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30 March 2023, Volume 42 Issue 3 Previous Issue   
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Transportation+Big Data & Artificial Intelligence
Transportation Infrastructure Engineering
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Transportation+Big Data & Artificial Intelligence

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Sensitivity Analysis of Parameters Affecting Main Cable State of Guojiatuo Yangtze River Bridge XIONG Guikai1,2, WANG Hui3, CHEN Hanxin2, HE Xudong4 2023, 42(3): 1-6.  DOI: 10.3969/j.issn.1674-0696.2023.03.01 Abstract ( )   PDF (512KB) ( )   The main cable state is an important control index in the construction process of suspension bridge, and it is the main factor influencing the accuracy of bridge alignment. Taking a highway-rail suspension bridge under construction as an example, five parameters during erection were selected, including main cable temperature, tower pre-lift value, elastic modulus of steel wire, diameter of steel wire, and weight error of steel truss beam. The influence of the above parameters on the main cable state was analyzed. The research results show that the main cable temperature, tower pre-lift value, elastic modulus of steel wire and weight error of steel truss beam during erection have a great impact on the empty cable alignment, which are highly sensitive factors. The elastic modulus of steel wire has a great influence on the unstressed length of the main cable, which is a highly sensitive factor. The diameter of steel wire has a certain impact on the empty cable alignment, which is a generally sensitive factor. The weight error of steel truss beam has a certain impact on the internal force of completed main cable bridge, which is a generally sensitive factor. In order to improve the erection accuracy of the main cable of suspension bridge, it is necessary to accurately obtain the relevant influencing parameters and feed them back to the monitoring work. References | Related Articles | Metrics

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Continuous Automatic Identification of Modal Parameters and Analysis on Frequency Variability Based on FDD Method WANG Xiaoguang1,2, MA Ming2, GAO Linli2, DANG Litao2 2023, 42(3): 7-16.  DOI: 10.3969/j.issn.1674-0696.2023.03.02 Abstract ( )   PDF (1665KB) ( )   Modal parameters are important indexes to analyze the change of bridge operation status, which can provide data basis for bridge status evaluation. A continuous automatic modal parameter identification method based on frequency domain decomposition (FDD) was proposed, and the relationship between modal parameters and environment was analyzed. The forward and backward linear mean filtering method was used to filter the singular value curve to eliminate the false burr peak caused by noise interference. The Dvp index was proposed, and the peak value of singular value corresponding to the real modal parameters was obtained by combining with the peak and trough detection algorithm. The K-means clustering method was introduced to realize the automatic selection of the true peak value of the singular value curve. According to the actual health monitoring data storage format, a framework of continuous automatic identification of modal parameters was designed, and an automatic identification algorithm incorporating modal parameters was proposed to realize continuous and automatic identification of modal parameters. The proposed method was applied to the measured data of cable-stayed bridges, and the modal parameters for one month were obtained through continuous automatic identification. The impact of the environment on the frequency of the structure was analyzed. The research results show that the proposed automatic modal parameter identification method based on FDD can realize the automatic identification of modal parameters. The proposed data automatic analysis framework combined with automatic identification algorithm can realize continuous and automatic identification of modal parameters, and solve the continuous and automatic analysis of bridge health monitoring data. The bridge structure frequency is greatly affected by ambient temperature, and the randomness of structure frequency caused by random environmental factors cannot be ignored. References | Related Articles | Metrics

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Seismic Performance Evaluation of a Cable-Stayed Bridge along Transverse Direction Based on Fragility Curves XU Lueqin1,2, HE Hongtao1, ZHANG Chao1, XU Yihong1 2023, 42(3): 17-25.  DOI: 10.3969/j.issn.1674-0696.2023.03.03 Abstract ( )   PDF (1369KB) ( )   Aiming at the reasonable evaluation of lateral seismic performance of cable-stayed bridges under seismic fortification at both E1 and E2 levels, the incremental dynamic analysis method (IDA) was adopted to establish the probabilistic seismic fragility curves of the background bridge at the component and structural system levels. The exceedance probabilities of the three damage states, i.e. slight damage, medium damage and severe damage, of the background bridge under the dual-level design earthquakes were studied to evaluate the lateral seismic performance of cable-stayed bridges. The research results show that at the component level, the exceedance probabilities of the three types of damage states of the pylons, cables, transition piers and auxiliary piers under the dual-level seismic designs are all less than 40%, and most of them are lower than 30%. While, the maximum exceedance probability of moderate damage to spherical steel bearings exceeds 50%, which is a weak link in the transverse seismic resistance of the entire bridge. At the system level, whether it is the first order limit method or the second order limit method, the damage exceedance probability of the structure is significantly higher than that of each component. The probability of moderate damage under two-level earthquake fortifications is the highest (88.77% and 85.22% respectively for the first and second order limit methods under the E2 earthquake), while the probability of serious damage is less than 40%. References | Related Articles | Metrics

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Numerical Study on Flow Field Characteristics of Anti-collision Pontoon for Bridge Pier Based on Overset Grid JI Nan1, YANG Guang1, SHU Linzhao1, QIAN Zhipeng1, WAN Decheng2 2023, 42(3): 26-35.  DOI: 10.3969/j.issn.1674-0696.2023.03.04 Abstract ( )   PDF (4279KB) ( )   In order to reveal the hydrodynamic performance and flow field characteristics of pier equipped with anti-collision pontoon, taking the typical circular self-floating pontoon pier system as an example, the Reynolds stress (RSM) turbulence model was adopted on the basis of the overset grid method. Using the VOF method to capture the free surface and taking into account the buoyancy tank heave displacement, a three-dimensional numerical calculation model was established. Firstly, the rationality of the numerical simulation method and the accuracy of the results were verified by comparing with the experimental data. Then the sinkage and heave motion of the floating tank was realized by using the overset grid technology. The effects of the changes of flow velocity and water depth on the sinkage and heave, dynamic response and flow field characteristics of the anti-collision floating pontoon were studied. The research results show that: the flow velocity mainly affects the heave displacement of the anti-collision pontoon, while the water depth mainly affects the heave process of the anti-collision pontoon. The force coefficients of the anti-collision pontoon in three directions basically decrease with the increase of water depth, but at a low flow velocity, the downward trend of the force coefficients with the increase of water depth is relatively gentle, and the longitudinal force coefficients first increase slightly and then decrease with the increase of water depth. The heave of the anti-collision pontoon is related to the vertical force. The variation period of the vertical force of the anti-collision pontoon increases with the increase of water depth at a lower flow velocity. At a higher flow velocity, the anti-collision pontoon produces strong heave and the periodic variation law disappears completely. References | Related Articles | Metrics

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Threat Level Evaluation of Technical Interface Suspension of Railway Bridge and Tunnel in Hard and Dangerous Mountainous Area BAO Xueying1, WEI Dailei1, BAN Xinlin2,3, XV Jianchao2,3 2023, 42(3): 36-43.  DOI: 10.3969/j.issn.1674-0696.2023.03.05 Abstract ( )   PDF (807KB) ( )   In hard and dangerous mountainous areas, the environmental conditions are extremely harsh and geological disasters occur frequently. The proportion of bridge and tunnel engineering along the railway is large. In order to improve the technical interface management level of bridge and tunnel engineering, a Bayesian feedback correction cloud model was constructed to evaluate the suspension threat level of the technical interfaces. Firstly, based on the technical interfaces of railway bridge-tunnel engineering and considering the impact of the common problems of the interface between different parties and a series of technical problems faced by the railway construction in difficult mountainous areas on the interface suspension, the evaluation index system of the suspension threat level of the technical interfaces was constructed from five aspects, including the owner’s factor, the survey and design party’s factor, the contractor’s factor, other factors related to the project and external factors. And the IFAHP method was used to assign weights. Then, an evaluation model of the suspension threat level of the technical interface of the railway bridge and tunnel engineering in the difficult mountainous area was constructed by using the Bayesian feedback correction principle. Finally, the bridge-tunnel engineering interface of Gongduoding tunnel and the double-track bridge of Benzhong Station was selected as the evaluation object, and its suspension threat level was evaluated and visually analyzed by using MATLAB. Through engineering examples, it is shown that the comprehensive level of suspension threat to the proposed technical interface is serious, with the highest degree of suspension threat from survey and design factors to the bridge tunnel technical interface. References | Related Articles | Metrics

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Deformation Law and Supporting Countermeasures of Huajiaoqing Soft Rock Tunnel BAO Xiankai1, SHI Muhan1, LEI Yanhong2, ZHANG Wu1, WANG Shurui1 2023, 42(3): 44-51.  DOI: 10.3969/j.issn.1674-0696.2023.03.06 Abstract ( )   PDF (1937KB) ( )   During the construction of soft rock tunnel, there are often extrusion deformation of surrounding rock, deformation limit of lining, fracture and instability of support structure and so on. Taking Huajiaoqing soft rock tunnel as the background, the numerical analysis software was used to simulate the construction process of double step reserved core soil method for circular excavation of tunnel, analyze the deformation mechanism and improve the support measures. Moreover, the new support countermeasures of “strengthened support at key parts + high-strength locking anchor bolt support + overall reinforcement of section anchor bolt” was adopted. The support effect after improvement was simulated and analyzed, which would be adopted after meeting the requirements, and the on-site deformation monitoring was also carried out. The research results show that the deformation of Huajiaoqing tunnel is the overall subsidence deformation of the arch caused by the shear failure of the surrounding rock of two sides and arch foot under the influence of high stress. The simulated deformation results exceed the early warning value and the support effect is poor. Targeted optimization was carried out by increasing the length of anchor rods and adding foot locking anchor rods. The deformation of arch crown, arch bottom and horizontal direction after improvement is reduced by 20.3%, 15.2% and 20% respectively compared with that before optimization, which all doesn’t exceed the early warning value, and the optimization effect is remarkable. The field monitoring measurement shows that after improving the support measures, the maximum deformation of the arch crown, arch shoulder, and arch waist is 17 cm, 3.67 cm and 3.02 cm respectively, and the optimization effect meets expectations. References | Related Articles | Metrics

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Latin Hypercube Sampling for Relevant Ramdom Variables and Probabilistic Analysis of Tunnel Face Stability ZHANG Congxu1, LAN Yuansheng2, LI Bin2 2023, 42(3): 52-58.  DOI: 10.3969/j.issn.1674-0696.2023.03.07 Abstract ( )   PDF (1206KB) ( )   The Latin hypercube sampling principles of four different types of relevant random variables were summarized and Latin hypercube sampling of relevant variables in various situations was realized through Python language. FLAC3D was utilized to perform deterministic analysis of tunnel face stability and calculate the failure probability based on the obtained samples generated by Latin hypercube sampling. The results show that Latin hypercube sampling can greatly reduce the number of samples required for uncertainty analysis while meeting the required computational accuracy and improving computational efficiency. References | Related Articles | Metrics

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Factors Affecting the Storage Stability of STAC Asphalt GOU Yongtao1, XU Lei2, KONG Lingyun3 2023, 42(3): 59-64.  DOI: 10.3969/j.issn.1674-0696.2023.03.08 Abstract ( )   PDF (568KB) ( )   In order to study the factors affecting the storage stability of cationic emulsified asphalt and establish the quantitative relationship model between each factor and stability, octadecy trimethy ammonium chloride (STAC) was selected as cationic emulsifier to prepare cationic emulsified asphalt. The storage stability was used as the index to analyze the influence of different factors on the performance of emulsified asphalt. The test results show that the cationic emulsified asphalt has good storage stability when the amount of emulsifier is 3.2%, the asphalt temperature is 125 ℃, the oil-water ratio is 5∶5, the soap temperature is 55 ℃, and the pH value of soap is 3. The influence degree of each factor on the system was obtained by grey relation analysis. It was found that asphalt temperature, oil-water ratio and soap temperature had a great influence on the storage stability of emulsified asphalt under the optimal condition of emulsifier dosage. The relationship model of storage stability factors and stability of STAC emulsified asphalt was established based on BP neural network. The model has high prediction accuracy, which can provide guidance for the determination of production conditions of this kind of emulsified asphalt. References | Related Articles | Metrics

Transportation Infrastructure Engineering

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Compatibility and Crack Resistance of PVA Fiber Asphalt Based on Warm Mixing Technology ZHAO Yang1，2, LIANG Naixing1, JIA Xiaodong2 2023, 42(3): 65-70.  DOI: 10.3969/j.issn.1674-0696.2023.03.09 Abstract ( )   PDF (791KB) ( )   Aiming at the defects of crimping, shortening, dehydration and etherification of polyvinyl alcohol (PVA) fiber in hot mixing (160~170 ℃), the heat resistance performance of PVA fiber at 130~170 ℃ and the compatibility of PVA fiber-asphalt was studied. Based on the interface theory of composite materials, the dispersed powder was optimized by calculating the contact angle and surface energy of PVA fiber, and the optimal ratio of PVA fiber and best dispersed powder was put forward. The dispersion uniformity was evaluated by mass variation coefficient method. The research shows that the PVA fiber processed by warm mix asphalt technology has compatibility with asphalt, and the anti-cracking performance of the asphalt mixture is improved by 54% compared with the hot mix asphalt mixture. PVA fiber plays the role of stabilization, adsorption and reinforcement in the asphalt mixture, which fills the blank of PVA fiber used in the asphalt mixture. References | Related Articles | Metrics

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Combined Prediction Model of Asphalt Pavement Performance Based on Neural Network Algorithm CAO Xuejuan1, LU Zhilin2, WU Bowen2, HUANG Ying2, WANG Min3 2023, 42(3): 71-77.  DOI: 10.3969/j.issn.1674-0696.2023.03.10 Abstract ( )   PDF (721KB) ( )   In order to accurately predict the change law of asphalt pavement performance, a combined prediction model PCA-GA-RBF of asphalt pavement performance based on radial basis function neural network algorithm was proposed. In view of the slow convergence speed of the neural network and easiness falling into local optimization of model parameters, the principal component analysis algorithm was used to reduce the dimension of the factors affecting the pavement performance, and the genetic algorithm was used to optimize the structure of the neural network. The combined prediction model was validated through predictive analysis of road driving quality. The research shows that the goodness of fit R2 of PCA-GA-RBF is 0.820, and the root mean square error S is 2.645, which is 11.4% lower than that of the single RBF neural network prediction model, and the average prediction accuracy of PCA-GA-RBF is 84.13%. The combined prediction model has fast calculation speed, high prediction accuracy and good prediction effect. References | Related Articles | Metrics

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Characteristics of Cushion Ship Berthing at Dock Based on ANSYS-AQWA YUAN Peiyin1, LI Yufeng1, ZHAO Yu2, ZHANG Zhe1 2023, 42(3): 78-83.  DOI: 10.3969/j.issn.1674-0696.2023.03.11 Abstract ( )   PDF (789KB) ( )   Ships are gradually developing in the direction of standardization and large scale. It is an urgent problem to be solved in the engineering field to effectively reduce or avoid the collision between large ships and wharves. Based on the three-dimensional potential flow theory and time-domain analysis method, and in combination with the characteristics of turbulent flow and large flow variation in mountainous rivers, the mooring motion response characteristics of ships under different mooring modes were studied by adopting the numerical analysis method and ANASYS-AQWA simulation software. The research results show that the wave direction angles of 0° and 180° have the most obvious effect on the amplitude response operator of surge, and the wave direction angle of 90° has a larger response to sway, heave and roll, and a smaller impact on surge, pitch and yaw. The 2-7-2 mooring mode has a better restriction on the lateral movement of ships, while the 4-4-4 mooring mode has a better restriction on the longitudinal movement of ships. References | Related Articles | Metrics

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Short-Term Prediction Method of Parking Space Based on WOA-XGBoost SONG Rui, CHENG Zilong, ZHAO Rixin 2023, 42(3): 84-89.  DOI: 10.3969/j.issn.1674-0696.2023.03.12 Abstract ( )   PDF (608KB) ( )   In order to improve the accuracy of short-term prediction of parking space, based on the data characteristics of free parking space in parking lots, a combined prediction model combined whale optimization algorithm (WOA) and extreme gradient boosting algorithm (XGBoost) was proposed. Firstly, the randomness of the data of free parking space was analyzed, and the singular spectrum analysis (SSA) was used to deconstruct and reconstruct the original data, so as to extract the main components of the original data and eliminate the noise. Secondly, the whale optimization algorithm was used to optimize the main parameters of XGBoost prediction model and find the global optimal parameters. Finally, the accuracy of the proposed prediction model was verified by an example. The test results show that the WOA-XGBoost prediction model that optimizes parameters has higher prediction accuracy and stability. References | Related Articles | Metrics

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Subway Short-Term Passenger Flow Forecast Based on Improved Logistic-SSA-BP Neural Network HU Mingwei1,2,3, HE Guoqing1, WU Wenlin1, ZHAO Qian1,2,3 2023, 42(3): 90-97.  DOI: 10.3969/j.issn.1674-0696.2023.03.13 Abstract ( )   PDF (769KB) ( )   he change rules of passenger flow of subway have certain periodic and tidal characteristics. Predicting subway passenger flow can help improve the operational efficiency of urban rail systems and achieve intelligent operation of rail transit. To improve the accuracy of short-term subway passenger flow prediction results, a short-term prediction model of subway passenger flow based on Logistic-SSA optimization BP neural network was proposed. The proposed model initialized the sparrow search algorithm population through a Logistic chaotic map, and then optimized the BP neural network by using the improved sparrow algorithm to improve the global search ability and convergence efficiency of the BP neural network. Taking the inbound and outbound AFC card data of Shenzhen Metro Xixiang Station as an example, a passenger flow prediction experiment was conducted by using the constructed prediction model, and the accuracy of the model prediction before and after the improvement was evaluated through three accuracy evaluation indicators such as MAE, RMSE and MAPE. The experimental results show that MAPE of inbound and outbound are 14.96% and 13.73% respectively for the improved Logistic-SSA-BP prediction model. Compared with the traditional BP prediction model, the passenger flow prediction results of the proposed model have higher accuracy. References | Related Articles | Metrics

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Reliability Design of Weaving Segment Length of Urban Expressway Interchange ZHANG Hang, DUAN Hezhu, CHU Zeyu 2023, 42(3): 98-104.  DOI: 10.3969/j.issn.1674-0696.2023.03.14 Abstract ( )   PDF (490KB) ( )   The reasonable setting of the weaving segment length of the interchange section in urban expressway will play a key role in improving the service level, traffic capacity and traffic safety of the whole urban expressway system. Therefore, it is necessary to calculate the weaving segment length of the interchange scientifically and reasonably. Based on the relevant methods of weaving section in Highway Capacity Manual, the calculation model of weaving section length was established. The reliability function of the minimum interweaving area length was established based on the proposed model and the reliability theory. And the randomness and distribution law of random variables such as “average speed of weaving vehicles interval” and “average free flow speed of basic section of weaving section” were analyzed. Monte Carlo method was used to discuss the safety and reliability of the design value of the minimum weaving section length in the current code, and the failure probability and reliability indicators were used for evaluation. With reference to the reliability requirements of the corresponding safety levels of urban expressways in the Uniform Standards for Structural Reliability Design of Highway Engineering, the lengths of weaving section at different design speeds were calculated, and the calculation results were verified to be of high safety by the case study. The results show that: using 150 m as the weaving section length of an interchange in expressway design has a high probability of failure and low safety. By backcalculating the target reliability that meets the conditions of the first level safety level, it is recommended that 400 m, 370 m and 350 m are selected respectively for the length of interchange weaving section at three design speeds of 100 km/h, 80 km/h and 60 km/h, which can improve the efficiency of the safety and reliability of the whole urban expressway system. References | Related Articles | Metrics

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Influence of Built Environment on the Severity of Urban Traffic Accidents CHEN Jian1, QIU Zhixuan1, PENG Tao1, LIU Keliang1, FU Zhiyan2, TUO Yongheng3 2023, 42(3): 105-111.  DOI: 10.3969/j.issn.1674-0696.2023.03.15 Abstract ( )   PDF (742KB) ( )   In view of the lack of systematic consideration of built environment factors in the analysis of urban traffic accidents, five dimensions including density, diversity, traffic design, accessibility and public transport proximity were selected to characterize the built environment, and four aspects including individual behavior, road conditions, accident types and natural environment were considered at the same time. The machine learning algorithm was used to establish an analysis model that incorporated built environment factors on the severity of urban road traffic accidents. Finally, an empirical analysis was carried out by use of the accident information in a certain district of Chongqing. The research results show that the built environment variables have a greater impact on the severity of accidents. From the perspective of variable importance ranking, the land use mixing degree (14.29%), the density of expressways and trunk roads (12.43%), the density of secondary roads and branch roads (11.54%), population density (11.35%) and accessibility (10.96%) have a higher impact and the cumulative importance reaches 60.57%. At the same time, each variable has a non-linear relationship with the severity of the accident. References | Related Articles | Metrics

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Short-Distance Travel Mode Choice Considering Spatial Heterogeneity HE Mingwei, XIAO Mingyang, HE Ming, SHI Zhuangbin, LIU Yang 2023, 42(3): 112-118.  DOI: 10.3969/j.issn.1674-0696.2023.03.16 Abstract ( )   PDF (1044KB) ( )   Promoting the change of urban residents’ short-distance travel mode from motor vehicles to slow traffic is of vital importance to alleviate traffic congestion and environmental pollution caused by motorized travel. Based on the travel survey data of Kunming residents, travel attributes and built environment data, a geographically weighted logistic regression model was used to explore the influence of travelers’ socioeconomic-demographic attributes, travel attributes and the built environment on the choice of cars and slow traffic modes in short-distance travel. The results show that the geographically weighted logistic regression model fits better than the global regression logistic model does. Intersection density, road network density, population density, total POI density, retirees and commuter trips have a negative effect on car use in short-distance travel in general and a positive effect on distance to CBD in general. But the effects of these variables are significantly spatially heterogeneous, showing opposite effects in different regions. In addition, men, self-employed individuals, groups under the age of 30, college graduates and above, and groups with higher household income are more likely to use cars for short-distance trips, while shopping and entertainment trips are more likely to use slow traffic. References | Related Articles | Metrics

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Influencing Factors of Elderly Adults Driving Switching Behavior CHEN Long1, YANG Chenglu1, JING Peng1, ZHA Qifen2 2023, 42(3): 119-127.  DOI: 10.3969/j.issn.1674-0696.2023.03.17 Abstract ( )   PDF (706KB) ( )   The aging process in China is accelerating. In 2020, the Ministry of Public Security has announced the abolition of the upper limit of 70 years of age for small car drivers license applications. The driving behavior of elderly people has attracted much more attention. A comprehensive analysis method combining the structural equation model and Bayesian network was proposed. The structural equation model was used to verify the social cognitive theoretical factors of elderly peoples switching intention toward driving, Bayesian networks in the field of machine learning was combined to calculate and output key determinants and the relationship strength among influencing factors were also quantified. The research results show that about 16% of the elderly have high-level switching intention toward driving, and attitude, subjective norms, and self-efficacy have the greatest impact on switching intention toward driving. When self-efficacy and attitude of the elderly people change from a low state to a high state, the probability of occurrence of a high state of switching intention increases by approximately 185% and 265%, which can help to understand the psychological needs of elderly drivers and provides ideas for predicting the size of the elderly driving group in the future. References | Related Articles | Metrics

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Refined Classification of Transit Riders under Bus One-Ticket System LI Jun,OU Jingyi, ZHAO Wenting 2023, 42(3): 128-134.  DOI: 10.3969/j.issn.1674-0696.2023.03.18 Abstract ( )   PDF (952KB) ( )   A refined classification method of transit riders under bus one-ticket system was proposed. Firstly, due to the characteristics of the bus one-ticket system, only boarding information is available. The characteristic indexes of the riders, namely, the travel intensity, temporal indicators, spatial indicators and peak-hour indicators, were selected as the indexes of the classification. The correlation analysis was employed to screen indicators. Then, Two-Step clustering was used to cluster transit riders into clear clusters and unclear clusters. Moreover, feature indicators were selected again for clear clusters and unclear clusters for secondary clustering to achieve the refined classification of passengers. A case study on the transit riders data of the one-ticket bus system in Guangzhou shows that the proposed method can effectively classify passengers, and the results of each class depict the travel characteristics of passengers in detail. The proposed classification method is effective and stable. References | Related Articles | Metrics

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Hierarchical Control of Adaptive Cruise System of Intelligent Electric Vehicle ZHAO Shuen1, ZHANG Liang2, GAN Huafu3, CHEN Wenbin4 2023, 42(3): 135-142.  DOI: 10.3969/j.issn.1674-0696.2023.03.19 Abstract ( )   PDF (827KB) ( )   Aiming at the problem of poor tracking of electric vehicles caused by frequent shifts of the preceding vehicle, an adaptive cruise control system based on hierarchical control was established. Firstly, considering the influence of the acceleration and deceleration changes of the preceding vehicle, the variable headway strategy was adopted as the expected safe vehicle distance, and the polynomial fitting method was used to analyze the influence of different vehicle time interval on the feedback gain matrix of the linear quadratic optimal control algorithm and build an upper-level controller based on improved linear quadratic optimal control. Then, the fractional PID control theory was applied to establish the lower controller to accurately track the expected driving torque and braking pressure, and genetic optimization algorithm was used to optimize and adjust the fractional PID parameters. The research shows that the adaptive cruise controller based on hierarchical control can ensure the safety and comfort of the vehicle, which has good adaptability to the frequent acceleration and deceleration conditions of the preceding vehicle and has good tracking performance. References | Related Articles | Metrics

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Dynamic Obstacle Avoidance Trajectory Planning System with Improved Timed-Elastic-Bands XIE Chunli, LIU Feihao 2023, 42(3): 143-150.  DOI: 10.3969/j.issn.1674-0696.2023.03.20 Abstract ( )   PDF (11485KB) ( )   In the robot navigation scene with dynamic obstacles, the timed elastic bands (TEB) algorithm cannot distinguish the types of obstacles, and it is easy to treat dynamic obstacles as static types, resulting in collisions in the navigation process and unable to complete the navigation task. Aiming at the real dynamic environment of the robot, two mean filters were used to filter the laser point cloud to achieve dynamic obstacle detection, and then the dynamic obstacle cost map layer was added to cluster the detected obstacles. Kalman filtering was used to perform the trajectory tracking and state prediction on the motion state of dynamic obstacles. Based on the current motion state of the robot, a dynamic obstacle avoidance trajectory plan was carried out. The Ackerman steering structure robot was used for simulation and the repeated experiments in real dynamic environments. The research results show that the dynamic obstacle avoidance trajectory planning system with improved TEB algorithm can perform real-time trajectory planning in complex dynamic environments and generate safe and smooth local trajectories, which realizes the dynamic obstacle avoidance to complete the navigation task and can meet the dynamic obstacle avoidance requirements of mobile robots. References | Related Articles | Metrics