase of
Zhu, HengjiaGao, YunyiYao, YananChao, Wang
The demand for eco-friendly electric powertrains has increased significantly in recent years. Cells are the most crucial component of a battery pack, directly influencing the dimensions, range, lifespan, performance, and cost of electric vehicles. Lithium-ion cells outperform other cell chemistries due to their higher energy density, allowing for more compact and lightweight designs while providing longer operational ranges. It is crucial that lithium-ion cell packaging complies with assembly requirements to maximize its lifespan and ensure operational safety. Assembly force requirements of lithium-ion cells are critical to ensure optimal cell performance throughout its lifetime & enhance the longevity of the battery pack. The compression pad between cells ensures appropriate cell assembly pressure. The service life is how long a lithium-ion cell can operate effectively, while the cyclic life refers to the number of charge-discharge cycles before cell functional degradation. The cell
Varambally, VishakhaSithick basha, AbubakkerChalumuru, MadhuSasikumar, K
The upcoming EURO 7 and EPA Tier 4 regulations and the possible China 7 are expected to tighten the tailpipe particulate emissions limits significantly. High performance Gasoline Particulate Filters (GPFs) with high filtration efficiency and low pressure drop would be mandated for gasoline engines to meet these stringent regulations. Due to packaging constraints, GPFs are often coated with three-way catalyst (TWC) materials to achieve four-way functionality. Ash accumulation in GPFs also has a significant impact on the performance of GPFs. This paper utilizes 3D CFD to predict the transient filtration efficiency and pressure drop of a washcoated GPF with ash accumulation during the soot loading process. Simulation results show a decent match with experimental data. The 3D CFD model also provides detailed information on soot penetration in the GPF wall substrate and soot cake characteristics on the wall. These information can be crucial for GPF wall substrate design and washcoating
Yang, PengzeCheng, Zhen
Developing safe and reliable autonomous vehicles is crucial for addressing contemporary mobility challenges. While the goal of autonomous vehicle development is full autonomy, up to SAE Level 4 and beyond, human intervention remains necessary in critical or unfamiliar driving scenarios. This article introduces a method for gracefully degrading system functionality and seamlessly transferring decision-making and control between the autonomous system and a remote safety operator when needed. This transfer is enabled by an onboard dependability cage, which continuously monitors the vehicle’s performance during its operation. The cage communicates with a remote command control center, allowing for remote supervision and intervention by a safety driver. We assess this methodology in both lab and test field settings in a case study of last-mile parcel delivery logistics and discuss the insights and results obtained from these evaluations.
Aniculaesei, AdinaAslam, IqraZhang, MengBuragohain, AbhishekVorwald, AndreasRausch, Andreas
In an era where technological advancements are rapid and constant, the U.S. Army will need a more agile and efficient approach to modernizing systems on succeeding generations of Army vehicles. Legacy platforms like Abrams, Stryker, and Bradley vehicles use multiple mission computers tied to individual sensors that often required the addition of “boxes” to accommodate new capabilities, which could take years to deploy and drove sustainment costs up due to vendor lock. In addition, this antiquated approach doesn't leverage data to converge effects across the formation in a multi-domain environment. Centralized, common computing as detailed in GCIA would help solve this problem, potentially linking all major subsystems and providing higher-speed processing to assess large datasets in real time with AI and ML algorithms. By using a common, open architecture computer, the Army will be able to rapidly integrate new capabilities inside one box, versus adding multiple boxes. This pivotal
This research investigates how distributed energy resources (DERs) and electric vehicles (EVs) affect distribution networks. With sensitivity analysis, the research focuses on how these integrations affect load profiles. The research focuses on sizing of various DERs and EV charging/discharging strategies to optimize the load profile, voltage stability, and network loss minimization. System parameters including load profile, EV charging pattern, weather conditions, DER sizes, and electricity pricing are analyzed to quantify their individual and combined impacts on load variability. However, with increased capacity of DERs, network losses increase. A mathematical model with system and operational constraints has been developed and simulated in MATLAB Simulink environment, validation of the proposed approach in improving the load profile, and reduction in network losses, with the intermittent power generation from DERs and EV integration. Simulation result shows that optimal capacity of
Khedar, Kamlesh KumarGoyal, Govind RaiSingh, Pushpendra
This study investigates the precursors of crashes under varying traffic states through an in-depth analysis of freeway traffic data. This method effectively addresses the limitations associated with using surrogate measures in traffic safety research. We used the k-means clustering method to categorize traffic states into three types: free flow, transitional state, and congested flow. By employing the case-control study experimental approach, we conducted an in-depth analysis of the traffic data. During the feature selection process, we set matching rules to choose control group data that meet the criteria of time, location, and traffic state. Initially, traffic flow feature variables were constructed based on multiple dimensions, including time window width, spatial location, traffic flow parameters, and statistical characteristics. To reduce feature multicollinearity, we used correlation matrices and variance inflation factors (VIF). We then applied Recursive Feature Elimination (RFE
Zhou, FeixiangLiu, ShaoweihuaFeng, ShiZhang, YujieLuo, Xi
Shared autonomous vehicles systems (SAVS) are regarded as a promising mode of carsharing service with the potential for realization in the near future. However, the uncertainty in user demand complicates the system optimization decisions for SAVS, potentially interfering with the achievement of desired performance or objectives, and may even render decisions derived from deterministic solutions infeasible. Therefore, considering the uncertainty in demand, this study proposes a two-stage robust optimization approach to jointly optimize the fleet sizing and relocation strategies in a one-way SAVS. We use the budget polyhedral uncertainty set to describe the volatility, uncertainty, and correlation characteristics of user demand, and construct a two-stage robust optimization model to identify a compromise between the level of robustness and the economic viability of the solution. In the first stage, tactical decisions are made to determine autonomous vehicle (AV) fleet sizing and the
Li, KangjiaoCao, YichiZhou, BojianWang, ShuaiqiYu, Yaofeng
Most autonomous vehicles employ a relatively conservative lane-changing strategy in freeway system. In the diversion areas, autonomous vehicles typically initiate lane-changing to curb lanes at lower speeds at a considerable distance from the diversion point, resulting in a decrease in the overall traffic efficiency within the diversion areas. However, lane-changing decision points excessively close to exit ramps can exacerbate the urgency of the lane-changing process, prompting irrationally forced lane-changing and increasing the collision risk. To provide decision-making references for the safe and rapid diverging of autonomous vehicles in freeway diversion areas, this study proposes a minimum diversion decision distance (MDDD) model for autonomous vehicles through microscopic lane-changing trajectory data. Specifically, the lane-changing process was divided into waiting for the acceptable gap stage and executing the lane-changing stage in this model. Subsequently, UAV aerial
Li, ZhenFaLuo, BaoGuoYang, QiChen, XuPan, BingHong
To accurately predict the fuel consumption of vehicles, this study proposes a vehicle fuel consumption prediction model based on the VMD-CNN-BiGRU algorithm by considering six road spatial features such as road grades, one-way road attributes and intersection attributes. First, the VMD algorithm is employed to reduce the nonlinearity and nonsmoothness of the raw data by determining the optimal number of VMD decomposition modes. Then, the CNN-BiGRU algorithm is used to predict each modal component after decomposition, and the obtained prediction results are compared and analyzed with the prediction results of existing CNN-BiGRU, EMD-CNN-BiGRU and EEMD-CNN-BiGRU models. The results show that the VMD-CNN-BiGRU model significantly outperforms other models in terms of prediction performance and can accurately capture the trend of vehicle fuel consumption, thus effectively verifying the superiority and feasibility of the model. In addition, this study provides an in-depth analysis of the
Gao, YatingYan, LixinDeng, GuangyangChen, Siyuan
Temperature segregation significantly affects the compaction of asphalt mixtures and the durability of the asphalt pavement layer. Uneven cooling of the mixture during transportation is a key factor contributing to temperature segregation. This study uses finite element simulations to analyze the temporal and spatial temperature evolution during the transportation of asphalt mixtures. A temperature segregation evaluation index (TSIv) is proposed to assess the significance of various factors affecting segregation. Support vector regression (SVR), random forest regression (RFR), and extreme gradient boosting (XGBoost) models are employed to predict temperature changes during transportation and optimize the predictive models. The results indicate that the proportion of areas with a temperature difference of less than 10°C is consistently the highest, followed by areas with a temperature difference greater than 25°C, and then those with temperature differences in the ranges of 10-16°C and
Cheng, HaoMa, TaoTang, FanlongFan, Jianwei
Intelligent transportation has emerged as a critical paradigm in the transportation sector, underscoring the growing significance of digital information. The extent to which travelers comprehend transportation network information fundamentally influences the dynamics of traffic flow evolution. Traditional random user equilibrium models assume that travelers possess knowledge of segment flow information; however, they fail to account for route flow information. To date, research has yet to investigate how travelers’ decision-making behaviors are altered following the acquisition of route flow information. When endowed with such information, travelers frequently demonstrate behaviors influenced by the bandwagon effect, adjusting their routes to conform to the choices of the majority. This behavioral modification disrupts the existing equilibrium, resulting in a continued evolution of traffic flow until a new stable state is achieved. To examine the implications of transportation network
Zhou, BojianYu, YaofengLi, ShihaoLi, Kangjiao
This study tackles the issue of order delays in logistics using XGBoost for feature analysis and reinforcement learning for intelligent courier scheduling. Pickup order data from May 1 to October 31, 2023, in Chongqing is analyzed using spatio-temporal statistical methods. Key findings include that order placement peaks at 9:00 a.m., delays peak at 10:00 a.m., and the delay rate is 8.6%. A significant imbalance exists between the regional daily average of dispatchable couriers and order volumes.XGBoost is employed to predict order delays, revealing that pickup location is the most influential factor (27%), followed by courier pickup location (22%). These factors and their relationships are identified as key drivers of delays.To address these issues, a reinforcement learning-based courier scheduling optimization model is developed. The model defines courier location, current time, and pending orders as state variables and adopts an epsilon-greedy strategy for action selection
Wang, ManjunYu, Xinlian
Highway construction zones present substantial safety challenges due to their dynamic and unpredictable traffic conditions. With the rising number of highway projects, limited accident data during brief construction phases underscores the need for alternative safety evaluation methods, such as traffic conflict analysis. This study addresses vehicular safety issues within the Kunshan section of the Shanghai-Nanjing Expressway, focusing on conflict risk assessment through a spatio-temporal analysis of a construction zone. Using drone-captured video, vehicle trajectories were extracted to derive key operational indicators, including speed and acceleration, providing a spatio-temporal foundation for analyzing traffic flow and conflict dynamics. A novel **Comprehensive Collision Risk Index (CCRI)** was introduced, integrating Time-to-Distance-to-Collision (TDTC) and Enhanced Time-to-Collision (ETTC) metrics to enable a multidimensional assessment of conflict risk. The CCRI captures both
Zhang, YuwenGuo, XiuchengMa, Yuheng
The swift and relentless progression of drone technology has ushered in novel opportunities within the realm of urban logistics, especially for the potential of drones to modify last-mile delivery and improve customer fulfillment through mobile application integration, offering the potential for delivery systems that are both efficient and environmentally sustainable. This development is not just a technological leap but a transformative shift in how goods are moved within urban spaces, potentially reducing traffic congestion and emissions from traditional vehicles. Nevertheless, the safety issues of drone flights in cities are becoming increasingly serious, and the accountability related to drone accidents is not clear, raising concerns in society regarding the use and safety of drones. Therefore, to fully utilize the potential of drones in urban logistics, the incorporation of drones into the urban airspace environment necessitates the establishment of a strong regulatory and policy
Ma, JieYang, JunjieDiao, WeileDu, YilingChen, Weiqi
In a complex and ever-changing environment, achieving stable and precise SLAM (Simultaneous Localization and Mapping) presents a significant challenge. The existing SLAM algorithms often exhibit limitations in design that restrict their performance to specific scenarios; they are prone to failure under conditions of perceptual degradation. SLAM systems should maintain high robustness and accurate state estimation across various environments while minimizing the impact of noise, measurement errors, and external disturbances. This paper proposes a three-stage method for registering LiDAR point cloud. First, the multi-sensor factor graph is combined with historical pose and IMU pre-integration to provide a priori pose estimation; then a new method for extracting planar features is used to describe and filter the local features of the point cloud. Second, the normal distribution transform (NDT) algorithm is used as coarse registration. Third, the feature to feature registration is used for
Li, ZhichaoTong, PanpanShi, WeigangBi, Xin
The introduction of autonomous truck platoons is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, energy consumption, and infrastructure durability. Since the lateral positions of autonomous trucks traveling consecutively within a lane are fixed and similar (channelized traffic), such platooning operations are likely to accelerate damage accumulation within pavement structures. To further advance the application of truck platooning technology in various pavement environments, this study develops a flexible evaluation method to evaluate the impact of lateral arrangement within autonomous truck platoons on asphalt pavement performance. This method simplifies the impact of intermittent axle load applications along the driving direction within a platoon, supporting platoon controllers in directly evaluating pavement damage for different platoon configurations. Specifically, a truck platoon
Wenlu, YuYe, QinChen, DaoxieMin, YitongChen, Leilei
Technology for lane line semantic segmentation is crucial for ensuring the safe operation of intelligent cars. Intelligent cars can now comprehend the distribution and meaning of scenes in an image more precisely thanks to semantic segmentation, which calls for a certain degree of accuracy and real-time network performance. A lightweight module is selected, and two previous models are improved and fused to create the lane line detection model. Finally, experiments are conducted to confirm the model's efficacy. This paper proposes a lightweight replacement program with the aim of addressing the issue of large parameterization in the generative adversarial network (GAN) model and difficult training convergence. The overall network structure is selected from the Pix2Pix network in the conditional generative adversarial network, and the U-net network of the generator is cut and replaced by the Ghost Module, which consists of a modified downsampling module that enhances the global fusion
Yang, KunWang, Jian
The present study aims to assess the tensile properties of Caryota urens fibre reinforced polyester composites. Composites were fabricated with different fiber weight fractions starting from 5% to 35% with 5% increment. The mechanical testing of composite material was conducted using ASTM standards. The results indicated that the tensile, impact, and flexural properties of composite material were increased up to 25% fiber weight fraction; after that, they have been reduced due to some factors, like fiber distribution, which may not be uniform, and adhesion between fiber and matrix may be reduced. The optimal weight fraction of caryota urens fiber found from this study is 25%. The maximum tensile, impact, and flexural strength obtained for the composites were 36.22 MPa, 62.21 MPa, and 0.224 N/m, respectively. Water absorption characteristics show the increase of water intake behavior of composites due to their hydrophobic nature.
Santhanam, KRaja, K.Naveen, MSaranbala, MM, Naveenkumar
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also
Oliveira Neto, Raimundo ArraisSouza, Camila Gomes PeçanhaBrito, Luis Roberto BonfimGuimarães, Georges Louis Nogueira
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
Leighton, MichaelTuschkan, AlwinPlayfoot , Ben
Modern vehicles are increasingly integrating electronic control units (ECUs), enhancing their intelligence but also amplifying potential security threats. Vehicle network security testing is crucial for ensuring the safety of passengers and vehicles. ECUs communicate via the in-vehicle network, adhering to the Controller Area Network (CAN) bus protocol. Due to its exposed interfaces, lack of data encryption, and absence of identity authentication, the CAN network is susceptible to exploitation by attackers. Fuzz testing is a critical technique for uncovering vulnerabilities in CAN network. However, existing fuzz testing methods primarily generate message randomly, lacking learning from the data, which results in numerous ineffective test cases, affecting the efficiency of fuzz testing. To improve the effectiveness and specificity of testing, understanding of the CAN message format is essential. However, the communication matrix of CAN messages is proprietary to the Original Equipment
Shen, LinXiu, JiapengZhang, ZhuopengYang, Zhengqiu
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