Pub Date : 2023-12-01Epub Date: 2022-03-23DOI: 10.1097/WNO.0000000000001527
Kristine M Nachbor, Olufemi E Adams, Chase A Liaboe, Anne S Abel
{"title":"Acute Bilateral Optic Neuropathy: A Rare Presentation of Wernicke Encephalopathy.","authors":"Kristine M Nachbor, Olufemi E Adams, Chase A Liaboe, Anne S Abel","doi":"10.1097/WNO.0000000000001527","DOIUrl":"10.1097/WNO.0000000000001527","url":null,"abstract":"","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"2662 1","pages":"e177-e179"},"PeriodicalIF":2.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75242523","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}
Pub Date : 2023-11-13DOI: 10.1177/03611981231207843
Qinghua Mao, Yang Li, Rongfu Yu
Conflict during an evacuation may turn into aggressive behavior and create problems for evacuation. To study the influence of attack behaviors such as pushing and shoving on evacuation and the evacuation law, an extended cellular automata model is developed in this paper. In the model, pedestrian movement is influenced by static, dynamic, and attack floor fields. In addition, pedestrian vision is influenced by the direction and location of movement of surrounding pedestrians, and pedestrians adopt different coping strategies for attacks: avoidance detour, or imitation. Attacker movement and aggressive behavior are also studied. Numerical simulations are conducted to discuss the pedestrian evacuation problem under attack behavior. The effects of the evacuation process, attack field sensitivity coefficient, location of fallen pedestrians, pedestrian density, number of initial attackers, initial attacker location, and pedestrian imitation ratio on evacuation time and number of fallen pedestrians are analyzed. The simulation results show that an appropriate increase in the impact of the attack field can slow down the congestion, that is, the evacuation time is the fastest at k A = 0.5. The evacuation time is faster when the room is full of normal pedestrians or full of attacking pedestrians. The number of casualty pairs is high when the initial position of the attacker is in the middle of the inner side of the room. The results of the study can provide recommendations and guidance for the formulation of evacuation strategies for pushing and shoving type attacks and reducing casualties.
疏散过程中的冲突可能会转变为攻击行为，给疏散带来麻烦。为了研究推、推等攻击行为对疏散的影响及疏散规律，本文建立了扩展元胞自动机模型。在模型中，行人的运动受到静态、动态和攻击地板场的影响。此外，行人的视觉受到周围行人运动方向和位置的影响，行人对攻击采取不同的应对策略:回避绕行或模仿。攻击者的运动和攻击行为也进行了研究。对攻击行为下的行人疏散问题进行了数值模拟。分析了疏散过程、攻击场敏感系数、倒下行人位置、行人密度、初始攻击者数量、初始攻击者位置、行人模仿比等因素对疏散时间和倒下行人数量的影响。仿真结果表明，适当增加攻击场的影响可以减缓拥塞，即在k A = 0.5时疏散时间最快。当房间里满是正常行人或满是攻击行人时，疏散时间更快。当攻击者的初始位置在房间内侧的中间时，伤亡人数会很高。研究结果可为推搡型袭击的疏散策略制定提供建议和指导，减少人员伤亡。
{"title":"Simulation Study of Pedestrians Evacuation Considering Aggressive Behavior","authors":"Qinghua Mao, Yang Li, Rongfu Yu","doi":"10.1177/03611981231207843","DOIUrl":"https://doi.org/10.1177/03611981231207843","url":null,"abstract":"Conflict during an evacuation may turn into aggressive behavior and create problems for evacuation. To study the influence of attack behaviors such as pushing and shoving on evacuation and the evacuation law, an extended cellular automata model is developed in this paper. In the model, pedestrian movement is influenced by static, dynamic, and attack floor fields. In addition, pedestrian vision is influenced by the direction and location of movement of surrounding pedestrians, and pedestrians adopt different coping strategies for attacks: avoidance detour, or imitation. Attacker movement and aggressive behavior are also studied. Numerical simulations are conducted to discuss the pedestrian evacuation problem under attack behavior. The effects of the evacuation process, attack field sensitivity coefficient, location of fallen pedestrians, pedestrian density, number of initial attackers, initial attacker location, and pedestrian imitation ratio on evacuation time and number of fallen pedestrians are analyzed. The simulation results show that an appropriate increase in the impact of the attack field can slow down the congestion, that is, the evacuation time is the fastest at k A = 0.5. The evacuation time is faster when the room is full of normal pedestrians or full of attacking pedestrians. The number of casualty pairs is high when the initial position of the attacker is in the middle of the inner side of the room. The results of the study can provide recommendations and guidance for the formulation of evacuation strategies for pushing and shoving type attacks and reducing casualties.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"132 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136351564","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}
Pub Date : 2023-11-13DOI: 10.1177/03611981231208903
Jiaqi Li, Xuesong Wang, Xiaohan Yang, Qi Zhang, Hanzhong Pan
Exploring and analyzing safety influencing factors can guide targeted traffic safety management. Traditional traffic safety models are aimed at specific data problems and making adjustments to the model structure, which lack focus on predictive ability and have limited information on the analysis of influencing factors. In recent years, machine-learning methods have opened new avenues in modeling that have higher prediction accuracy, can identify complex nonlinear relationships, and can overcome over- and under-dispersion and correlation. Machine-learning methods, however, pose the problem of limited interpretability. The interpretable machine-learning framework SHAP can be an effective solution, which can not only reflect the influence of features in each sample but also generate global interpretation. This study established gradient boosting models including the CatBoost and XGBoost models as traffic safety models, which were compared with a traditional NB regression model and a zero-inflated negative binomial regression model. SHAP was used to analyze several safety influencing factors, including geometric design features, traffic operation characteristics, time of day, and land use. Results confirmed that the CatBoost model has better prediction ability and is a more suitable traffic safety model than the traditional negative binomial regression model. Among the key findings were that ramp type is the most important factor in freeway crash frequency; curve presence has a great positive impact, while truck proportion has a great negative impact; and traffic volume is highly correlated with truck proportion. These findings can provide theoretical support for safety operation management and targeted improvement measures for freeways.
{"title":"Analyzing Freeway Safety Influencing Factors Using the CatBoost Model and Interpretable Machine-Learning Framework, SHAP","authors":"Jiaqi Li, Xuesong Wang, Xiaohan Yang, Qi Zhang, Hanzhong Pan","doi":"10.1177/03611981231208903","DOIUrl":"https://doi.org/10.1177/03611981231208903","url":null,"abstract":"Exploring and analyzing safety influencing factors can guide targeted traffic safety management. Traditional traffic safety models are aimed at specific data problems and making adjustments to the model structure, which lack focus on predictive ability and have limited information on the analysis of influencing factors. In recent years, machine-learning methods have opened new avenues in modeling that have higher prediction accuracy, can identify complex nonlinear relationships, and can overcome over- and under-dispersion and correlation. Machine-learning methods, however, pose the problem of limited interpretability. The interpretable machine-learning framework SHAP can be an effective solution, which can not only reflect the influence of features in each sample but also generate global interpretation. This study established gradient boosting models including the CatBoost and XGBoost models as traffic safety models, which were compared with a traditional NB regression model and a zero-inflated negative binomial regression model. SHAP was used to analyze several safety influencing factors, including geometric design features, traffic operation characteristics, time of day, and land use. Results confirmed that the CatBoost model has better prediction ability and is a more suitable traffic safety model than the traditional negative binomial regression model. Among the key findings were that ramp type is the most important factor in freeway crash frequency; curve presence has a great positive impact, while truck proportion has a great negative impact; and traffic volume is highly correlated with truck proportion. These findings can provide theoretical support for safety operation management and targeted improvement measures for freeways.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"134 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352099","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}
Pub Date : 2023-11-10DOI: 10.1177/03611981231190634
Max Gardner, Paul Waddell
Use of the multinomial logit (MNL) functional form is widespread in transportation and land use demand modeling. As the state-of-the-art evolves away from aggregate forecasting and toward activity-based models and microsimulation, MNL models are being asked to accommodate increasingly large choice sets. Different strategies exist to address the challenge of estimating models with very large choice sets, but perhaps none is as commonly employed as sampling of alternatives. The effect of sampling of alternatives on parameter estimation has received considerable attention in the scientific literature. Yet comparatively little quantitative research exists that examines the issues that arise when the same sampling strategies are applied in the context of forecasting. In this study we conducted an analysis of the effect of sampling of alternatives in discrete choice models for disaggregate location choice forecasting. First, a novel measure of forecast error was defined and then used to quantify the extent of the problem as a function of sample rate, model error, and size of the universe of alternatives. Finally, we explored the potential for strategic sampling techniques to reduce the error observed under simple random sampling. In general, we found that the proportion of aggregate demand that was misallocated owing to sampling of alternatives was actually reduced as the size of the universe of alternatives increased. Additionally, simple random sampling was shown to outperform importance sampling in most scenarios. These findings suggest that error resulting from random sampling of alternatives is less of a problem for logit-based microsimulation models than previously assumed.
{"title":"Numerical Analysis of Error From Sampling of Alternatives in Logit-Based Demand Forecasting Models with Massive Choice Sets","authors":"Max Gardner, Paul Waddell","doi":"10.1177/03611981231190634","DOIUrl":"https://doi.org/10.1177/03611981231190634","url":null,"abstract":"Use of the multinomial logit (MNL) functional form is widespread in transportation and land use demand modeling. As the state-of-the-art evolves away from aggregate forecasting and toward activity-based models and microsimulation, MNL models are being asked to accommodate increasingly large choice sets. Different strategies exist to address the challenge of estimating models with very large choice sets, but perhaps none is as commonly employed as sampling of alternatives. The effect of sampling of alternatives on parameter estimation has received considerable attention in the scientific literature. Yet comparatively little quantitative research exists that examines the issues that arise when the same sampling strategies are applied in the context of forecasting. In this study we conducted an analysis of the effect of sampling of alternatives in discrete choice models for disaggregate location choice forecasting. First, a novel measure of forecast error was defined and then used to quantify the extent of the problem as a function of sample rate, model error, and size of the universe of alternatives. Finally, we explored the potential for strategic sampling techniques to reduce the error observed under simple random sampling. In general, we found that the proportion of aggregate demand that was misallocated owing to sampling of alternatives was actually reduced as the size of the universe of alternatives increased. Additionally, simple random sampling was shown to outperform importance sampling in most scenarios. These findings suggest that error resulting from random sampling of alternatives is less of a problem for logit-based microsimulation models than previously assumed.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":" 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135141657","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231205886
Thor Dodson, Viktoriia Dunleavy
This article discusses the inequities in exposure to highway noise, which can have adverse effects on health, productivity, and quality of life. If certain subpopulations tend to live near highways because of structural inequality, gentrification, lack of social capital, or other reasons, then highway noise can contribute to inequity in a systematic way. The authors developed an online mapping application, the Noise Inequity Identification Tool (NIIT), to visualize the noise damage cost of noise pollution from road segments, the noise-equity ratios at the county level, and the population distribution of various demographics. The methodology combines estimates of roadway traffic noise levels with the cost of noise damage from the hedonic pricing literature and estimates of the number of households affected to estimate the noise damage cost for each road segment in the U.S. The cost of the noise damage accruing to each demographic is then aggregated over a larger region and normalized by their proportion of the population to calculate the “noise-equity ratio,” revealing substantial inequities in highway noise exposure between demographics at a variety of spatial scales. By using this tool, planners and practitioners can easily identify regions with existing highway noise exposure inequities and pinpoint roadways with excessive noise damage costs to recommend potential externality mitigation projects.
{"title":"Equity of Highway Noise Exposure","authors":"Thor Dodson, Viktoriia Dunleavy","doi":"10.1177/03611981231205886","DOIUrl":"https://doi.org/10.1177/03611981231205886","url":null,"abstract":"This article discusses the inequities in exposure to highway noise, which can have adverse effects on health, productivity, and quality of life. If certain subpopulations tend to live near highways because of structural inequality, gentrification, lack of social capital, or other reasons, then highway noise can contribute to inequity in a systematic way. The authors developed an online mapping application, the Noise Inequity Identification Tool (NIIT), to visualize the noise damage cost of noise pollution from road segments, the noise-equity ratios at the county level, and the population distribution of various demographics. The methodology combines estimates of roadway traffic noise levels with the cost of noise damage from the hedonic pricing literature and estimates of the number of households affected to estimate the noise damage cost for each road segment in the U.S. The cost of the noise damage accruing to each demographic is then aggregated over a larger region and normalized by their proportion of the population to calculate the “noise-equity ratio,” revealing substantial inequities in highway noise exposure between demographics at a variety of spatial scales. By using this tool, planners and practitioners can easily identify regions with existing highway noise exposure inequities and pinpoint roadways with excessive noise damage costs to recommend potential externality mitigation projects.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"103 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242820","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231205876
Ahmet Yildiz, Oktay Arikan, Kemal Keskin
This manuscript presents a speed trajectory optimization to minimize driving energy consumption using four different nature-inspired algorithms. For this purpose, a model was developed that can simulate motion of a single train. To test the train motion model and speed trajectories, Istanbul M3 subway line was modeled with its actual parameters such as gradient, curve, and speed limit. Concerning computational time and energy usage, a straightforward speed profile and proposed speed profiles by the algorithms have been compared. Afterwards, variable passenger numbers at each station in a certain hour were taken as dynamic mass input. With the marine predator algorithm (MPA) that finds the best result among the four, speed profile optimization was performed again under the effect of unstable mass. Finally, a train was operated by a driver according to the optimal speed profile. As a result, energy saving is 18.75% in simulation environment and 21.27% in real-life test.
{"title":"Energy-Efficient Train Operation Optimization in Istanbul Metro Network Considering Variable Passenger Numbers","authors":"Ahmet Yildiz, Oktay Arikan, Kemal Keskin","doi":"10.1177/03611981231205876","DOIUrl":"https://doi.org/10.1177/03611981231205876","url":null,"abstract":"This manuscript presents a speed trajectory optimization to minimize driving energy consumption using four different nature-inspired algorithms. For this purpose, a model was developed that can simulate motion of a single train. To test the train motion model and speed trajectories, Istanbul M3 subway line was modeled with its actual parameters such as gradient, curve, and speed limit. Concerning computational time and energy usage, a straightforward speed profile and proposed speed profiles by the algorithms have been compared. Afterwards, variable passenger numbers at each station in a certain hour were taken as dynamic mass input. With the marine predator algorithm (MPA) that finds the best result among the four, speed profile optimization was performed again under the effect of unstable mass. Finally, a train was operated by a driver according to the optimal speed profile. As a result, energy saving is 18.75% in simulation environment and 21.27% in real-life test.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"182 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242015","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231198480
Yang Song, Ang Li, Hongshuai Wang, Xiaofeng Xu, Xin Wang, Zuoming Xiao, Qiang Yuan
When shield tunneling is performed in water-rich silt and fine sand strata, the grout becomes runny when diluted by groundwater. After dilution, the filling effect of the grout is not significant, and the level of surface settlement is very high. In this study, based on bidding section 04 of Tianjin Metro Line 11, traditional grouting materials were selected to conduct response surface method (RSM) tests. The purposes of the RSM analysis were to analyze the interactions between materials and their influences on grout performance and to optimize the grout mix ratio. Various admixtures were compared to assess the effects of different admixtures and compositions on the dispersion resistance and flow performance of the grout. Finally, a shield synchronous grouting test system was developed, and a similar indoor grouting simulation test was performed to analyze the influences of the different admixtures on the filling effects and to determine a reasonable grout mix ratio. The following three results were obtained. (1) The RSM was suitable for grout performance prediction and grout mix ratio optimization, and hydroxyethyl cellulose could improve the grout performance and increase the bond performance between the cementing material and aggregate. (2) Admixture incorporation enhancement could improve the grout utilization rate and increase the diffusion distance at the top of the tunnel, which would be conducive to filling the gap at the tail end of the shield. (3) The optimal preparation scheme of grout in water-rich fine sand formations included a water–binder ratio of 0.72, cement–sand ratio of 0.80, fly ash content of 5%, bentonite content of 14.94%, and admixture content of 0.8%–0.9%
{"title":"Optimization of the Grout Mix Ratio and Simulation Test of Shield Tail Grouting Similarities in a Water-Rich Fine Sand Layer","authors":"Yang Song, Ang Li, Hongshuai Wang, Xiaofeng Xu, Xin Wang, Zuoming Xiao, Qiang Yuan","doi":"10.1177/03611981231198480","DOIUrl":"https://doi.org/10.1177/03611981231198480","url":null,"abstract":"When shield tunneling is performed in water-rich silt and fine sand strata, the grout becomes runny when diluted by groundwater. After dilution, the filling effect of the grout is not significant, and the level of surface settlement is very high. In this study, based on bidding section 04 of Tianjin Metro Line 11, traditional grouting materials were selected to conduct response surface method (RSM) tests. The purposes of the RSM analysis were to analyze the interactions between materials and their influences on grout performance and to optimize the grout mix ratio. Various admixtures were compared to assess the effects of different admixtures and compositions on the dispersion resistance and flow performance of the grout. Finally, a shield synchronous grouting test system was developed, and a similar indoor grouting simulation test was performed to analyze the influences of the different admixtures on the filling effects and to determine a reasonable grout mix ratio. The following three results were obtained. (1) The RSM was suitable for grout performance prediction and grout mix ratio optimization, and hydroxyethyl cellulose could improve the grout performance and increase the bond performance between the cementing material and aggregate. (2) Admixture incorporation enhancement could improve the grout utilization rate and increase the diffusion distance at the top of the tunnel, which would be conducive to filling the gap at the tail end of the shield. (3) The optimal preparation scheme of grout in water-rich fine sand formations included a water–binder ratio of 0.72, cement–sand ratio of 0.80, fly ash content of 5%, bentonite content of 14.94%, and admixture content of 0.8%–0.9%","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":" 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242041","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231203231
Daniel Castro-Fresno, Helena Miera-Dominguez, Pedro Lastra-González, Irune Indacoechea-Vega, Ronald van Loon, Gijsjan van Blokland
Road transportation is one of the major sources of noise emissions that seriously affect human health. The porous surfaces of roads are sound absorbing, which helps to reduce noise pollution. For this purpose, different two-layer porous asphalt mixtures were evaluated both mechanically and functionally, to develop an asphalt mixture that reduces the noise generated between tires and road. This research focused on the variables that determine the main properties to be considered: texture wavelength spectrum, acoustic absorption, and flow resistivity. Void content, thickness, and maximum aggregate size were identified as the variables that should be controlled to decrease noise emissions.
{"title":"Two-Layer Porous Asphalt: Main Properties to Decrease the Noise Emissions","authors":"Daniel Castro-Fresno, Helena Miera-Dominguez, Pedro Lastra-González, Irune Indacoechea-Vega, Ronald van Loon, Gijsjan van Blokland","doi":"10.1177/03611981231203231","DOIUrl":"https://doi.org/10.1177/03611981231203231","url":null,"abstract":"Road transportation is one of the major sources of noise emissions that seriously affect human health. The porous surfaces of roads are sound absorbing, which helps to reduce noise pollution. For this purpose, different two-layer porous asphalt mixtures were evaluated both mechanically and functionally, to develop an asphalt mixture that reduces the noise generated between tires and road. This research focused on the variables that determine the main properties to be considered: texture wavelength spectrum, acoustic absorption, and flow resistivity. Void content, thickness, and maximum aggregate size were identified as the variables that should be controlled to decrease noise emissions.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":" 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135242055","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231205882
Xiaotong Ding, John Maleyeff, Frans Valk
A business intelligence (BI) system was designed to create a proactive, reactive, and precursor decision tool to improve safety of bus operations at the Massachusetts Bay Transportation Authority (MBTA). The system’s development was motivated in part by recommendations of a safety inspection by the Federal Transportation Administration, and the realization that the MBTA has access to vest amounts of data that are not being used to create information effectively. The developers reduced the complexity of the BI system by incorporating analytics to determine the areas of focus where safety has the most impact. Challenges were posed by the need to integrate internal and external databases with various formats and structures, and the desire to create a self-service BI solution for multiple MBTA users. The resulting BI solution includes applications that support key performance indicator analyses, root cause investigations, and targeted improvement actions. These applications represent an enhanced approach that combines data for a more holistic analysis and eliminates the need to transfer datasets or data analyses by email. The system includes various forms of visualizations to help users navigate the myriad of information, including geospatial maps, interactive pie, line, and bar charts, and word frequency and relationship mapping. The paper details the system’s development and how analytical approaches were used to expose important information that is hidden in the data. Examples of applications are shown using screenshots and a general workflow is presented that could be applicable to agencies with fewer resources.
{"title":"Bus Operation Safety Business Intelligence Solution: Applying Analytics for Key Performance Indicator, Investigation, and Targeted Actions Analyses with a Centralized Data Warehouse","authors":"Xiaotong Ding, John Maleyeff, Frans Valk","doi":"10.1177/03611981231205882","DOIUrl":"https://doi.org/10.1177/03611981231205882","url":null,"abstract":"A business intelligence (BI) system was designed to create a proactive, reactive, and precursor decision tool to improve safety of bus operations at the Massachusetts Bay Transportation Authority (MBTA). The system’s development was motivated in part by recommendations of a safety inspection by the Federal Transportation Administration, and the realization that the MBTA has access to vest amounts of data that are not being used to create information effectively. The developers reduced the complexity of the BI system by incorporating analytics to determine the areas of focus where safety has the most impact. Challenges were posed by the need to integrate internal and external databases with various formats and structures, and the desire to create a self-service BI solution for multiple MBTA users. The resulting BI solution includes applications that support key performance indicator analyses, root cause investigations, and targeted improvement actions. These applications represent an enhanced approach that combines data for a more holistic analysis and eliminates the need to transfer datasets or data analyses by email. The system includes various forms of visualizations to help users navigate the myriad of information, including geospatial maps, interactive pie, line, and bar charts, and word frequency and relationship mapping. The paper details the system’s development and how analytical approaches were used to expose important information that is hidden in the data. Examples of applications are shown using screenshots and a general workflow is presented that could be applicable to agencies with fewer resources.","PeriodicalId":23279,"journal":{"name":"Transportation Research Record","volume":"172 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241844","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}
Pub Date : 2023-11-09DOI: 10.1177/03611981231206167
Clare Nelson, Gregory Rowangould
Examining substitutes to the current state and federal gasoline and diesel fuel excise taxes has become a pressing issue, exacerbated by the rise of high-efficiency and alternative-fuel vehicles threatening the revenue-generating capacity of these taxes. A mileage-based user fee has been frequently proposed in the literature as an alternative that would offer greater benefits to rural and low-income populations than to urban and higher-income populations. However, most prior analyses relied on small data sets and aggregated data. This study examined the impact of replacing the Vermont state fuels tax with a revenue-neutral, mileage-based user fee using mileage and fuel economy data for over 300,000 registered passenger vehicles. We found that, on average, Vermont households would pay an additional $23 per year, with rural households and low-income households facing smaller tax burdens than their urban and high-income counterparts. The impact of a $180 flat fee replacing the Vermont state motor fuels tax was also examined owing to state interest. Findings indicated that a flat fee would result in much larger price fluctuations, with most households paying an additional $47 per year. The disaggregated data approach presented here directly addresses public misconceptions of inequitable cost differences and provides context for public education campaigns to garner mileage-based user fee policy support. Based on our results, there is political ground for further research into the implementation of a mileage-based user fee, including the logistics of an administrative transition to mileage charging and the associated program implementation and technological costs.
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