Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883751
Fenglu Zhao, Ruishan Sun, Xiongbing Chen, Kai Zhang, Shunmei Han
In order to provide scientific advice for civil aviation safety management, this paper analyzes and forecasts the fluctuation rules of Chinese civil aviation incidents. For the said purpose, a research based on the time series of the monthly incidents per 10000 flight hours from 2006–2016 year was done by model of X–12 seasonal adjustment multiplication. And then the time series was decomposed into seasonal periodic components, trend components, and random components. On this basis, the Autoregressive Integrated Moving Average (ARIMA) model, the trend regression model and the mean value method were used to predict the sequence of each sequence respectively. The X–12 multiplication model was used to restore the fitting value and the prediction value of the frequency of the accident, and the actual data were used to verify the value. The results show that: the monthly incidents per 10000 flight hours from 2006–2016 year have obvious trends and seasonality. September and April each year are the most affected by the seasons, and December and January are the least affected by the seasons; in the long run, the 2006–2008 year trend is declining, the 2009–2016 year trend is fluctuating, and the other stages tend to be stable. The prediction results show that the accuracy is more reliable. In 2017, the highest monthly incidents per 10000 flight hours is in October and the second in June.
{"title":"Flight Incidents Prediction Based on Model of X-12 and ARIMA","authors":"Fenglu Zhao, Ruishan Sun, Xiongbing Chen, Kai Zhang, Shunmei Han","doi":"10.1109/ICTIS.2019.8883751","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883751","url":null,"abstract":"In order to provide scientific advice for civil aviation safety management, this paper analyzes and forecasts the fluctuation rules of Chinese civil aviation incidents. For the said purpose, a research based on the time series of the monthly incidents per 10000 flight hours from 2006–2016 year was done by model of X–12 seasonal adjustment multiplication. And then the time series was decomposed into seasonal periodic components, trend components, and random components. On this basis, the Autoregressive Integrated Moving Average (ARIMA) model, the trend regression model and the mean value method were used to predict the sequence of each sequence respectively. The X–12 multiplication model was used to restore the fitting value and the prediction value of the frequency of the accident, and the actual data were used to verify the value. The results show that: the monthly incidents per 10000 flight hours from 2006–2016 year have obvious trends and seasonality. September and April each year are the most affected by the seasons, and December and January are the least affected by the seasons; in the long run, the 2006–2008 year trend is declining, the 2009–2016 year trend is fluctuating, and the other stages tend to be stable. The prediction results show that the accuracy is more reliable. In 2017, the highest monthly incidents per 10000 flight hours is in October and the second in June.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132341908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883818
Jun-Jie Liu, Huijuan Yan, Meiye Cui
This research is aimed to study potential causal factors of pilot fatigue events and patterns of different consequences caused by theses events, and to put forward corresponding improvement measures. Firstly, taking 250 typical fatigue events collected from ASRS in 2012-2016 as samples, the Element Event Analysis Method (EEAM) is used to split the content of the reports, in this way, 5 fatigue causes, 6 contributory causes and 7 event consequences are obtained. Secondly, using ECCAIRS encoding rules to make fatigue reports encoding rules, which can encode the sample events information, then the effective actions based on different events encoding are taken. Taking a fatigue report from ASRS as an example, the empirical analysis results show that fatigue events can be effectively and quickly distinguished through classification analysis and scientific encoding of the acquired flight fatigue events, at the same time, corresponding control measures could be conceived and taken in an appropriate manner.
{"title":"Research on Information Analysis and Prevention Strategy of Flight Fatigue Events","authors":"Jun-Jie Liu, Huijuan Yan, Meiye Cui","doi":"10.1109/ICTIS.2019.8883818","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883818","url":null,"abstract":"This research is aimed to study potential causal factors of pilot fatigue events and patterns of different consequences caused by theses events, and to put forward corresponding improvement measures. Firstly, taking 250 typical fatigue events collected from ASRS in 2012-2016 as samples, the Element Event Analysis Method (EEAM) is used to split the content of the reports, in this way, 5 fatigue causes, 6 contributory causes and 7 event consequences are obtained. Secondly, using ECCAIRS encoding rules to make fatigue reports encoding rules, which can encode the sample events information, then the effective actions based on different events encoding are taken. Taking a fatigue report from ASRS as an example, the empirical analysis results show that fatigue events can be effectively and quickly distinguished through classification analysis and scientific encoding of the acquired flight fatigue events, at the same time, corresponding control measures could be conceived and taken in an appropriate manner.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114131283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883692
Huaizhong Zhu, Xiaoguang Yang, Yizhe Wang, N. Zhang
Accurate prediction of multimodal public transportation sharing rate is of great significance in coordinating traffic management, increasing public transport efficiency and allocating resources properly. The daily number of trips by subway, bus and ferry of pubic transport is calculated through data reduction and data mining, and the data of main factors affecting the fluctuation of public transportation sharing rate, i.e. holidays (or not), weather and air temperature, is collected in this paper based on big data on swiping public transportation IC cards in Shanghai. In addition, the sharing rates of subway, bus and ferry are predicted by using deep learning model based on historical data on daily number of trips and main influence factors, setting characteristic data and label data, and selecting activation function, loss function and gradient descent algorithm. The results show that the prediction error is less than 2.9%.
{"title":"The Prediction of Multimodal Public Transportation Sharing Rate Based on Data","authors":"Huaizhong Zhu, Xiaoguang Yang, Yizhe Wang, N. Zhang","doi":"10.1109/ICTIS.2019.8883692","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883692","url":null,"abstract":"Accurate prediction of multimodal public transportation sharing rate is of great significance in coordinating traffic management, increasing public transport efficiency and allocating resources properly. The daily number of trips by subway, bus and ferry of pubic transport is calculated through data reduction and data mining, and the data of main factors affecting the fluctuation of public transportation sharing rate, i.e. holidays (or not), weather and air temperature, is collected in this paper based on big data on swiping public transportation IC cards in Shanghai. In addition, the sharing rates of subway, bus and ferry are predicted by using deep learning model based on historical data on daily number of trips and main influence factors, setting characteristic data and label data, and selecting activation function, loss function and gradient descent algorithm. The results show that the prediction error is less than 2.9%.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114776273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883821
Mingjian Lu, Xin-ping Yan, Jian Wang, Yuwei Sun, Zikang Gong
Printed circuit heat exchanger (PCHE) is a new type of millimeter–level channel heat exchanger. The working fluid in the PCHE precooler of the supercritical carbon dioxide (SCO2) Brayton cycle usually works near or cross the pseudo-critical point, where the thermophysical properties exhibit drastic nonlinear characteristics. This brings challenges to analysis the thermal hydraulic performance of the PCHE. In present paper, a straight channel PCHE precooler model is established by the segment method to accurately account for the change of thermophysical properties. The precooler is designed by adopting the Gnielinski empirical correlations. Local heat transfer and pressure drop characteristics of SCO2 along the length are analyzed. The results show that the designed length obtained by segment method is significantly larger than by logarithmic mean temperature difference (LMTD) method. Overall the local temperature difference decreases from the hot end to the cold end. The heat transfer coefficient on SCO2 side is more relevant to the Prandtl number than the Reynolds number. The research results are of great significance for the development of PCHE design methods.
{"title":"Thermal Hydraulic Performance Analysis of PCHE Precooler for Supercritical CO2 Brayton Cycle","authors":"Mingjian Lu, Xin-ping Yan, Jian Wang, Yuwei Sun, Zikang Gong","doi":"10.1109/ICTIS.2019.8883821","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883821","url":null,"abstract":"Printed circuit heat exchanger (PCHE) is a new type of millimeter–level channel heat exchanger. The working fluid in the PCHE precooler of the supercritical carbon dioxide (SCO2) Brayton cycle usually works near or cross the pseudo-critical point, where the thermophysical properties exhibit drastic nonlinear characteristics. This brings challenges to analysis the thermal hydraulic performance of the PCHE. In present paper, a straight channel PCHE precooler model is established by the segment method to accurately account for the change of thermophysical properties. The precooler is designed by adopting the Gnielinski empirical correlations. Local heat transfer and pressure drop characteristics of SCO2 along the length are analyzed. The results show that the designed length obtained by segment method is significantly larger than by logarithmic mean temperature difference (LMTD) method. Overall the local temperature difference decreases from the hot end to the cold end. The heat transfer coefficient on SCO2 side is more relevant to the Prandtl number than the Reynolds number. The research results are of great significance for the development of PCHE design methods.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114453306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid development of ride-hailing services has sparked debate about their role in urban transport. While there are several studies exploring impacts of ride-hailing services on transportation systems, little work has been done to study mode choice transitions of ride-hailing users. This paper investigates ride-hailing use in November 2018 in Chengdu, China. We use survey results to depict usage characteristics of ride-hailing trips and users. A binary logit model is utilized to investigate factors influencing mode transitions because we suspect that the previous mode has an important effect on the future mode choice (when ride-hailing services is banned or heavily restricted). Ride-hailing services caters specially to younger and educated respondents. Although total shares of car-based modes (drive alone, taxi, get a ride with friends /family) does not show obvious changes, many respondents would shift away from taxi towards transit, bike, and driving alone. Besides, some respondents who used transit previously would be more likely to choose taxi. Our study could offer insights for relative regulations and policies.
{"title":"Usage Characteristics and Mode Choice Transitions of Ride-hailing Users in Chengdu, China","authors":"Guocong Zhai, Hongtai Yang, Renbin Pan, Jingying Wang, Yaohua Xiong","doi":"10.1109/ICTIS.2019.8883820","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883820","url":null,"abstract":"The rapid development of ride-hailing services has sparked debate about their role in urban transport. While there are several studies exploring impacts of ride-hailing services on transportation systems, little work has been done to study mode choice transitions of ride-hailing users. This paper investigates ride-hailing use in November 2018 in Chengdu, China. We use survey results to depict usage characteristics of ride-hailing trips and users. A binary logit model is utilized to investigate factors influencing mode transitions because we suspect that the previous mode has an important effect on the future mode choice (when ride-hailing services is banned or heavily restricted). Ride-hailing services caters specially to younger and educated respondents. Although total shares of car-based modes (drive alone, taxi, get a ride with friends /family) does not show obvious changes, many respondents would shift away from taxi towards transit, bike, and driving alone. Besides, some respondents who used transit previously would be more likely to choose taxi. Our study could offer insights for relative regulations and policies.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121755581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of e-commerce, more and more express packages need to be delivered. The Last-mile indoor task always takes most time of a whole delivery due to the complex and unfamiliar indoor environment. Generally, there aren’t enough existing indoor localization algorithms that are able to meet the business needs. To benefit the public, in this paper, an advanced low-cost and accurate intelligent localization and mapping algorithm is proposed. Three strengths, according to the experiment results, are concluded. First, the algorithm could run on Android devices, and it is able to save the cost of infrastructure as well as battery resources. Second, the algorithm can achieve an accuracy of less than 5cm, which is enough for general commercial purposes. Last, the system could intelligently shift the sensors between the Inertial Measurement Unit (IMU) sensors and the camera. To test our algorithm, we used the robot to execute the delivery of an indoor mailbox, obtaining a result of high accuracy (>95%) and low battery cost (saving more than 56%). Our algorithm is possible to be deployed in autonomous delivery vehicles or drones to provide last-mile delivery service.
{"title":"A Low-cost Simultaneous Localization And Mapping Algorithm For Last-mile Indoor Delivery","authors":"Wenming Wang, Wei Zhao, Xiaohan Wang, Zhihong Jin, Yuanchen Li, Troy Runge","doi":"10.1109/ICTIS.2019.8883749","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883749","url":null,"abstract":"With the development of e-commerce, more and more express packages need to be delivered. The Last-mile indoor task always takes most time of a whole delivery due to the complex and unfamiliar indoor environment. Generally, there aren’t enough existing indoor localization algorithms that are able to meet the business needs. To benefit the public, in this paper, an advanced low-cost and accurate intelligent localization and mapping algorithm is proposed. Three strengths, according to the experiment results, are concluded. First, the algorithm could run on Android devices, and it is able to save the cost of infrastructure as well as battery resources. Second, the algorithm can achieve an accuracy of less than 5cm, which is enough for general commercial purposes. Last, the system could intelligently shift the sensors between the Inertial Measurement Unit (IMU) sensors and the camera. To test our algorithm, we used the robot to execute the delivery of an indoor mailbox, obtaining a result of high accuracy (>95%) and low battery cost (saving more than 56%). Our algorithm is possible to be deployed in autonomous delivery vehicles or drones to provide last-mile delivery service.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122672684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unmanned surface vehicles (USVs) are becoming increasingly vital in a variety of maritime applications. The development of a real-time autonomous collision avoidance system is the pivotal issue in the study on USVs, in which the reliable collision risk detection and the adoption of a plausible collision avoidance maneuver play a key role. Existing studies on this subject seldom integrate the International Regulations for Preventing Collisions at Sea 1972 (COLREGS) guidelines. However, in order to ensure maritime safety, it is of fundamental importance that such a regulation should be obeyed at all times. In this paper, an approach of real-time collision avoidance has been presented with the compliance with the COLREGS rules been successfully integrated for USV. The approach has been designed in a way that through the judgment of the collision situation, the velocity and heading angle of the USV are changed to complete the collision avoidance of the obstacle. A strategy with reference obstacle is proposed to deal with the multiple moving obstacles situation. A number of simulations have been conducted in order to confirm the validity of the theoretic results obtained. The results show that the algorithms can sufficiently deal with complex traffic environments and that the generated practical path is suitable for USVs.
{"title":"Collision Avoidance for Unmanned Surface Vehicles based on COLREGS","authors":"Jiayuan Zhuang, Jing Luo, Yuanchang Liu, R. Bucknall, Hanbing Sun, Cheng Huang","doi":"10.1109/ICTIS.2019.8883829","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883829","url":null,"abstract":"Unmanned surface vehicles (USVs) are becoming increasingly vital in a variety of maritime applications. The development of a real-time autonomous collision avoidance system is the pivotal issue in the study on USVs, in which the reliable collision risk detection and the adoption of a plausible collision avoidance maneuver play a key role. Existing studies on this subject seldom integrate the International Regulations for Preventing Collisions at Sea 1972 (COLREGS) guidelines. However, in order to ensure maritime safety, it is of fundamental importance that such a regulation should be obeyed at all times. In this paper, an approach of real-time collision avoidance has been presented with the compliance with the COLREGS rules been successfully integrated for USV. The approach has been designed in a way that through the judgment of the collision situation, the velocity and heading angle of the USV are changed to complete the collision avoidance of the obstacle. A strategy with reference obstacle is proposed to deal with the multiple moving obstacles situation. A number of simulations have been conducted in order to confirm the validity of the theoretic results obtained. The results show that the algorithms can sufficiently deal with complex traffic environments and that the generated practical path is suitable for USVs.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126233114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883591
Jianfeng Hu, Feiqiang Liu, Ping Wang
For new automatic technology, an EEG-based approach for studying driver fatigue is one of the potential important research field in traffic safety. In this article, the proposed method based on EEG signals aimed to assess driver fatigue by using multi-entropy measures and compare the performance with channel combination and multiple classifiers. Given that EEG signals are unstable and non-linear, that using several common entropy evaluators to analyze EEG is more appropriate, including spectral entropy, approximate entropy, sample entropy and fuzzy entropy. In this paper, unlike other methods using whole electrodes and single classifier, the influence of channel combination on fatigue detection is discussed, and three types of common classifiers including Random Forest, Decision Tree and K-Nearest Neighbor are applied for classifying driver fatigue, implying that a comprehensive comparison is deeply discussed among them. A simulated driving experiment in this study for twenty-two healthy adults was used to perform continuous signal acquisition for about 20 minutes. The experimental results show that the proposed method can hit the highest accuracy for driver fatigue detection of 97.5% with the leave-one-out cross-validation approach, implying that it could be suitable for accessing driver fatigue by using four entropy measures based on O1 channel and RF classifier.
{"title":"EEG-Based Multiple Entropy Analysis for Assessing Driver Fatigue","authors":"Jianfeng Hu, Feiqiang Liu, Ping Wang","doi":"10.1109/ICTIS.2019.8883591","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883591","url":null,"abstract":"For new automatic technology, an EEG-based approach for studying driver fatigue is one of the potential important research field in traffic safety. In this article, the proposed method based on EEG signals aimed to assess driver fatigue by using multi-entropy measures and compare the performance with channel combination and multiple classifiers. Given that EEG signals are unstable and non-linear, that using several common entropy evaluators to analyze EEG is more appropriate, including spectral entropy, approximate entropy, sample entropy and fuzzy entropy. In this paper, unlike other methods using whole electrodes and single classifier, the influence of channel combination on fatigue detection is discussed, and three types of common classifiers including Random Forest, Decision Tree and K-Nearest Neighbor are applied for classifying driver fatigue, implying that a comprehensive comparison is deeply discussed among them. A simulated driving experiment in this study for twenty-two healthy adults was used to perform continuous signal acquisition for about 20 minutes. The experimental results show that the proposed method can hit the highest accuracy for driver fatigue detection of 97.5% with the leave-one-out cross-validation approach, implying that it could be suitable for accessing driver fatigue by using four entropy measures based on O1 channel and RF classifier.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126387910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883707
Huaizhong Zhu, Xiaoguang Yang, Yizhe Wang, N. Zhang
Car-following models are the core component of microscopic traffic simulation. Most of the deterministic models take fixed parameter values for different drivers. However, considerable behavioral differences exist between individual drivers. Simulating car-following behaviors of different drivers thus poses a challenge for microscopic traffic simulation. In this study, three approaches to calibrating car-following models for a group of heterogeneous drivers (calibrating an ‘average’ driver, calibrating at an individual-driver level, calibrating based on clustered drivers’ data) were tested with real-world driving data. Specifically, twenty randomly selected drivers’ car-following trajectories extracted from the Safety Pilot Model Deployment (SPMD) project were used to calibrate the intelligent driver model (IDM) with the abovementioned three calibration approaches. The errors of replicating drivers’ behavior in the validation datasets were used to evaluate the performances of the three calibration approaches.Results show that 1) calibrating at the individual level (i.e., each driver has its own model parameters) has the best performance in replicating a group of drivers’ car-following behavior; 2) calibrating an ‘average’ driver based on all drivers’ data performs worst; 3) calibrating at the cluster level achieves intermediate performance; and 4) simply averaging calibrated individual drivers’ parameters is not a good way to simulate a group of heterogeneous drivers’ car-following behavior. The results suggest that inter-driver heterogeneity in car-following should not be neglected in microscopic traffic simulation, and also that there is a need to develop archetypes of a variety of drivers to build a traffic mix in simulation.
{"title":"Simulating Car-following Behavior for Heteregeneous Drivers: the Need for Driver Specific Model Parameters","authors":"Huaizhong Zhu, Xiaoguang Yang, Yizhe Wang, N. Zhang","doi":"10.1109/ICTIS.2019.8883707","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883707","url":null,"abstract":"Car-following models are the core component of microscopic traffic simulation. Most of the deterministic models take fixed parameter values for different drivers. However, considerable behavioral differences exist between individual drivers. Simulating car-following behaviors of different drivers thus poses a challenge for microscopic traffic simulation. In this study, three approaches to calibrating car-following models for a group of heterogeneous drivers (calibrating an ‘average’ driver, calibrating at an individual-driver level, calibrating based on clustered drivers’ data) were tested with real-world driving data. Specifically, twenty randomly selected drivers’ car-following trajectories extracted from the Safety Pilot Model Deployment (SPMD) project were used to calibrate the intelligent driver model (IDM) with the abovementioned three calibration approaches. The errors of replicating drivers’ behavior in the validation datasets were used to evaluate the performances of the three calibration approaches.Results show that 1) calibrating at the individual level (i.e., each driver has its own model parameters) has the best performance in replicating a group of drivers’ car-following behavior; 2) calibrating an ‘average’ driver based on all drivers’ data performs worst; 3) calibrating at the cluster level achieves intermediate performance; and 4) simply averaging calibrated individual drivers’ parameters is not a good way to simulate a group of heterogeneous drivers’ car-following behavior. The results suggest that inter-driver heterogeneity in car-following should not be neglected in microscopic traffic simulation, and also that there is a need to develop archetypes of a variety of drivers to build a traffic mix in simulation.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125656242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/ICTIS.2019.8883796
Jingyu Zhang, Ling Sun
With global warming, melting Arctic sea ice and development of maritime technology are enabling the regular voyages in Arctic waters. Although, the Arctic maritime transport can save time and costs, the Arctic waters serve as a high-risk, environmentally fragile and sensitive ice area for ship navigation. The Arctic maritime transport faces the test of complex sea ice, geomagnetic disturbance, high winds and low visibility. In the face of the increase in shipping risks and their particularity, shipping insurance will play a critical role. Estimating of Arctic shipping insurance premiums has become the top point for insurance companies. For this, this paper uses the shipping cost accounting method to estimate the shipping costs of 5 ship types passing through the Arctic route and the traditional route to 10 different ports respectively. A reasonable interval for hull and cargo insurance premiums is estimated by the cost balance between the two routes. The reasonable number of the insurance premiums for the Arctic shipping calculated in this study can provide a reference for fulfilling of the Arctic shipping insurance.
{"title":"Estimation of shipping insurance premiums for Arctic routes","authors":"Jingyu Zhang, Ling Sun","doi":"10.1109/ICTIS.2019.8883796","DOIUrl":"https://doi.org/10.1109/ICTIS.2019.8883796","url":null,"abstract":"With global warming, melting Arctic sea ice and development of maritime technology are enabling the regular voyages in Arctic waters. Although, the Arctic maritime transport can save time and costs, the Arctic waters serve as a high-risk, environmentally fragile and sensitive ice area for ship navigation. The Arctic maritime transport faces the test of complex sea ice, geomagnetic disturbance, high winds and low visibility. In the face of the increase in shipping risks and their particularity, shipping insurance will play a critical role. Estimating of Arctic shipping insurance premiums has become the top point for insurance companies. For this, this paper uses the shipping cost accounting method to estimate the shipping costs of 5 ship types passing through the Arctic route and the traditional route to 10 different ports respectively. A reasonable interval for hull and cargo insurance premiums is estimated by the cost balance between the two routes. The reasonable number of the insurance premiums for the Arctic shipping calculated in this study can provide a reference for fulfilling of the Arctic shipping insurance.","PeriodicalId":325712,"journal":{"name":"2019 5th International Conference on Transportation Information and Safety (ICTIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125874460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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