The coefficients of retroreflection and chromaticity coordinates are critical metrics for determining the quality of a retroreflector. However, conventional retroreflection measurement techniques rely heavily on the night-time colour, size, and characteristics of the sample being measured. This complicates the measurement process and leads to deviations in the test results. In addition, chromaticity cannot be determined using this approach. Therefore, it is necessary to improve the measurement accuracy, simplify the measurement process, and achieve the measurement of the traffic sign RA and chromaticity coordinates simultaneously. In this study, an improved method for retroreflector characterisation using imaging was proposed. This allowed for the measurement of the coefficients of retroreflection and the chromaticity coordinates simultaneously, and only a white standard sample was required for calibration. The primary components of the proposed system included a lighting projector, a receiver, two motorised rotational stages, a retroreflective sample holder, and customised software that used scaling factors to convert a digital signal into sample retroreflection coefficients and retroreflective chromaticity coordinates. The experimental results indicated that the raw data output from the camera exhibited a positive correlation relationship with the luminous flux from the surface of the retroreflector. The maximum measurement errors for the retroreflection and chromaticity were −12.2 cd/(lx·m2) and −2.09%, respectively. This method was inexpensive and convenient, used a commercially available digital camera, could help to identify defects in retroreflection and chromaticity for retroreflective sheeting, and led to increased accessibility for the quality control of retroreflective sheeting.
{"title":"Establishment of a metric to characterise retroreflector properties using a consumer-grade colour camera","authors":"Huayang He, Wenying Su, Qiutong Cheng","doi":"10.1093/tse/tdac039","DOIUrl":"https://doi.org/10.1093/tse/tdac039","url":null,"abstract":"\u0000 The coefficients of retroreflection and chromaticity coordinates are critical metrics for determining the quality of a retroreflector. However, conventional retroreflection measurement techniques rely heavily on the night-time colour, size, and characteristics of the sample being measured. This complicates the measurement process and leads to deviations in the test results. In addition, chromaticity cannot be determined using this approach. Therefore, it is necessary to improve the measurement accuracy, simplify the measurement process, and achieve the measurement of the traffic sign RA and chromaticity coordinates simultaneously. In this study, an improved method for retroreflector characterisation using imaging was proposed. This allowed for the measurement of the coefficients of retroreflection and the chromaticity coordinates simultaneously, and only a white standard sample was required for calibration. The primary components of the proposed system included a lighting projector, a receiver, two motorised rotational stages, a retroreflective sample holder, and customised software that used scaling factors to convert a digital signal into sample retroreflection coefficients and retroreflective chromaticity coordinates. The experimental results indicated that the raw data output from the camera exhibited a positive correlation relationship with the luminous flux from the surface of the retroreflector. The maximum measurement errors for the retroreflection and chromaticity were −12.2 cd/(lx·m2) and −2.09%, respectively. This method was inexpensive and convenient, used a commercially available digital camera, could help to identify defects in retroreflection and chromaticity for retroreflective sheeting, and led to increased accessibility for the quality control of retroreflective sheeting.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46861556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Li Yu, Wang Xuhui, Yang Jie, Zhang Zemiao, Wang Chenglei, Qian Bosen, Tian Xudong, Wang Tiantian
This study investigates the airborne transmission of virus-laden droplets generated by a cough of patients in an aircraft cabin to reveal the infection risk of taking an airplane. The influence of the ventilation system on flow field of the cabin was analyzed to reveal its effects on the airborne transmission of virus-laden droplets. Meanwhile, human body heat was also considered in the simulations. The results show that hot plume due to human body heat has significant impact on the upward movement of virus-laden droplets. The virus-laden droplets expelled by a cough can be transmitted to the region with two to three rows away from the generator. Particularly, the transverse motion present in the early stage of the droplet transmission results in a high infection risk to the passengers in the same row with the patient. This work gives insight into the understanding of the airborne transmission of virus-laden droplets in the entire passenger cabin.
{"title":"Airborne transmission of virus-laden droplets in an aircraft cabin","authors":"Li Yu, Wang Xuhui, Yang Jie, Zhang Zemiao, Wang Chenglei, Qian Bosen, Tian Xudong, Wang Tiantian","doi":"10.1093/tse/tdac079","DOIUrl":"https://doi.org/10.1093/tse/tdac079","url":null,"abstract":"\u0000 This study investigates the airborne transmission of virus-laden droplets generated by a cough of patients in an aircraft cabin to reveal the infection risk of taking an airplane. The influence of the ventilation system on flow field of the cabin was analyzed to reveal its effects on the airborne transmission of virus-laden droplets. Meanwhile, human body heat was also considered in the simulations. The results show that hot plume due to human body heat has significant impact on the upward movement of virus-laden droplets. The virus-laden droplets expelled by a cough can be transmitted to the region with two to three rows away from the generator. Particularly, the transverse motion present in the early stage of the droplet transmission results in a high infection risk to the passengers in the same row with the patient. This work gives insight into the understanding of the airborne transmission of virus-laden droplets in the entire passenger cabin.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42434862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to solve path planning of intelligent vehicles in self-driving. In this study, an improved path planning method combining constraints of environment and vehicle is proposed. The algorithm designs a reasonable path cost function, then uses heuristic guided search strategy to improve the speed and quality of path planning, and finally generates smooth and continuous curvature paths based on the path post-processing method based on the requirements of path smoothness. simulation test show that compared with the basic RRT, RRT-connect and RRT* algorithms, the path length of the proposed algorithm can be reduced by 19.7%, 29.3% and 1% respectively and the maximum planned path curvature of the proposed algorithm is 0.0796 m-1 and 0.1512 m-1 respectively under the condition of a small amount of planning time. The algorithm can plan the more suitable driving path for intelligent vehicle in complex environment.
{"title":"Path Planning Algorithms for Self-Driving vehicle based on improved RRT-Connect","authors":"Li Jin, Huang Chaowei, Pan Minqiang","doi":"10.1093/tse/tdac061","DOIUrl":"https://doi.org/10.1093/tse/tdac061","url":null,"abstract":"\u0000 This study aims to solve path planning of intelligent vehicles in self-driving. In this study, an improved path planning method combining constraints of environment and vehicle is proposed. The algorithm designs a reasonable path cost function, then uses heuristic guided search strategy to improve the speed and quality of path planning, and finally generates smooth and continuous curvature paths based on the path post-processing method based on the requirements of path smoothness. simulation test show that compared with the basic RRT, RRT-connect and RRT* algorithms, the path length of the proposed algorithm can be reduced by 19.7%, 29.3% and 1% respectively and the maximum planned path curvature of the proposed algorithm is 0.0796 m-1 and 0.1512 m-1 respectively under the condition of a small amount of planning time. The algorithm can plan the more suitable driving path for intelligent vehicle in complex environment.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46995926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Convolutional neural networks (CNNs) are widely used in the field of fault diagnosis due to their strong feature-extraction capability. However, in each timestep, CNNs only consider the current input and ignores any cyclicity in time, therefore finding difficulties in mining temporal features from the data. In this work, the third-generation neural network—spiking neural network (SNN)—is utilized in bearing fault diagnosis. SNNs incorporate temporal concepts and utilize discrete spike sequences in communication, making it more biologically explanatory. Inspired by the classic CNN LeNet-5 framework, a bearing fault diagnosis method based on a convolutional SNN is proposed. In this method, the spiking convolutional network and the spiking classifier network are constructed by using the IF and LIF model, respectively, and end-to-end training is conducted on the overall model using a surrogate gradient method. The signals are adaptively encoded into spikes in the spiking neuron layer. In addition, the network utilizes max-pooling, which is consistent with the spatial–temporal characteristics of SNNs. Combined with the spiking convolutional layers, the network fully extracts the spatial–temporal features from the bearing vibration signals. Experimental validations and comparisons are conducted on bearings. The results show that the proposed method achieves high accuracy and takes fewer time steps.
{"title":"A bearing fault diagnosis method based on a convolutional spiking neural network with spatial–temporal feature-extraction capability","authors":"Changfan Zhang, Z. Xiao, Zhenwen Sheng","doi":"10.1093/tse/tdac050","DOIUrl":"https://doi.org/10.1093/tse/tdac050","url":null,"abstract":"\u0000 Convolutional neural networks (CNNs) are widely used in the field of fault diagnosis due to their strong feature-extraction capability. However, in each timestep, CNNs only consider the current input and ignores any cyclicity in time, therefore finding difficulties in mining temporal features from the data. In this work, the third-generation neural network—spiking neural network (SNN)—is utilized in bearing fault diagnosis. SNNs incorporate temporal concepts and utilize discrete spike sequences in communication, making it more biologically explanatory. Inspired by the classic CNN LeNet-5 framework, a bearing fault diagnosis method based on a convolutional SNN is proposed. In this method, the spiking convolutional network and the spiking classifier network are constructed by using the IF and LIF model, respectively, and end-to-end training is conducted on the overall model using a surrogate gradient method. The signals are adaptively encoded into spikes in the spiking neuron layer. In addition, the network utilizes max-pooling, which is consistent with the spatial–temporal characteristics of SNNs. Combined with the spiking convolutional layers, the network fully extracts the spatial–temporal features from the bearing vibration signals. Experimental validations and comparisons are conducted on bearings. The results show that the proposed method achieves high accuracy and takes fewer time steps.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44062724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kian Lun Soon, Robin Kuok Cheong Chan, J. Lim, R. Parthiban
The design parameters serve as an integral part of developing a robust short-term traffic forecasting model. These parameters include scope determination, input data preparation, output parameters, and modelling techniques. This paper takes a further leap to analyse the recent trend of design parameters through a Systematic Literature Review (SLR) based on peer-reviewed articles up to 2021. The key important findings are summarised along with the challenges to performing short-term traffic forecasting. Intuitively, this paper offers insights into the next wave of research that contributes significantly to industries.
{"title":"Short-term traffic forecasting model – prevailing trends and guidelines","authors":"Kian Lun Soon, Robin Kuok Cheong Chan, J. Lim, R. Parthiban","doi":"10.1093/tse/tdac058","DOIUrl":"https://doi.org/10.1093/tse/tdac058","url":null,"abstract":"\u0000 The design parameters serve as an integral part of developing a robust short-term traffic forecasting model. These parameters include scope determination, input data preparation, output parameters, and modelling techniques. This paper takes a further leap to analyse the recent trend of design parameters through a Systematic Literature Review (SLR) based on peer-reviewed articles up to 2021. The key important findings are summarised along with the challenges to performing short-term traffic forecasting. Intuitively, this paper offers insights into the next wave of research that contributes significantly to industries.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46795689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With increase of train speed, braking plate technology has a good application prospect in the high-speed stage of the train. Based on the 1/8th scaled symmetrical train model composed by two half cars, Reynolds Average Navier-stokes (RANS) equations and Shear Stress Transfer (SST) k-ω turbulence model are adopted to simulate the aerodynamic performance of the train with plate, aerodynamic drag dependence of the single parameter of the plate (shape, area, angle, position and number) is analyzed, and the identification research of the main aerodynamic parameters of plate is also carried out. The numerical settings used in this paper is verified by wind tunnel test data. Results show that the braking plate with aspect ratio of 1 has better performance on aerodynamic drag. The area, opening angle and number of plates are basically positively correlated with the total aerodynamic drag of the target car and plate. Arranging plates at the downstream of the vehicle is a good method of raising total aerodynamic drag. Within the range of plate parameter design in this paper, by using orthogonal design of experiment and method of range analysis and analysis of variance, the influence degrees of plate parameters on aerodynamic drag are determined, and the order is number, area and opening angle of plate. The research results provide theoretical support for the design and safe operation of high-speed train with aerodynamic braking plate.
{"title":"Regularity and sensitivity analysis of main parameters of plate effects on the aerodynamic braking drag of a high-speed train","authors":"Peng Li, Shan Huang, Y. Liu, J. Niu","doi":"10.1093/tse/tdac051","DOIUrl":"https://doi.org/10.1093/tse/tdac051","url":null,"abstract":"\u0000 With increase of train speed, braking plate technology has a good application prospect in the high-speed stage of the train. Based on the 1/8th scaled symmetrical train model composed by two half cars, Reynolds Average Navier-stokes (RANS) equations and Shear Stress Transfer (SST) k-ω turbulence model are adopted to simulate the aerodynamic performance of the train with plate, aerodynamic drag dependence of the single parameter of the plate (shape, area, angle, position and number) is analyzed, and the identification research of the main aerodynamic parameters of plate is also carried out. The numerical settings used in this paper is verified by wind tunnel test data. Results show that the braking plate with aspect ratio of 1 has better performance on aerodynamic drag. The area, opening angle and number of plates are basically positively correlated with the total aerodynamic drag of the target car and plate. Arranging plates at the downstream of the vehicle is a good method of raising total aerodynamic drag. Within the range of plate parameter design in this paper, by using orthogonal design of experiment and method of range analysis and analysis of variance, the influence degrees of plate parameters on aerodynamic drag are determined, and the order is number, area and opening angle of plate. The research results provide theoretical support for the design and safe operation of high-speed train with aerodynamic braking plate.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41835982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Track utilization is the most important technical operation in high-speed railway stations. It's an effective way to take flexible management based on dispatchers’ decision preferences into consideration for making track utilization plans to relieve the influence caused by unmeasurable unstructured factors. Thus, based on flexible management concept and taken the flexible optimal for track utilization in high-speed railway stations as the object, time and space occupation safety trajectories of arrival routes, departure routes and tracks are all analyzed. Then, taking following constraints into consideration, i.e. minimum safety time intervals for various routes and tracks occupation, space-time arc occupation and decision-makers’ preferences, a flexible optimal model for track utilization in high-speed railway stations are established to maximize its balance and robustness and to minimize its volatility at the same time. Further, a flexible optimal solution based on a simulated annealing algorithm is designed to make a safety track utilization plan in high-speed railway stations integrating the dispatchers’ decision preference. The results gained from given experiments show that the proposed methodology can effectively make satisfied safety track utilization plans based on decision-makers’ preferences, which can improve its balance and robustness level significantly. Meanwhile, its volatility can be reduced as much as possible caused by flexible management based on artificial intervention to ensure the relative stability of the plan.
{"title":"Flexible Optimal Model and Algorithm for Track Utilization in High-speed Railway Stations","authors":"Quan Gao, Yinggui Zhang, Zhiya Chen, Yuan Chen","doi":"10.1093/tse/tdac057","DOIUrl":"https://doi.org/10.1093/tse/tdac057","url":null,"abstract":"\u0000 Track utilization is the most important technical operation in high-speed railway stations. It's an effective way to take flexible management based on dispatchers’ decision preferences into consideration for making track utilization plans to relieve the influence caused by unmeasurable unstructured factors. Thus, based on flexible management concept and taken the flexible optimal for track utilization in high-speed railway stations as the object, time and space occupation safety trajectories of arrival routes, departure routes and tracks are all analyzed. Then, taking following constraints into consideration, i.e. minimum safety time intervals for various routes and tracks occupation, space-time arc occupation and decision-makers’ preferences, a flexible optimal model for track utilization in high-speed railway stations are established to maximize its balance and robustness and to minimize its volatility at the same time. Further, a flexible optimal solution based on a simulated annealing algorithm is designed to make a safety track utilization plan in high-speed railway stations integrating the dispatchers’ decision preference. The results gained from given experiments show that the proposed methodology can effectively make satisfied safety track utilization plans based on decision-makers’ preferences, which can improve its balance and robustness level significantly. Meanwhile, its volatility can be reduced as much as possible caused by flexible management based on artificial intervention to ensure the relative stability of the plan.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47506086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel switch diagnosis method based on self-attention and residual deep Convolutional Neural Networks (CNN) is proposed. Because of the imbalanced dataset, the Kmeans synthetic minority oversampling technique (SMOTE) is applied to balancing the dataset at first. Then, the deep CNN is utilized to extract local features from long power curves, and the residual connection is performed to handle the performance degeneration. In the end, the Multi-heads Channel Self Attention focuses on those important local features. The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods. With the residual connection and Multi-heads Channel Self Attention, the proposed method has achieved an accuracy of 99.83% impressively. The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.
{"title":"Railway switch fault diagnosis based on Multi heads Channel Self Attention, Residual Connection and Deep CNN","authors":"Xirui Chen, Hui Liu, Zhu Duan","doi":"10.1093/tse/tdac045","DOIUrl":"https://doi.org/10.1093/tse/tdac045","url":null,"abstract":"\u0000 A novel switch diagnosis method based on self-attention and residual deep Convolutional Neural Networks (CNN) is proposed. Because of the imbalanced dataset, the Kmeans synthetic minority oversampling technique (SMOTE) is applied to balancing the dataset at first. Then, the deep CNN is utilized to extract local features from long power curves, and the residual connection is performed to handle the performance degeneration. In the end, the Multi-heads Channel Self Attention focuses on those important local features. The ablation and comparison experiments are applied to verifying the effectiveness of the proposed methods. With the residual connection and Multi-heads Channel Self Attention, the proposed method has achieved an accuracy of 99.83% impressively. The t-SNE based visualizations for features of the middle layers enhance the trustworthiness.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42705840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shuai Li, Weijia Wu, Xiaofeng Ma, Ming Zhong, M. Safdar
Transportation sector is the most significant contributor to anthropogenic greenhouse gas (GHG) emissions. Particularly, maritime transportation, which is predominantly powered by fossil-fuel engines, accounts for more than 90% of world freight movement and emits 3% of global carbon dioxide (CO2) emissions. China is the world's largest emitter of CO2 and plays a key role in mitigating global climate change. In order to tackle this pressing concern, this study analyzes the port's throughput, the current number of trucks, and their emissions during the container truck purchasing process. While the previous studies about container truck purchasing plans mostly focused on the trucks' price and port needs. The objective of this study is to minimize the total cost of a port's inland transportation using optimization technique such as the interval uncertainty planning model to convert container truck emissions into social costs. This study considers the port of Yangtze as a case study. This study has designed two scenarios. (i) The base scenario (business-as-usual (BAU)) is used to quantify the relationship between pollutant emissions and system cost. In the base scenario, no environmental control facilities are used during the planning period, and there is no need to purchase new energy container trucks (ii) Expected scenario, referred to as (scenario A), for three planning periods. In scenario A, the emissions levels are required to remain at the same level as the first planning period during the whole planning period. By solving the above model, the number of all truck types, system cost, container throughput, and truck emissions in the port area were analyzed. The results showed that if no emission reduction control measures are implemented in the next 9 years, the growth rate of pollutants in the port area can be exceeded up to 20%. In addition, The findings showed clearly that truck emissions are reduced by purchasing new energy trucks and restricting the number of fossil-fuel (diesel) trucks. This study could also help to minimize system costs associated with port planning and management.
{"title":"Modeling medium and long term purchasing plans for environment-oriented container truck: a case study of yangtze river port","authors":"Shuai Li, Weijia Wu, Xiaofeng Ma, Ming Zhong, M. Safdar","doi":"10.1093/tse/tdac043","DOIUrl":"https://doi.org/10.1093/tse/tdac043","url":null,"abstract":"\u0000 Transportation sector is the most significant contributor to anthropogenic greenhouse gas (GHG) emissions. Particularly, maritime transportation, which is predominantly powered by fossil-fuel engines, accounts for more than 90% of world freight movement and emits 3% of global carbon dioxide (CO2) emissions. China is the world's largest emitter of CO2 and plays a key role in mitigating global climate change. In order to tackle this pressing concern, this study analyzes the port's throughput, the current number of trucks, and their emissions during the container truck purchasing process. While the previous studies about container truck purchasing plans mostly focused on the trucks' price and port needs. The objective of this study is to minimize the total cost of a port's inland transportation using optimization technique such as the interval uncertainty planning model to convert container truck emissions into social costs. This study considers the port of Yangtze as a case study. This study has designed two scenarios. (i) The base scenario (business-as-usual (BAU)) is used to quantify the relationship between pollutant emissions and system cost. In the base scenario, no environmental control facilities are used during the planning period, and there is no need to purchase new energy container trucks (ii) Expected scenario, referred to as (scenario A), for three planning periods. In scenario A, the emissions levels are required to remain at the same level as the first planning period during the whole planning period. By solving the above model, the number of all truck types, system cost, container throughput, and truck emissions in the port area were analyzed. The results showed that if no emission reduction control measures are implemented in the next 9 years, the growth rate of pollutants in the port area can be exceeded up to 20%. In addition, The findings showed clearly that truck emissions are reduced by purchasing new energy trucks and restricting the number of fossil-fuel (diesel) trucks. This study could also help to minimize system costs associated with port planning and management.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":"1 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41390805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Chen, Christian Buerger, Miao Lin, Xudong Li, Volker Labenski, Haixia Jin, Hai Wang, Yang Liu, Tsuyoshi Ino, Harald Feifel, Tian Tan, Fangrong Chang
Left Turn Across Path with Opposite Direction (LTAP/OD) conflicts are one of the most common crash types at intersections. The research aims to reveal the general and dynamic information about the conflict for the most relevant street layouts for each conflict configuration of the LTAP/OD accidents involving passenger cars, motorcycles and Ebikes. The analysis was based on 276 LTAP/OD accidents collected by China In-Depth Accident Study (CIDAS 2011–2019). The LTAP/OD accidents include 44 car-to-car conflicts, 157 car-to-motorcycle conflicts and 75 car-to-Ebike conflicts. Most of accidents belonging to three types were observed at the W0 street layout without green belt separating the oncoming lane and no offset lane between the turning car and the oncoming traffic, the main distance between both vehicles in the beginning of the critical situation being about four meters, occurring in the clear day with no rain and at junctions lighted either because of daylight or based on street lighting. In terms of the turning car initial speed, the range is between 15-30 km/h for most car-to-car and car-to-motorcycle accidents but 30-40 km/h for most car-to-Ebike accidents. As for the collision speed, this range is between 10 and 20 km/h for car-to-car and car-to-Ebike accidents and between 10 and 25 km/h for car-to-motorcycle crashes. Based on the distributions of objective motorcycles’ and Ebike's positions in collisions with passenger cars, the maximum longitudinal distance is 60 m for both two types of accidents and the maximum lateral distance ranges from -20 m to 20 m and from -15 m to 15 m, respectively.
{"title":"Left turn across path and opposite direction accidents in China: CIDAS accident study","authors":"Y. Chen, Christian Buerger, Miao Lin, Xudong Li, Volker Labenski, Haixia Jin, Hai Wang, Yang Liu, Tsuyoshi Ino, Harald Feifel, Tian Tan, Fangrong Chang","doi":"10.1093/tse/tdac070","DOIUrl":"https://doi.org/10.1093/tse/tdac070","url":null,"abstract":"\u0000 Left Turn Across Path with Opposite Direction (LTAP/OD) conflicts are one of the most common crash types at intersections. The research aims to reveal the general and dynamic information about the conflict for the most relevant street layouts for each conflict configuration of the LTAP/OD accidents involving passenger cars, motorcycles and Ebikes. The analysis was based on 276 LTAP/OD accidents collected by China In-Depth Accident Study (CIDAS 2011–2019). The LTAP/OD accidents include 44 car-to-car conflicts, 157 car-to-motorcycle conflicts and 75 car-to-Ebike conflicts. Most of accidents belonging to three types were observed at the W0 street layout without green belt separating the oncoming lane and no offset lane between the turning car and the oncoming traffic, the main distance between both vehicles in the beginning of the critical situation being about four meters, occurring in the clear day with no rain and at junctions lighted either because of daylight or based on street lighting. In terms of the turning car initial speed, the range is between 15-30 km/h for most car-to-car and car-to-motorcycle accidents but 30-40 km/h for most car-to-Ebike accidents. As for the collision speed, this range is between 10 and 20 km/h for car-to-car and car-to-Ebike accidents and between 10 and 25 km/h for car-to-motorcycle crashes. Based on the distributions of objective motorcycles’ and Ebike's positions in collisions with passenger cars, the maximum longitudinal distance is 60 m for both two types of accidents and the maximum lateral distance ranges from -20 m to 20 m and from -15 m to 15 m, respectively.","PeriodicalId":52804,"journal":{"name":"Transportation Safety and Environment","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49166064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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