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How does trip frequency distort time value to impact congestion charging schemes?

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transportation Safety and Environment 2024年第1期6卷 22-39页

作者： Maosheng Li Hangcong Li school of traffic and transportation Engineering Central South UniversityChangshaHunan 410075China

A notable feature of a city or region with close economic and social connections with its neighbours is its highly mixed local and external traffic,and in some cases the external traffic volume is almost as high as that of local *** local traffic volume may be largely made up of the same regular local commuters making frequent trips,external traffic from outside of the city(region)may not be the same people making regular trips to/from the ***,from a large pool of people making infrequent trips to/from the city,the existence of external traffic is proven by data from the licence plate recognition system of road vehicles in Changde,*** function of value of time correlated with the income/wage rate and trip frequency is exploited and verified *** time value distorted by trip frequency is defined as perceived time value(PTV),which also influences the way travellers perceive any travel impedance such as congestion delay and toll *** paper analyses the price of anarchy(POA)when explicitly considering the travel frequency of the trip-makers and their PTV,and compares with previous analysis without considering travel *** show that when travel frequency is considered,the optimal toll of congested road pricing schemes which converts road traffic flow from user equilibrium into system optimization is much lower than that without considering travel *** cost of licence plate auction cannot be treated as a congestion toll,which is only a threshold of vehicle *** travellers choose routes by PTV rather than TV(time value)is proven by an example of Heishipu Bridge in Changsha,Hunan Province,China.

关键词： road congestion charging travel frequency perceived time value road traffic impedance price of anarchy

The characteristics of driver lane-changing behaviour in congested road environments

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transportation Safety and Environment 2024年第3期6卷 96-110页

作者： Wanqi Wang Guozhu Cheng school of traffic and transportation Northeast Forestry UniversityHarbin 150040HeilongjiangChina

Lane-changing behaviour is one of the complex|driving *** lane-changing behaviour of drivers may exacerbate congestion,however driver behavioural characteristics are difficult to accurately acquire and quantify,and thus tend to be simplified or ignored in existing lane-changing *** this paper,the Bik-means clustering algorithm is used to analyse the urban road congestion state discrimination ***,simulated driving tests were conducted for different traffic congestion *** the force feedback system and infrared camera,the data of driver lane-changing behaviours at different traffic congestion levels are obtained separately,and the definitions of the start and end points of a vehicle changing lanes are ***,statistical analysis and discussion of key feature parameters including driver lane-changing behaviour data and visual data under different levels of traffic congestion were *** is found that the average lane-change intention times in each congestion state are 2 s,4 s,6 s and 7 s,while the turn-signal duration and the number of rear-view mirror observations have similar patterns of change to the data on lane-changing intention ***,drivers’pupil diameters become smaller during the lane-changing intention phase,and then relatively enlarge during lane-changing;the range of pupil variation is roughly 3.5 mm to 4 *** frequency of observing the vehicle in front of the target lane increased as the level of congestion increased,and the frequency of observation in the driver’s mirrors while changing lanes approximately doubled compared to driving straight ahead,and this ratio increased as the level of congestion increased.

关键词： road congestion lane-changing behaviour Bik-means clustering algorithm characterization study

Multi-Objective Optimization of Aluminum Alloy Electric Bus Frame Connectors for Enhanced Durability

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 735-755页

作者： Wenjun Zhou Mingzhi Yang Qian Peng Yong Peng Kui Wang Qiang Xiao Key Laboratory of traffic Safety on Track Ministry of EducationSchool of Traffic&Transportation EngineeringCentral South UniversityChangsha410018China school of Mechanical and Automotive Engineering Xiamen University of TechnologyXiamen361024China

The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to *** issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries,necessitating robust frame *** study aims to optimize the connectors of aluminum alloy bus frames,emphasizing durability,energy efficiency,and *** research delves into Multi-Objective Coordinated Optimization(MCO)techniques for lightweight design in aluminum alloy bus body *** goal is to enhance lightweighting,reinforce energy absorption,and improve deformation resistance in connector *** typical aluminum alloy connectors were selected and a design optimization platform was built for their MCO using a variety of software and ***,through three-point bending experiments and finite element analysis on three types of connector components,we identified optimized design parameters based on deformation ***,employing Optimal Latin hypercube design(OLHD),parametric modeling,and neural network approximation,we developed high-precision approximate models for the design parameters of each connector component,targeting energy absorption,mass,and logarithmic ***,utilizing the Archive-based Micro Genetic Algorithm(AMGA),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-dominated SortingGenetic Algorithm(NSGA2),we explored optimized design solutions for these joint ***,we simulated joint assembly buckling during bus rollover crash scenarios to verify and analyze the optimized solutions in three-point bending *** joint component showcased a remarkable 30%–40%mass reduction while boosting energy *** design optimization method exhibits high efficiency and *** contemporary automation technology,the design optimiza

关键词： Aluminum connectors three-point bending simulation parametric design model multi-objective collaborative optimization

Quantitative measurement and application of droplets on physical surfaces based on LIF technology

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transportation Safety and Environment 2024年第2期6卷 104-113页

作者： Fan Wu Shuaixiong Zhou Qingmin Cui Renze Xu Hengkui Li Chao Yu Key Labor atory of traffic Safety on Track of Ministry of Education School of Traffic&Transportation EngineeringCentr al South Univ ersityChangsha 410075HunanChina Joint International Research Laboratory of Key Technologies for Rail traffic Safety School of Traffic&Transportation EngineeringCentral South UniversityChangsha 410075HunanChina school of software Henan University of EngineeringZhengzhou 451191HenanChina National&Local Joint Engineering Research Center of Safety Technology for Rail Vehicle School of Traffic&Transportation EngineeringCentral South UniversityChangsha 410075HunanChina

Contaminated surfaces play a significant role in the transmission of respiratory infectious *** address this issue,we pre-sented a novel quantitative detection method for droplets on physical surfaces,based on the laser-induced fluorescence *** proposed detection method was demonstrated in a realistic high-speed train compartment scenario by simulating the process of droplet release during passengers’breathing and *** experimental results showed that this method could offer high precision(10-1 mg/m^(2))for detecting minute substance concentrations,and its ease of operation makes it suitable for complex en-gineering *** results also revealed that under the combined effects of the indoor airflow and breathing airflow,the range of droplets released by breathing activity exceeded two rows in front of and behind the release ***,we observed that a large number of droplets settled on the seat surfaces on both sides of the same row as the releaser,with over 36%of these droplets concentrated on the backrest area of the *** the respiratory jet velocity increased,the location with the most sed-iment droplets(accounting for 8%of the total sedimentation)occurred on the seat directly in front of the releaser,and approximately 48% of the droplets were found on the back of this *** proposed method overcomes the shortcomings of existing experimental methods in quantitatively capturing the motion characteristics of droplets in complex flow fields.

关键词： quantitative measurement sediment droplets physical surfaces fluorescence measurement high-speed train compart-ment

Investigation of surface textures deterioration on pavement skid-resistance using hysteresis friction models and numerical simulation method

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Friction 2024年第4期12卷 745-779页

作者： Haoyuan LUO Siyu CHEN Leyi ZHU Xiyin LIU Yangzezhi ZHENG Runming ZHAO Xiaoming HUANG school of transportation Southeast UniversityNanjing 211189China National Demonstration Center for Experimental Education of Road and traffic Engineering Southeast UniversityNanjing 211189China

Many rubber friction theories or some method combined theories and field-experiments are employed to evaluate the pavement skid-resistance deterioration due to the evolution of surface ***,these methods are difficult to be implemented in the analysis of situations with multi-factor coupling and some extreme *** study developed a framework to evaluate the skid-resistance deterioration of asphalt *** this framework,the portable laser scanning was used to create the digital worn pavement model,and a hydroplaning finite element(FE)model for these digital worn pavements was constructed to evaluate coupling effects of the texture evolution and factors of slip ratio,slip angle,velocity and water film on braking-cornering characteristics of *** this study,the deterioration of skid-resistance of five typical asphalt pavements due the surface texture wear was systematically investigated by this *** with previous works,this study established the rubber friction models for each digital worn pavement considering the energy hysteresis of rubber and the power spectrum density of surface *** the rubber friction model was used to define the interaction behaviors between the tire and corresponding wore pavements in the FE hydroplaning model,rather than using an empirical friction model or a fixed friction coefficient.

关键词： worn pavement skid-resistance friction coefficient textures evolution water film computer numerical simulation

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

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Computers, Materials & Continua 2024年第6期79卷 3877-3896页

作者： Mingyuan Li Yuanli Gu Qingqiao Geng Hongru Yu school of traffic and transportation Beijing Jiaotong UniversityBeijing100044China Transport Planning and Research Institute Ministry of TransportBeijing100028China

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing *** model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel *** CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and *** on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction *** this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban *** combined prediction model is tested on a taxi travel demand dataset in a certain area of *** results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 ***,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed *** results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

关键词： Urban transport taxi travel demand prediction CEEMDAN-ConvLSTM modal components

Ride-hailing origin-destination demand prediction with spatiotemporal information fusion

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transportation Safety and Environment 2024年第2期6卷 63-74页

作者： Ning Wang Liang Zheng Huitao Shen Shukai Li school of traffic and transportation Engineering Central South UniversityChangsha 410075China State Key Laboratory of Rail traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China

Accurate demand forecasting for online ride-hailing contributes to balancing traffic supply and demand,and improving the service level of ride-hailing *** contrast to previous studies,which have primarily focused on the inflow or outflow demands of each zone,this study proposes a conditional generative adversarial network with a Wasserstein divergence objective(CWGAN-div)to predict ride-hailing origin-destination(OD)demand *** blocks and refined loss functions help to enhance the stability of model *** conditional information is employed to capture external spatiotemporal dependencies and guide the model towards generating more precise *** analysis using ride-hailing data from Manhattan,New York City,demon-strates that our proposed CWGAN-div model can effectively predict the network-wide OD matrix and exhibits strong convergence *** experiments also show that the CWGAN-div outperforms other benchmarking ***,the proposed model displays potential for network-wide ride-hailing OD demand prediction.

关键词： intelligent transport system ride-hailing generative adversarial networks spatiotemporal dependencies origin-destination(OD)demand prediction

Energy-efficient buffer and service rate allocation in manufacturing systems using hybrid machine learning and evolutionary algorithms

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Advances in Manufacturing 2024年第2期12卷 227-251页

作者： Si-Xiao Gao Hui Liu Jun Ota Key Laboratory of traffic Safety on Track of Ministry of Education Institute of Artificial Intelligence and Robotics(IAIR)School of Traffic and Transportation EngineeringCentral South UniversityChangsha410075People’s Republic of China Research into Artifacts Center for Engineering School of EngineeringThe University of TokyoTokyoJapan

Currently,simultaneous buffer and service rate allocation is a topic of interest in the optimization of manufacturing *** allocation problems have been solved previously to satisfy economic requirements;however,owing to the progress of green manufacturing,energy conservation and environmental protection have become increasingly ***,an energy-efficient approach is developed to maximize the throughput and minimize the energy consumption of manufacturing systems,subject to the total buffer capacity,total service rate,and predefined energy *** energy-efficient approach integrates the simulated annealing-non-dominated sorting genetic algorithm-II with the honey badger algorithm-histogram-based gradient boosting regression *** former algorithm searches for Pareto-optimal solutions of sufficient *** latter algorithm builds prediction models to rapidly calculate the throughput,energy consumption,and energy *** examples show that the proposed hybrid approach can achieve a better solution quality compared with previously reported ***,the prediction models can rapidly evaluate manufacturing systems with sufficient *** study benefits the multi-objective optimization of green manufacturing systems.

关键词： Energy-efficient allocation Multi-objective optimization Energy efficiency Energy consumption Machine learning

A review of vehicle detection methods based on computer vision

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Journal of Intelligent and Connected Vehicles

Journal of Intelligent and Connected Vehicles 2024年第1期7卷 1-18页

作者： Changxi Ma Fansong Xue school of traffic and transportation Lanzhou Jiaotong UniversityLanzhou 730070China Key Laboratory of Railway Industry on Plateau Railway transportation Intelligent Management and Control Lanzhou 730070China

With the increasing number of vehicles,there has been an unprecedented pressure on the operation and maintenance of intelligent transportation systems and transportation *** order to achieve faster and more accurate identification of traffic vehicles,computer vision and deep learning technology play a vital role and have made significant *** study summarizes the current research status,latest findings,and future development trends of traditional detection algorithms and deep learning-based detection *** the detection algorithms based on deep learning,this study focuses on the representative convolutional neural network ***,it examines the two-stage and one-stage detection algorithms,which have been extensively utilized in the field of intelligent transportation *** to traditional detection algorithms,deep learning-based detection algorithms can achieve higher accuracy and *** single-stage detection algorithm is more efficient for real-time detection,while the two-stage detection algorithm is more accurate than the single-stage detection *** the follow-up research,it is important to consider the balance between detection efficiency and detection ***,vehicle missed detection and false detection in complex scenes,such as bad weather and vehicle overlap,should be taken into *** will ensure better application of the research findings in engineering practice.

关键词： intelligent transportation system computer vision deep learning vehicle detection object detection algorithm