Current Issue

• 2026, Vol. 17 No. 3
  Published on:30 June 2026 Previous issue   
  Review, Progress and Prospects

  Review of LiDAR-based SLAM methods

  LIU Kaiqi, KANG Fuxiang, LI Wei, GAO Bolin

  2026, 17(3):  279-295.  doi:10.3969/j.issn.1674-8484.2026.03.001

  Abstract ( 87 )   HTML ( 9)   PDF (4940KB) ( 36 )  

  As the core technology of robot navigation and environment perception, LiDAR-based simultaneous localization and mapping (SLAM) technology has been widely used in the fields of autonomous driving, drones, robots and so on. This paper summarizes the basic framework and key technologies of LiDAR-based SLAM, and focuses on the point cloud processing, front-end data registration, back-end optimization and closed-loop detection steps of LiDAR. It further reviews classical LiDAR-based SLAM methods and their corresponding improvements, discusses their technical innovations, and reveals the developmental trajectory and research trends of LiDAR-based SLAM, namely the transition from single-sensor-driven systems to multi-sensor fusion, from traditional geometric constraints to enhanced semantic understanding, and from local pose estimation to global consistency optimization. Meanwhile, an indoor 3D mapping experiment was conducted using a Livox HAP LiDAR to validate the effective support of high-precision maps constructed by SLAM for environmental perception tasks. Experimental results show that point cloud maps obtained through LiDAR-based SLAM can not only reconstruct the spatial structure of a scene with relatively high accuracy, but also provide a reliable data foundation for downstream tasks such as semantic segmentation, thereby demonstrating the significant application value of LiDAR-based SLAM in perception systems. Finally, the paper discusses the development potential of LiDAR-based SLAM in directions such as deep learning, neural radiance fields, and multi-sensor fusion, and points out that challenges remain in dynamic environment adaptation, the trade-off between real-time performance and accuracy, and large-scale engineering deployment.

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  Materials underpin BIW safety: SMARTeX innovation practices of Baosteel automotive sheet

  BAO Ping, JIA Fanghui, HAN Fei

  2026, 17(3):  296-313.  doi:10.3969/j.issn.1674-8484.2026.03.002

  Abstract ( 102 )   HTML ( 10)   PDF (6221KB) ( 41 )  

  With the global automotive industry transitioning toward electrification and intelligence, and with the continuous advancement of vehicle safety assessment systems, automotive body safety technologies are evolving from traditional passive safety concepts to a comprehensive and systematic safety framework integrating active and passive safety, intelligence and information security, and low-carbon safety. This paper reviews the development of vehicle crash safety regulations and assessment programs both domestically and internationally. From the perspective of body safety, it summarizes the evolution of automotive materials from conventional steels to advanced high-strength steels (AHSS). Taking Baosteel automotive steel products as the example, the technical characteristics and body applications of all three-generations AHSS is introduced. Furthermore, from the perspective of advanced manufacturing technologies such as forming and joining, the critical role of synergistic innovation between material properties and manufacturing processes in enhancing vehicle safety performance is discussed. On this basis, Baosteel's “SMARTeX” safety innovation practice is introduced, which establishes a comprehensive vehicle body safety solution featuring a three-layer, seven-dimensional framework encompassing body-in-white (BIW), assemblies, components, joining, corrosion protection, digital intelligence, and low-carbon safety. Finally, the paper provides perspectives and discussions on the future development of vehicle body safety technologies, emphasizing that the realization of a safe vehicle body relies on the combined intelligence of structural design and material application. Material innovation plays a vital supporting role in body safety and overall vehicle safety development, as well as in the coordinated advancement of high safety, lightweighting, and low-carbonization within the automotive industry.

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  Automotive Safety

  Machine learning-based method for predicting the performance of automotive side curtain airbags

  YE Ye, LIU Eryong, CHEN Yixiong

  2026, 17(3):  314-321.  doi:10.3969/j.issn.1674-8484.2026.03.003

  Abstract ( 85 )   HTML ( 5)   PDF (1368KB) ( 34 )  

  To address excessive iterations and long computation time in the performance simulation of automotive side curtain airbags during vehicle development, a machine learning-based prediction approach was proposed to model two key performance indicators: inflation volume and deployment shape. Leveraging a large repository of enterprise simulation data, a domain knowledge-driven image feature extraction method was proposed, and the XGBoost algorithm was selected for inflation volume prediction through comparative evaluation. Meanwhile, a dual-head neural network based on ResUNet was adopted for deployment shape prediction. The results show that 98.2% of the test samples for the inflation volume prediction model have an error of less than 5%, and 93.3% of the samples for the deployment shape prediction model achieve an intersection-over-union (IoU) greater than 0.8, both meeting engineering accuracy requirements. Compared with traditional simulation methods, the proposed AI models reduce prediction time from two days to the order of seconds, significantly improving iteration efficiency. An effective and feasible technical pathway is provided for automotive safety component development, offering substantial practical value for enterprise digital transformation.

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  Analysis of injury risk disparities between Chinese and Western occupants in small aircraft crash scenarios

  SHI Xiaopeng, CHEN Hao, GUO Kai, LIU Tianfu, XIE Jiang

  2026, 17(3):  322-331.  doi:10.3969/j.issn.1674-8484.2026.03.004

  Abstract ( 93 )   HTML ( 2)   PDF (3199KB) ( 16 )  

  In order to study the difference of injury risk caused by different physical signs between Chinese and Western occupants in aircraft crash scene, the Chinese and Western adult male finite element models AC-HUMS and THUMS were used to simulate the small aircraft crash scene respectively, and the difference of injury risk of head, neck and waist between Chinese and Western male occupants under two conditions of vertical 19 g crash and horizontal 26 g crash was analyzed. The results show that the head injury probability of Chinese occupants is 66.6%~84.9% of that of Western occupants under the horizontal 26 g simulated crash condition. Under the vertical 19 g simulated crash condition, the waist injury probability of Chinese occupants was 71.43% of that of Western occupants. Chinese occupants showed more frequent stress concentration at the junction of cervical vertebrae and intervertebral discs, and the stress of cervical cortical bone was significantly higher than that of Western occupants under the simulated crash condition of 26 g. It can be seen that the difference in signs has a significant impact on the transmission path of the impact energy of small aircraft crashes and on the prediction results of the distribution patterns of human head, neck and lumbar spine injuries. The existing airworthiness standards and occupant restraint systems formulated for Westerners ' signs are difficult to adapt to the protection needs of Chinese small aircraft occupants.

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  Research on truck gear selection and speed characteristics on extended longitudinal gradients on mountainous expressways

  WU Kaixiang, WANG Rui, DUAN Weijian, XU Jin, LIU Ying

  2026, 17(3):  332-341.  doi:10.3969/j.issn.1674-8484.2026.03.005

  Abstract ( 54 )   HTML ( 2)   PDF (2403KB) ( 15 )  

  A questionnaire survey was conducted among nearly one hundred truck drivers with certain driving experience, collecting gear selection decisions and speed choices of trucks to investigate the driving habits and the driving characteristics of truck drivers on long and steep longitudinal gradients on mountainous expressways to improve safety levels on such roads. The results show that the trucks with more axles use higher gears on long uphill sections when fully loaded; the truck drivers use higher gears as the number of axles increases on long downhill sections. The truck drivers use higher gears and speeds on downhill than on uphill. When empty, truck drivers use higher gears and speeds than when fully loaded. The drivers use higher gears and speeds on gentler gradients than on steeper gradients. The speeds of three-axle and four-axle trucks are higher, while those of five-axle and six-axle trucks are lowest. Moreover, the truck’s speed increases when descending a slope compared to ascending it. The findings of this study provide a theoretical basis for optimizing safety management protocols and operational strategies for extended longitudinal gradients on mountainous expressways.

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  Automotive Energy Efficiency and Environment Protection

  High-performance vanadium-nickel thin-film electrocatalysts by using magnetron co-sputtering toward the hydrogen evolution reaction

  ZHANG Han, CHEN Zuochao, FANG Jiongchong, YANG Fuyuan, ZENG Guosong

  2026, 17(3):  342-350.  doi:10.3969/j.issn.1674-8484.2026.03.006

  Abstract ( 77 )   HTML ( 2)   PDF (4055KB) ( 12 )  

  A highly active non-precious metal vanadium-nickel (VNi) thin-film electrocatalyst was developed for the hydrogen evolution reaction (HER) with scalable preparation to meet the demand for the low-cost, high-performance non-precious metal catalysts for large-scale water electrolysis for hydrogen production. NiV thin film catalysts of different atomic ratios were prepared by using sing magnetron co-sputtering technology, on self-supported carbon paper electrodes with regulating the doping level when the Ni target directional current power was set to 120 W. The results show that the NiV25 sample catalyst (with the V target radiation frequency power of 25 W) exhibits an overpotential as low as 42.3 mV for the hydrogen evolution reaction in alkaline media, corresponding to a current density of 10 mA/cm² with having a Tafel slope of 125.17 mV with outstanding stability; notably, the NiV50 sample catalyst (with the V target radiation frequency power of 50 W) can operate continuously for 100 h at the current density of 10 mA/cm².

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  Knock prediction of high-compression-ratio spark-ignition engine based on neural networks

  ZHANG Weixuan, MA Zhiyin, FU Jinhong, LI Xuesong, XU Min

  2026, 17(3):  351-358.  doi:10.3969/j.issn.1674-8484.2026.03.007

  Abstract ( 42 )   HTML ( 4)   PDF (1981KB) ( 17 )  

  A neural-network-based intelligent knock prediction method was developed based on neural-network, by using a calibrated 1-dimension simulation model and engine test bench data, to predict knock in a spark-ignition (SI) engine with a compression ratio of 14. Two neural network architectures with multilayer perception were constructed and compared, including an end-to-end model and a two-stage pipeline model. The end-to-end model directly used control parameters for knock prediction. The pipeline model followed an explicit physical reasoning chain of “control parameters, combustion state, knock prediction”. Some validation tests were performed on an engine bench. The results show that the pipeline model achieves a prediction accuracy of 98.6%, which is superior to the end-to-end model's accuracy of 96.1%. The model achieves 100% prediction accuracy for 20 actual control parameter sets. Therefore, this model can predict knock events in real engines and will provide a solution for real-time engine control and performance optimization.

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  Spatiotemporal path planning for energy saving of logistics delivery electric vehicles under load-speed coupling

  WANG Jianqiang, CAO Jianzhong, TONG Ting, WANG Feng

  2026, 17(3):  359-368.  doi:10.3969/j.issn.1674-8484.2026.03.008

  Abstract ( 53 )   HTML ( 3)   PDF (2050KB) ( 13 )  

  A load (mass) -speed-coupling driven-energy-efficient spatiotemporal path-planning method was proposed to optimize the energy consumption of electric vehicles in logistics distribution. A load-space-time state network was constructed to characterize vehicle distribution paths in the spatiotemporal domain. The energy consumption of each arc was formulated by integrating a comprehensive power-based energy consumption model (CPEM). Functional relationship between energy consumption and speed was derived to determine the optimal economic speed under varying load conditions. A two-stage decomposed path search strategy was developed combining the Ant Colony Optimization and the Dijkstra’s algorithm to address candidate path exploration in complex delivery stages and precise energy-optimal routing in the return stage. Simulation experiments were conducted on a 10-node network and the Sioux Falls 24-node network. The results show that the proposed method reduces energy consumption by approximately 7% compared with the alternative paths under equal-distance conditions. The overall energy consumption is reduced by 13%~16% compared with the conventional shortest-path strategy.

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  Intelligent Driving and Intelligent Transportation

  Collaborative control and safety analysis of connected and automated vehicles based on hybrid car-following strategy

  ZHENG Yuan, YU Wenhao, LI Shen, LIU Yang, CHEN Tianyi, LI Meng, RAN Bin

  2026, 17(3):  369-379.  doi:10.3969/j.issn.1674-8484.2026.03.009

  Abstract ( 78 )   HTML ( 3)   PDF (2252KB) ( 20 )  

  A novel cooperative control method for CAVs was proposed based on a hybrid car-following strategy to improve the traffic safety of the connected and automated vehicle (CAV) platoons using the constant spacing (CS) strategy in terms of the rear-end collisions. Specifically, the leader adopted the constant time gap (CTG) strategy while the followers used the CS strategy, the car-following control models were formulated based on the linear feedback and feedforward controllers, and the sufficient conditions of the string stability were derived. Numerical experiments were conducted and the results show that the proposed hybrid strategy reduces rear-end collision risks by more than 93% for a single platoon and 97% for two platoons under a time-to-collision threshold (TTCT) of 3.0 s compared with the pure CS strategy. All rear-end collision risks can be eliminated for both a CAV platoon and two CAV platoons when the TTCT is set at 2.0 s. The implementation of the hybrid car-following strategy for platooning of CAVs improves travel efficiency by 39% compared to the pure CTG strategy. Therefore, the proposed strategy provides a theoretical support for the car-following controls and safety improvements of the CAV platoons.

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  Three-level collaborative optimization control of signal-route-speed for vehicle-road cooperation

  CHEN Shi, ZHONG Shaopeng, WU Jianjun, JIANG Qihan, XU Hang, QIU Tianrun

  2026, 17(3):  380-387.  doi:10.3969/j.issn.1674-8484.2026.03.010

  Abstract ( 52 )   HTML ( 2)   PDF (1176KB) ( 12 )  

  A signal-path-speed three-level collaborative optimization control-method was proposed to develop an intelligent transportation system for multi-intersection mixed traffic flow environments. At the upper level, the model predictive control (MPC) was adopted to solve the signal timing optimization problem in a rolling horizon manner, and the trust region bayesian optimization (TuRBO) was introduced to adaptively shrink the search region for efficiently approaching the global optimum. At the middle level, the K-Shortest Path (KSP) algorithm was employed to generate candidate path sets; and the method of successive averages was combined to iteratively update path flow assignment for dynamic route guidance. At the lower level, a speed planning model was constructed based on the MPC; and the TuRBO was utilized to optimize the speed trajectories of connected vehicles online, achieving microscopic speed collaborative control. The SUMO (simulation of urban mobility) was used to simulate. The results show that compared to the baseline scenario without collaborative optimization, the proposed method significantly reduces the total vehicle travel time under various connected vehicle penetration rates, with the best optimization rate reaching 67.6%, outperforming single-level or two-level control models. Therefore, this method provides a solution for collaborative control in intelligent transportation systems.

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  Research on the steady-state of driver takeover in scenarios involving livestock obstructing grassland highways

  WANG Haixiao, ZHANG Hang, GAO Mingxing, JI Tianxing, WANG Qingju

  2026, 17(3):  388-396.  doi:10.3969/j.issn.1674-8484.2026.03.011

  Abstract ( 56 )   HTML ( 1)   PDF (3291KB) ( 18 )  

  A livestock occupation scenario was constructed using driving simulation technology to investigate the impact of different takeover alert schemes on the takeover steady-state performance in specific dynamic scenarios of grassland highways. 4 takeover alert schemes were established: visual alert (VA), visual combined with tactile alert (VTA), visual combined with auditory alert (VAA), visual combined with both auditory and tactile alert (VATA). The entire driving takeover process was divided into initialy takeover phase and later takeover phase based on temporal dimensions, using survival probability model and data envelopment analysis (DEA), in conjunction with fundamental indicators to assess the effectiveness of takeover steady-state transitions. The results indicate that VTA and VATA demonstrates superior performance in terms of survival time, the takeover response is most rapid in the VTA, with a takeover response time of 0.52 s; in the initial takeover phase, integrating auditory alerts can enhance the driver's cognitive-homeostasis transition by 7.2%; in the later takeover phase, the synergistic interaction between tactile and auditory significantly enhances the steady-state transformation benefits, the integration of visual with other modalities contributes to improved steady-state performance, specifically, the steady-state transformation benefits of the VATA is 13.9% higher than alternative schemes.

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  Path tracking and roll stability control for distributed drive autonomous vehicles based on LTV-MPC

  CAO Shouqi, JIANG Jiasheng, ZHOU Guofeng, CHEN Jianwei

  2026, 17(3):  397-408.  doi:10.3969/j.issn.1674-8484.2026.03.012

  Abstract ( 43 )   HTML ( 1)   PDF (2507KB) ( 19 )  

  A hierarchical cooperative path-tracking control strategy considering roll stability was proposed to address the deterioration of roll stability caused by lateral load transfer in distributed-drive autonomous vehicles during high-speed lane-change and steering maneuvers. Firstly, a four-degree-of-freedom vehicle model was established, and variable tire cornering stiffness was introduced to improve the model accuracy under high-speed lateral load transfer conditions. On this basis, a hierarchical cooperative control architecture was designed. In the upper layer, a linear time-varying model predictive control (LTV-MPC) method was developed to coordinate path-tracking performance and vehicle stability, where the lateral load transfer ratio (LTR) was incorporated as an explicit optimization constraint. In the lower layer, the driving torque of each wheel was optimally allocated to further improve tire utilization and vehicle stability. Finally, a CarSim-MATLAB/Simulink co-simulation platform was built to evaluate the proposed strategy under high-speed double lane change (DLC) and Fishhook maneuvers. The results show that, compared with the conventional MPC method, at a speed of 100 km/h, the proposed strategy reduces the peak LTR and peak roll angle by 6.58% and 11.92%, respectively, in the DLC maneuver; while in the Fishhook maneuver, reduces by 10.64% and 14.89%, respectively demonstrating that the proposed method can effectively suppress roll tendency and improve vehicle stability under extreme driving conditions.

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  Optimized passage strategies and game-theoretic analysis for unbalanced intersections in mixed CAV and CHV traffic

  GUO Shitong, WU Chengcheng, ZHENG Dingwei, HUANG Xingyu

  2026, 17(3):  409-419.  doi:10.3969/j.issn.1674-8484.2026.03.013

  Abstract ( 50 )   HTML ( 2)   PDF (2266KB) ( 14 )  

  An intersection passage optimization strategy based on multi-agent negotiation was proposed to optimize urban intersections under unbalanced traffic flow in a mixed environment of connected and automated vehicles (CAVs) and conventional human-driven vehicles (CHVs). Three strategies were developed: when no pedestrians or non-motorized vehicles were crossing, CAVs were allowed to perform lane-borrowing left turns across the median, while approach vehicles turned left directly; when pedestrians or non-motorized vehicles crossed normally, the left-turn waiting area and the CAV lane-borrowing left-turn area were extended; when a negotiated agreement on delayed crossing with charging compensation was reached, wireless charging was provided to improve the acceptability of waiting, CAVs performed lane-borrowing left turns across the median while approach vehicles turned left directly, and the subsequent release scheme was dynamically adjusted within a single cycle to improve responsiveness to traffic-flow variation. The strategy was built on the outcome of pedestrian-vehicle crossing negotiation and a waiting-compensation mechanism, in which the wireless charging service offered during delayed crossing reduced the waiting cost of pedestrians and non-motorized vehicles. With pedestrians/non-motorized vehicles and motor vehicles taken as the game players, bilateral evolutionary game models were established, and a three-dimensional payoff of “time cost-safety risk-energy compensation” was introduced. The results show that, under mixed and unbalanced traffic conditions, the combination of signal-compliant crossing by pedestrians/non-motorized vehicles, extended left-turn waiting for CHVs, and CAV lane-borrowing left turns into the extended area constitutes an evolutionarily stable strategy, which significantly reduces delay and disorder without altering the existing channelization or signal-control framework.

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