International Journal of Transportation Science and Technology最新文献_第2页

Comparing the vibrational behavior of e-kick scooters and e-bikes: Evidence from Italy 比较电动滑板车和电动自行车的振动特性。来自意大利的证据

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2023.10.010

Roberto Ventura , Andrea Ghirardi , David Vetturi , Giulio Maternini , Benedetto Barabino

E-kick scooters are currently among the most popular emerging electric-powered personal micro-mobility vehicles (e-PMVs), and have recently been equated to e-bikes. However, even if the dynamic behavior of e-bikes is well studied, much less has been done to understand the behavior of e-kick scooters. Furthermore, comparisons between the two vehicles have rarely been investigated and only based on mechanical models. This study addresses this gap by proposing a novel framework that evaluates the vibrational behaviors of both vehicles when driven by different users and exposed to the pavement irregularities, using both real and simulated data. The experimental data are collected equipping an e-kick scooter and an e-bike with inertial measurement units (IMUs), and then processed by the ISO 2631–1 method to obtain an objective evaluation of the comfort. Next, the experimental data are expanded to include uncertainty applying a Monte Carlo simulation based on a two-layer feed-forward artificial neural network (ANN). Afterwards, several statistical analyses are performed to understand the key factors affecting the vibrational magnitude (and their extent) for each vehicle. This framework was tested in an Italian city (Brescia) along urban paths with five different pavement surfaces. The results showed that the e-kick scooter appears to be globally more solicited than the e-bike in terms of vibrational magnitude. Moreover, the pavement surface, sensor position, user gender, user height, and travel speed are identified as crucial factors explaining the vibrational magnitude for both vehicles. The overall findings challenge the recent European regulations that equated e-kick scooters with bikes. These findings can assist public administrations in planning the urban circulation of e-bikes and e-kick scooters, and suggest that manufacturers incorporate shock absorbers into e-kick scooter designs to enhance rider comfort.

电动滑板车是目前最受欢迎的新兴电动个人微型移动交通工具(e- pmv)之一，最近被等同于电动自行车。然而，即使对电动自行车的动态行为进行了很好的研究，对电动踏板车的行为的了解也少得多。此外，两种车辆之间的比较很少被调查，只是基于机械模型。这项研究通过提出一个新的框架来弥补这一差距，该框架使用真实和模拟数据来评估两种车辆在由不同用户驾驶和暴露于路面不平整时的振动行为。在电动踏板车和电动自行车上安装惯性测量装置，采集实验数据，并采用ISO 2631-1方法对实验数据进行处理，获得对电动踏板车和电动自行车舒适性的客观评价。其次，应用基于两层前馈人工神经网络的蒙特卡罗模拟将实验数据扩展到包含不确定性。之后，进行了一些统计分析，以了解影响每辆车振动幅度(及其程度)的关键因素。这个框架在意大利城市布雷西亚沿着五种不同路面的城市道路进行了测试。结果表明，就振动幅度而言，电动滑板车似乎比电动自行车在全球范围内更受欢迎。此外，路面表面、传感器位置、用户性别、用户身高和行驶速度被认为是解释两种车辆振动幅度的关键因素。总体调查结果挑战了最近欧洲将电动滑板车与自行车等同起来的规定。这些发现可能有助于公共管理部门规划电动自行车和电动踏板车在城市的流通，并建议制造商改进电动踏板车的设计，包括减震器，以增加舒适性。

{"title":"Comparing the vibrational behavior of e-kick scooters and e-bikes: Evidence from Italy","authors":"Roberto Ventura , Andrea Ghirardi , David Vetturi , Giulio Maternini , Benedetto Barabino","doi":"10.1016/j.ijtst.2023.10.010","DOIUrl":"10.1016/j.ijtst.2023.10.010","url":null,"abstract":"<div><div>E-kick scooters are currently among the most popular emerging electric-powered personal micro-mobility vehicles (e-PMVs), and have recently been equated to e-bikes. However, even if the dynamic behavior of e-bikes is well studied, much less has been done to understand the behavior of e-kick scooters. Furthermore, comparisons between the two vehicles have rarely been investigated and only based on mechanical models. This study addresses this gap by proposing a novel framework that evaluates the vibrational behaviors of both vehicles when driven by different users and exposed to the pavement irregularities, using both real and simulated data. The experimental data are collected equipping an e-kick scooter and an e-bike with inertial measurement units (IMUs), and then processed by the ISO 2631–1 method to obtain an objective evaluation of the comfort. Next, the experimental data are expanded to include uncertainty applying a Monte Carlo simulation based on a two-layer feed-forward artificial neural network (ANN). Afterwards, several statistical analyses are performed to understand the key factors affecting the vibrational magnitude (and their extent) for each vehicle. This framework was tested in an Italian city (Brescia) along urban paths with five different pavement surfaces. The results showed that the e-kick scooter appears to be globally more solicited than the e-bike in terms of vibrational magnitude. Moreover, the pavement surface, sensor position, user gender, user height, and travel speed are identified as crucial factors explaining the vibrational magnitude for both vehicles. The overall findings challenge the recent European regulations that equated e-kick scooters with bikes. These findings can assist public administrations in planning the urban circulation of e-bikes and e-kick scooters, and suggest that manufacturers incorporate shock absorbers into e-kick scooter designs to enhance rider comfort.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 68-86"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135455205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatically detect crosswalks from satellite view images: A deep learning approach with ground truth verification 从卫星视图图像自动检测人行横道--带地面实况验证的深度学习方法

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.01.006

Joseph Luttrell IV , Yuanyuan Zhang , Chaoyang Zhang

Like roadway information is to motor vehicle safety, pedestrian facility information (e.g., sidewalk presence) is crucial towards improving the safety of these vulnerable road users. Yet unlike widely accessible roadway data, pedestrian facility data is unavailable for most state agencies. Without this information, data-driven problem identification, countermeasure analysis, project evaluation, and performance management will be heavily impeded. Thus, urgent need for this data was recognized by state departments of transportation (DOTs). To address this need, we developed an automated approach for the automated detection of crosswalks in satellite images. The most advanced deep learning methodology, transfer learning with a convolutional neural network (CNN) was used to handle real-world images. During the prediction process, a satellite image of a roadway pavement was analyzed by the satellite view model to predict the presence of a crosswalk. Then, the street view image of the same target was detected by the integrated street view model as a ground truth check. A total of 18 361 images from Bing maps in satellite view and street view were used to train and test the deep learning model. As a result, the satellite view model itself achieved 98.43% accuracy using testing data from the same region. When dealing with data from another region, using the satellite view detection with ground truth checking increased the accuracy by 49%. It is obvious that by integrating the ground truth checking model into the satellite view crosswalk detection, we can obtain a more robust model which can handle highly occluded, low quality satellite images.

{"title":"Automatically detect crosswalks from satellite view images: A deep learning approach with ground truth verification","authors":"Joseph Luttrell IV , Yuanyuan Zhang , Chaoyang Zhang","doi":"10.1016/j.ijtst.2024.01.006","DOIUrl":"10.1016/j.ijtst.2024.01.006","url":null,"abstract":"<div><div>Like roadway information is to motor vehicle safety, pedestrian facility information (e.g., sidewalk presence) is crucial towards improving the safety of these vulnerable road users. Yet unlike widely accessible roadway data, pedestrian facility data is unavailable for most state agencies. Without this information, data-driven problem identification, countermeasure analysis, project evaluation, and performance management will be heavily impeded. Thus, urgent need for this data was recognized by state departments of transportation (DOTs). To address this need, we developed an automated approach for the automated detection of crosswalks in satellite images. The most advanced deep learning methodology, transfer learning with a convolutional neural network (CNN) was used to handle real-world images. During the prediction process, a satellite image of a roadway pavement was analyzed by the satellite view model to predict the presence of a crosswalk. Then, the street view image of the same target was detected by the integrated street view model as a ground truth check. A total of 18 361 images from Bing maps in satellite view and street view were used to train and test the deep learning model. As a result, the satellite view model itself achieved 98.43% accuracy using testing data from the same region. When dealing with data from another region, using the satellite view detection with ground truth checking increased the accuracy by 49%. It is obvious that by integrating the ground truth checking model into the satellite view crosswalk detection, we can obtain a more robust model which can handle highly occluded, low quality satellite images.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 165-176"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139634129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An empirical study on the stochastic long-term travel demands of a large-scale metro network 大型地铁网络随机长期旅行需求实证研究

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.02.003

Sen Huang , Xiangdong Xu , Yichao Pu

The widely-existed uncertainty of origin–destination (OD) demand in transportation networks has attracted extensive attention. Most characterizations or models of stochastic OD demands in networks assume a homogenous probability distribution, though empirical studies are lacking of large-scale networks to justify this assumption. Given that the long-term continuous automatic fare collection (AFC) data of metro networks can provide complete OD passenger demand information, this study takes the Shanghai metro network as an example to empirically examine the stochasticity characteristics of OD passenger demands of metro network. Based on the morning peak OD demand data for 250 weekdays, a local outlier factor (LOF) method is used to identify and remove outliers in the data. A clustering method is used to cluster the OD pairs, study the fluctuation and distribution characteristics of the OD passenger demands, and select the optimal distribution type through goodness-of-fit indices. The results show that 1) the coefficients of variation of morning peak OD demands in the network are mainly distributed in the range of 0.2–0.6, different OD pairs have different fluctuations, and the degree of demand fluctuation decreases as the mean increases; 2) the probability distribution types of OD demands based on statistical characteristics are heterogeneous; and 3) the optimal distribution type of OD demands is Poisson, lognormal/Gamma, and normal for OD pairs characterized by a small mean and right-skewness, a small mean and skewness close to 0, and a large mean, respectively. In contrast to the simple average-based data processing of OD passenger demand in metro networks, this paper presents a new perspective of mining long-term continuous data to understand the inherent stochasticity of OD passenger demands. The results can provide more realistic and practical inputs and assumptions for theoretical research on stochastic OD demands in metro networks.

{"title":"An empirical study on the stochastic long-term travel demands of a large-scale metro network","authors":"Sen Huang , Xiangdong Xu , Yichao Pu","doi":"10.1016/j.ijtst.2024.02.003","DOIUrl":"10.1016/j.ijtst.2024.02.003","url":null,"abstract":"<div><div>The widely-existed uncertainty of origin–destination (OD) demand in transportation networks has attracted extensive attention. Most characterizations or models of stochastic OD demands in networks assume a homogenous probability distribution, though empirical studies are lacking of large-scale networks to justify this assumption. Given that the long-term continuous automatic fare collection (AFC) data of metro networks can provide complete OD passenger demand information, this study takes the Shanghai metro network as an example to empirically examine the stochasticity characteristics of OD passenger demands of metro network. Based on the morning peak OD demand data for 250 weekdays, a local outlier factor (LOF) method is used to identify and remove outliers in the data. A clustering method is used to cluster the OD pairs, study the fluctuation and distribution characteristics of the OD passenger demands, and select the optimal distribution type through goodness-of-fit indices. The results show that 1) the coefficients of variation of morning peak OD demands in the network are mainly distributed in the range of 0.2–0.6, different OD pairs have different fluctuations, and the degree of demand fluctuation decreases as the mean increases; 2) the probability distribution types of OD demands based on statistical characteristics are heterogeneous; and 3) the optimal distribution type of OD demands is Poisson, lognormal/Gamma, and normal for OD pairs characterized by a small mean and right-skewness, a small mean and skewness close to 0, and a large mean, respectively. In contrast to the simple average-based data processing of OD passenger demand in metro networks, this paper presents a new perspective of mining long-term continuous data to understand the inherent stochasticity of OD passenger demands. The results can provide more realistic and practical inputs and assumptions for theoretical research on stochastic OD demands in metro networks.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 244-259"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140469448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vehicle carbon emission estimation for urban traffic based on sparse trajectory data 基于稀疏轨迹数据的城市交通车辆碳排放估算

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.01.010

Wanjing Ma, Yuhan Liu, Philip Kofi Alimo, Ling Wang

Sparse trajectory data with non-second-by-second sampling intervals are common. However, most carbon emission estimation models for vehicles require second-by-second inputs. Additionally, some models ignore the emission generation principle, and some have complicated inputs. To address these limitations, this study proposes a vehicle carbon emission estimation method for urban traffic, based on sparse trajectory data. First, a trajectory reconstruction method based on interpolation of acceleration distribution is proposed. The results showed that the reconstructed trajectory was close to the real trajectory, and the accuracy was 2%–17% higher than that of other methods. Second, a carbon emission estimation model that considers both the emission generation principle and feasibility is proposed. The model with a goodness-of-fit of 0.887 had the best performance compared to the other models. The emission estimation results of the reconstructed sparse trajectories showed that the precision improved significantly for data with different frequencies compared to that of other reconstruction methods, e.g., 9% higher at a 30 s sampling interval.

{"title":"Vehicle carbon emission estimation for urban traffic based on sparse trajectory data","authors":"Wanjing Ma, Yuhan Liu, Philip Kofi Alimo, Ling Wang","doi":"10.1016/j.ijtst.2024.01.010","DOIUrl":"10.1016/j.ijtst.2024.01.010","url":null,"abstract":"<div><div>Sparse trajectory data with non-second-by-second sampling intervals are common. However, most carbon emission estimation models for vehicles require second-by-second inputs. Additionally, some models ignore the emission generation principle, and some have complicated inputs. To address these limitations, this study proposes a vehicle carbon emission estimation method for urban traffic, based on sparse trajectory data. First, a trajectory reconstruction method based on interpolation of acceleration distribution is proposed. The results showed that the reconstructed trajectory was close to the real trajectory, and the accuracy was 2%–17% higher than that of other methods. Second, a carbon emission estimation model that considers both the emission generation principle and feasibility is proposed. The model with a goodness-of-fit of 0.887 had the best performance compared to the other models. The emission estimation results of the reconstructed sparse trajectories showed that the precision improved significantly for data with different frequencies compared to that of other reconstruction methods, e.g., 9% higher at a 30 s sampling interval.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 222-233"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139821478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis on the synergistic variation of soil freezing and pile foundation bearing capacity in permafrost regions 冻土地区土壤冻结与桩基承载力协同变化分析

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.01.004

Dezhong Yu , Yang Cao , Qianqian Zhao

The construction of bored piles in permafrost regions disturbs the thermal stability of frozen soil, leading to decreased early bearing capacity of the pile foundation. As the permafrost ground temperature influences the area, the pile-soil gradually undergoes refreezing, resulting in a continuous enhancement of the pile foundation's bearing capacity. To study the synergistic variation law of soil refreezing and bearing capacity of bridge pile foundation in permafrost regions, two test piles with a length of 15 m and a diameter of 1.2 m were poured based on the actual bridge engineering construction project in the permafrost region of Daxing’an mountains, China. An intelligent temperature monitoring system was set up inside and around the area of the test pile. Combined with the collected temperature data, the refreezing state of pile-soil was comprehensively judged. The self-balancing method was employed to assess the bearing capacity of pile foundation before and after refreezing, unveiling the variation patterns in friction resistance at different soil layers and pile-end resistance. On this basis, a finite element model was established to analyze the interaction between pile side friction and pile tip resistance at varying depths of frozen soil. The test and analysis results revealed that the permafrost temperature in the pile foundation area was −1.9 ℃. Following pile-soil refreezing, the ultimate bearing capacity of the pile foundation increased by 2 232 kN, and the growth rate was 42.9%. The friction resistance of each soil (rock) layer on the pile side increased, with the growth rate ranging from 15% to 75%.

{"title":"Analysis on the synergistic variation of soil freezing and pile foundation bearing capacity in permafrost regions","authors":"Dezhong Yu , Yang Cao , Qianqian Zhao","doi":"10.1016/j.ijtst.2024.01.004","DOIUrl":"10.1016/j.ijtst.2024.01.004","url":null,"abstract":"<div><div>The construction of bored piles in permafrost regions disturbs the thermal stability of frozen soil, leading to decreased early bearing capacity of the pile foundation. As the permafrost ground temperature influences the area, the pile-soil gradually undergoes refreezing, resulting in a continuous enhancement of the pile foundation's bearing capacity. To study the synergistic variation law of soil refreezing and bearing capacity of bridge pile foundation in permafrost regions, two test piles with a length of 15 m and a diameter of 1.2 m were poured based on the actual bridge engineering construction project in the permafrost region of Daxing’an mountains, China. An intelligent temperature monitoring system was set up inside and around the area of the test pile. Combined with the collected temperature data, the refreezing state of pile-soil was comprehensively judged. The self-balancing method was employed to assess the bearing capacity of pile foundation before and after refreezing, unveiling the variation patterns in friction resistance at different soil layers and pile-end resistance. On this basis, a finite element model was established to analyze the interaction between pile side friction and pile tip resistance at varying depths of frozen soil. The test and analysis results revealed that the permafrost temperature in the pile foundation area was −1.9 ℃. Following pile-soil refreezing, the ultimate bearing capacity of the pile foundation increased by 2 232 kN, and the growth rate was 42.9%. The friction resistance of each soil (rock) layer on the pile side increased, with the growth rate ranging from 15% to 75%.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 134-149"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139633250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The future of AI in transportation: challenges and opportunities?

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.09.005

Wei (David) Fan, Zhongyin Guo, Yanli Wang, Yanna Sun

引用次数: 0

Injury severity of drowsy drivers involved in single vehicle crashes: Accounting for temporal instability and unobserved heterogeneity 涉及单一车辆碰撞的疲劳驾驶员的伤害严重程度:考虑时间稳定性和未观察到的异质性

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2023.10.011

Nabeel Saleem Saad Al-Bdairi , Hamsa Zubaidi , Ihsan Obaid

Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues, despite its devastating impact on society in terms of human life lost and associated economic burdens. Therefore, this significant safety threat requires a thorough investigation. To address the temporal instability of factors contributing to crashes involving drowsy drivers, this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters. To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes, injury outcomes are categorized into three groups: serious, moderate, and no injuries. Using four years of crash data from the state of Washington between 2013 and 2016, a wide range of factors were examined, including driver characteristics, roadway conditions, crash characteristics, vehicle conditions, lighting conditions, and temporal factors. The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years. However, some factors exhibit stable effects, such as female drivers, sober drivers, and non-hit-and-run crashes. Based on the findings of this study, decision-makers, traffic engineers, and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes, enabling them to make informed recommendations for safety countermeasures.

与其他安全问题相比，疲劳驾驶在交通安全文献中受到的关注相对较少，尽管它在人命损失和相关经济负担方面对社会造成了毁灭性的影响。因此，这一重大安全威胁需要进行彻底调查。为了解决涉及疲劳驾驶的碰撞因素的时间不稳定性，本文将碰撞数据分为四个时间段，同时捕获随机参数均值和方差中未观察到的异质性。为了探索影响疲劳驾驶员在单车碰撞中受伤严重程度的决定因素，将伤害结果分为三组:严重、中度和无伤害。利用2013年至2016年华盛顿州四年的碰撞数据，研究了一系列因素，包括驾驶员特征、道路状况、碰撞特征、车辆状况、照明条件和时间因素。估计结果表明，就决定因素对损伤严重程度的影响而言，存在时间不稳定性。然而，一些因素表现出稳定的影响，如女性司机、清醒的司机、非肇事逃逸事故。根据这项研究的结果，决策者、交通工程师和交通管理部门可以获得有价值的知识和见解，了解导致昏昏欲睡相关碰撞的因素，使他们能够为安全对策提出明智的建议。

{"title":"Injury severity of drowsy drivers involved in single vehicle crashes: Accounting for temporal instability and unobserved heterogeneity","authors":"Nabeel Saleem Saad Al-Bdairi , Hamsa Zubaidi , Ihsan Obaid","doi":"10.1016/j.ijtst.2023.10.011","DOIUrl":"10.1016/j.ijtst.2023.10.011","url":null,"abstract":"<div><div>Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues, despite its devastating impact on society in terms of human life lost and associated economic burdens. Therefore, this significant safety threat requires a thorough investigation. To address the temporal instability of factors contributing to crashes involving drowsy drivers, this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters. To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes, injury outcomes are categorized into three groups: serious, moderate, and no injuries. Using four years of crash data from the state of Washington between 2013 and 2016, a wide range of factors were examined, including driver characteristics, roadway conditions, crash characteristics, vehicle conditions, lighting conditions, and temporal factors. The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years. However, some factors exhibit stable effects, such as female drivers, sober drivers, and non-hit-and-run crashes. Based on the findings of this study, decision-makers, traffic engineers, and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes, enabling them to make informed recommendations for safety countermeasures.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 87-99"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135515105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive models for road traffic sign: Retroreflectivity status, retroreflectivity coefficient, and lifespan 道路交通标志的预测模型：逆反射状态、逆反射系数和使用寿命

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.02.008

Roxan Saleh , Hasan Fleyeh

This study addresses the critical safety issue of declining retroreflectivity values of road traffic signs, which can lead to unsafe driving conditions, especially at night. The paper aims to predict the retroreflectivity coefficient values of these signs and to classify their status as acceptable or rejected (in need of replacement) using machine learning models. Moreover, logistic regression and survival analysis are used to predict the median lifespans of road traffic signs across various geographical locations, focusing on signs in Croatia and Sweden as case studies. The results indicate high accuracy in the predictive models, with classification accuracy at 94% and an R² value of 94% for regression analysis. A significant finding is that a considerable number of signs maintain acceptable retroreflectivity levels within their warranty period, suggesting the feasibility of extending maintenance checks and warranty periods to 15 years which is longer than the current standard of 10 years. Additionally, the study reveals notable variations in the median lifespans of signs based on color and location. Blue signs in Croatia and Sweden exhibit the longest median lifespans (28 to 35 years), whereas white signs in Sweden and red signs in Croatia show the shortest (16 and 10 years, respectively). The high accuracy of logistic regression models (72–90%) for lifespan prediction confirms the effectiveness of this approach. These findings provide valuable insights for road authorities regarding the maintenance and management of road traffic signs, enhancing road safety standards.

{"title":"Predictive models for road traffic sign: Retroreflectivity status, retroreflectivity coefficient, and lifespan","authors":"Roxan Saleh , Hasan Fleyeh","doi":"10.1016/j.ijtst.2024.02.008","DOIUrl":"10.1016/j.ijtst.2024.02.008","url":null,"abstract":"<div><div>This study addresses the critical safety issue of declining retroreflectivity values of road traffic signs, which can lead to unsafe driving conditions, especially at night. The paper aims to predict the retroreflectivity coefficient values of these signs and to classify their status as acceptable or rejected (in need of replacement) using machine learning models. Moreover, logistic regression and survival analysis are used to predict the median lifespans of road traffic signs across various geographical locations, focusing on signs in Croatia and Sweden as case studies. The results indicate high accuracy in the predictive models, with classification accuracy at 94% and an <em>R</em><sup>2</sup> value of 94% for regression analysis. A significant finding is that a considerable number of signs maintain acceptable retroreflectivity levels within their warranty period, suggesting the feasibility of extending maintenance checks and warranty periods to 15 years which is longer than the current standard of 10 years. Additionally, the study reveals notable variations in the median lifespans of signs based on color and location. Blue signs in Croatia and Sweden exhibit the longest median lifespans (28 to 35 years), whereas white signs in Sweden and red signs in Croatia show the shortest (16 and 10 years, respectively). The high accuracy of logistic regression models (72–90%) for lifespan prediction confirms the effectiveness of this approach. These findings provide valuable insights for road authorities regarding the maintenance and management of road traffic signs, enhancing road safety standards.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 276-291"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139820618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Temporal assessment of emission inventory model for Indian heavy commercial vehicle segment: A top-down approach 印度重型商用车辆排放清单模型的时间评估--一种自上而下的方法

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2024.01.005

Vikrant Bhalerao , Kirtesh Gadiya , Gopal Patil , Prakash Rao

Heavy commercial vehicles (HCVs) are pivotal to India's economy, but are also significant sources of air pollution. To address this issue, the Indian government implemented Bharat stage VI (BS-VI) emission standards in 2020. Research gap regarding realistic inputs for annual vehicle kilometres and survival rate of HCVs has been identified. The HCV sector is categorized into long-haul vehicles (32 t and above, with higher annual vehicle usage and survival rates) and pick-up and delivery HCV trucks (16–32 t, with relatively lower annual vehicle usage and survival rates). Based on the primary research by taking into account the inputs from various stakeholders regarding annual vehicle kilometres and survival rates subject to vehicle type and emission standards, an HCV emission inventory for India has been developed for regulated pollutants (NO_x, PM_2.5, and CO) till 2035. We assume no additional external technological or policy interventions, except the anticipated shift to Bharat stage VII (BS-VII) standards by 2027. Key findings reveal that the on-road HCV population is projected to marginally increase (6.5%) by 2035 compared to 2020. However, there is a notable 97% surge in goods transport tonnage by 2035, indicating more efficient commercial vehicle usage, especially in the heavier category (32 t and above). Crucially, annual emissions of NO_x, PM_2.5, and CO from the HCV segment are expected to peak in 2020, and decline significantly by 2035. Emissions are projected to decrease by 91.5% (NO_x), 96.6% (PM_2.5), and 97.6% (CO) compared to 2020 levels due to the introduction of BS-VI standards in 2020 and the anticipated adoption of BS-VII standards in 2027. This study is instrumental in defining base emission inventory till 2035 for any further policy evaluation for the HCV segment for reducing air pollution and enhancing environmental sustainability.

{"title":"Temporal assessment of emission inventory model for Indian heavy commercial vehicle segment: A top-down approach","authors":"Vikrant Bhalerao , Kirtesh Gadiya , Gopal Patil , Prakash Rao","doi":"10.1016/j.ijtst.2024.01.005","DOIUrl":"10.1016/j.ijtst.2024.01.005","url":null,"abstract":"<div><div>Heavy commercial vehicles (HCVs) are pivotal to India's economy, but are also significant sources of air pollution. To address this issue, the Indian government implemented Bharat stage VI (BS-VI) emission standards in 2020. Research gap regarding realistic inputs for annual vehicle kilometres and survival rate of HCVs has been identified. The HCV sector is categorized into long-haul vehicles (32 t and above, with higher annual vehicle usage and survival rates) and pick-up and delivery HCV trucks (16–32 t, with relatively lower annual vehicle usage and survival rates). Based on the primary research by taking into account the inputs from various stakeholders regarding annual vehicle kilometres and survival rates subject to vehicle type and emission standards, an HCV emission inventory for India has been developed for regulated pollutants (NO<sub><em>x</em></sub>, PM<sub>2.5</sub>, and CO) till 2035. We assume no additional external technological or policy interventions, except the anticipated shift to Bharat stage VII (BS-VII) standards by 2027. Key findings reveal that the on-road HCV population is projected to marginally increase (6.5%) by 2035 compared to 2020. However, there is a notable 97% surge in goods transport tonnage by 2035, indicating more efficient commercial vehicle usage, especially in the heavier category (32 t and above). Crucially, annual emissions of NO<sub><em>x</em></sub>, PM<sub>2.5</sub>, and CO from the HCV segment are expected to peak in 2020, and decline significantly by 2035. Emissions are projected to decrease by 91.5% (NO<sub><em>x</em></sub>), 96.6% (PM<sub>2.5</sub>), and 97.6% (CO) compared to 2020 levels due to the introduction of BS-VI standards in 2020 and the anticipated adoption of BS-VII standards in 2027. This study is instrumental in defining base emission inventory till 2035 for any further policy evaluation for the HCV segment for reducing air pollution and enhancing environmental sustainability.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 150-164"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140518816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Train rescheduling and platforming in large high-speed railway stations 大型高速铁路车站列车重新调度与站台

IF 4.3 Q2 TRANSPORTATION

International Journal of Transportation Science and Technology

Pub Date : 2024-12-01 DOI: 10.1016/j.ijtst.2023.11.001

Jing Teng , Jinke Gao , Pengling Wang , Siyuan Qu

To deal with train delays in large high-speed railway stations, a multi-objective mixed-integer nonlinear programming (MO-MINLP) optimization model was proposed. The model used the arrival time, departure time, track occupation, and route selection as the decision variables, and fully considered the station infrastructure layout, train operational requirements, and time standards as limiting factors. The optimization objectives were to minimize train delays and reduce track and to route adjustments. To realize the large-scale and rapid solution of the MO-MINLP model, this study proposed a rolling horizon optimization algorithm that used half an hour as a time interval and solved the rescheduling and platforming problem of each time interval step-by-step. In numerical experiments, 227 train movements under delay circumstances in Hangzhoudong station were optimized by using the proposed model and solution algorithm. The results show that the proposed MO-MINLP model could resolve route conflicts, compress unnecessary dwell times, and reduce train delays, and the solution algorithm could efficiently increase the computational speed. The maximum solution time for optimizing the 227 train movements is 15 min 24 s.

针对大型高铁车站列车延误问题，提出了一种多目标混合整数非线性规划优化模型。该模型以到达时间、出发时间、轨道占用、路线选择为决策变量，充分考虑车站基础设施布局、列车运行要求、时间标准等限制因素。优化目标是最小化列车延误，减少轨道和路线调整。为实现MO-MINLP模型的大规模快速求解，本研究提出了一种以“半小时”为时间间隔的滚动地平线优化算法，分步解决每个时间间隔的重调度与平台问题。在数值实验中，利用该模型和求解算法对杭州东站227列列车在延误情况下的运行进行了优化。结果表明，所提出的MO-MINLP模型能够有效地解决路线冲突，压缩不必要的停留时间，减少列车延误;该求解算法可以有效地提高计算速度。227次列车运行优化的最大求解时间为15分24秒。

{"title":"Train rescheduling and platforming in large high-speed railway stations","authors":"Jing Teng , Jinke Gao , Pengling Wang , Siyuan Qu","doi":"10.1016/j.ijtst.2023.11.001","DOIUrl":"10.1016/j.ijtst.2023.11.001","url":null,"abstract":"<div><div>To deal with train delays in large high-speed railway stations, a multi-objective mixed-integer nonlinear programming (MO-MINLP) optimization model was proposed. The model used the arrival time, departure time, track occupation, and route selection as the decision variables, and fully considered the station infrastructure layout, train operational requirements, and time standards as limiting factors. The optimization objectives were to minimize train delays and reduce track and to route adjustments. To realize the large-scale and rapid solution of the MO-MINLP model, this study proposed a rolling horizon optimization algorithm that used half an hour as a time interval and solved the rescheduling and platforming problem of each time interval step-by-step. In numerical experiments, 227 train movements under delay circumstances in Hangzhoudong station were optimized by using the proposed model and solution algorithm. The results show that the proposed MO-MINLP model could resolve route conflicts, compress unnecessary dwell times, and reduce train delays, and the solution algorithm could efficiently increase the computational speed. The maximum solution time for optimizing the 227 train movements is 15 min 24 s.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"16 ","pages":"Pages 100-118"},"PeriodicalIF":4.3,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135515660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0