Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively advanced.However,these methods have difficulty in covering p...Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively advanced.However,these methods have difficulty in covering private vehicles.Naturalistic driving studies have disadvantages of small sample size and high cost,one new driving behavior evaluation method using massive vehicle trajectory data is put forward.An automatic encoding machine is used to reduce the noise of raw data,and then driving dynamics and self-organizing mapping(SOM)classification are used to give thresholds or the judgement method of overspeed,rapid speed change,rapid turning and rapid lane changing.The proportion of different driving behaviors and typical dangerous driving behaviors is calculated,then the temporal and spatial distribution of drivers’driving behavior and the driving behavior characteristics on typical roads are analyzed.Driving behaviors on accident-prone road sections and normal road sections are compared.Results show that in Shenzhen,frequent lane changing and overspeed are the most common unsafe driving behaviors;16.1%drivers have relatively aggressive driving behavior;the proportion of dangerous driving behavior is higher outside the original economic special zone;dangerous driving behavior is highly correlated with traffic accident frequency.展开更多
Due to the widespread use of navigational satellites,the ubiquity of mobile phones,and the rapid advancement of mobile communication technologies,high-precision mobile phone signaling data(HMPSD)holds exceptional prom...Due to the widespread use of navigational satellites,the ubiquity of mobile phones,and the rapid advancement of mobile communication technologies,high-precision mobile phone signaling data(HMPSD)holds exceptional promise for discerning fine-grained characteristics of residents'travel behaviors,owing to its superior spatial and temporal resolution.This study focuses on identifying the most consistent commuting patterns of residents in the Qiaoxi District of Shijiazhuang,China,over the course of a month,using these patterns as the basis for transport mode identification.Leveraging the high-precise geographical coordinates of individuals'workplaces and homes,along with actual commuting durations derived from the high-frequency positioning of HMPSD,and comparing these with the predicted commuting durations for four transport modes from a navigational map,we have developed a novel approach for identifying individual transport modes,incorporating time matching,frequency ranking,and speed threshold assessments.This approach swiftly and effectively identifies the commuting modes for each resident—namely,driving,public transportation,walking,bicycling,and electric biking—along with their respective commuting distances and durations.Furthermore,to support urban planning and transportation management efforts,we aggregated individual commuting data—including flows,modes,distances,and durations—at a parcel level.This aggregation method effectively reveals favorable commuting characteristics within the central area of Qiaoxi District,highlights the commuting needs and irrational commuting conditions in peripheral parcels,and informs tailored strategies for adjusting planning layouts and optimizing facility configurations.This study facilitates an in-depth exploration of fine-grained travel patterns through integrated air-land transportation resources,providing new insights and methodologies for refined urban transportation planning and travel management through advanced data applications and identification methods.展开更多
The conventional dynamic approach for gravity filed modelling has been implemented in the PANDA(Position and Navigation Data Analyst) software. A variant of the so-called ’two-step’ method for gravity field modellin...The conventional dynamic approach for gravity filed modelling has been implemented in the PANDA(Position and Navigation Data Analyst) software. A variant of the so-called ’two-step’ method for gravity field modelling is adopted for this purpose, where the GRACE(Gravity Recovery and Climate Experiment)orbits are derived from the GPS(Global Positioning System) data in a first step followed by a simultaneous determination of dynamic orbit and gravity filed from the GPS-derived orbits and K-band rangerate measurements in a second step. In this way, the monthly gravity field solutions complete to degree and order 96 are produced for the period Jan. 2005 to Dec. 2010. Their performance is assessed by comparing them with the official solutions, i.e., CSR RL05, GFZ RL05 a and JPL RL05. A comparison in the spectral domain in terms of geoid heights reveals that the obtained solutions present the smallest degree amplitudes at degree 30-75. A further analysis of mass changes in the spatial domain demonstrates that the main signals observed from the obtained solutions are in great agreement with those from the official solutions. Remarkably, the correlation coefficients of mass changes in large river basins from the official solutions with respect to those from the obtained solutions are all above 0.97. These results demonstrate that the obtained solutions are comparable to the official solutions.展开更多
基金The National Natural Science Foundation of China(No.71641005)the National Key Research and Development Program of China(No.2018YFB1601105)
文摘Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively advanced.However,these methods have difficulty in covering private vehicles.Naturalistic driving studies have disadvantages of small sample size and high cost,one new driving behavior evaluation method using massive vehicle trajectory data is put forward.An automatic encoding machine is used to reduce the noise of raw data,and then driving dynamics and self-organizing mapping(SOM)classification are used to give thresholds or the judgement method of overspeed,rapid speed change,rapid turning and rapid lane changing.The proportion of different driving behaviors and typical dangerous driving behaviors is calculated,then the temporal and spatial distribution of drivers’driving behavior and the driving behavior characteristics on typical roads are analyzed.Driving behaviors on accident-prone road sections and normal road sections are compared.Results show that in Shenzhen,frequent lane changing and overspeed are the most common unsafe driving behaviors;16.1%drivers have relatively aggressive driving behavior;the proportion of dangerous driving behavior is higher outside the original economic special zone;dangerous driving behavior is highly correlated with traffic accident frequency.
基金supported by the Key Research Base of Philosophy and Social Sciences in Sichuan Province—Modern Design and Culture Research Center(Grant No.MD24C003)the National Natural Science Foundation of China(Grant No.52308084)+1 种基金China Postdoctoral Science Foundation(Grant No.2022M712877)Key R&D and Promotion Projects of Henan Province(Grant No.222102110125)。
文摘Due to the widespread use of navigational satellites,the ubiquity of mobile phones,and the rapid advancement of mobile communication technologies,high-precision mobile phone signaling data(HMPSD)holds exceptional promise for discerning fine-grained characteristics of residents'travel behaviors,owing to its superior spatial and temporal resolution.This study focuses on identifying the most consistent commuting patterns of residents in the Qiaoxi District of Shijiazhuang,China,over the course of a month,using these patterns as the basis for transport mode identification.Leveraging the high-precise geographical coordinates of individuals'workplaces and homes,along with actual commuting durations derived from the high-frequency positioning of HMPSD,and comparing these with the predicted commuting durations for four transport modes from a navigational map,we have developed a novel approach for identifying individual transport modes,incorporating time matching,frequency ranking,and speed threshold assessments.This approach swiftly and effectively identifies the commuting modes for each resident—namely,driving,public transportation,walking,bicycling,and electric biking—along with their respective commuting distances and durations.Furthermore,to support urban planning and transportation management efforts,we aggregated individual commuting data—including flows,modes,distances,and durations—at a parcel level.This aggregation method effectively reveals favorable commuting characteristics within the central area of Qiaoxi District,highlights the commuting needs and irrational commuting conditions in peripheral parcels,and informs tailored strategies for adjusting planning layouts and optimizing facility configurations.This study facilitates an in-depth exploration of fine-grained travel patterns through integrated air-land transportation resources,providing new insights and methodologies for refined urban transportation planning and travel management through advanced data applications and identification methods.
基金sponsored by the National "863 Program" of China (2014AA121501)the National Natural Science Foundation of China (41574030)sponsored by the Stichting Nationale Computer faciliteiten (National Computing Facilities Foundation, NCF) by providing the high-performance computing facilities
文摘The conventional dynamic approach for gravity filed modelling has been implemented in the PANDA(Position and Navigation Data Analyst) software. A variant of the so-called ’two-step’ method for gravity field modelling is adopted for this purpose, where the GRACE(Gravity Recovery and Climate Experiment)orbits are derived from the GPS(Global Positioning System) data in a first step followed by a simultaneous determination of dynamic orbit and gravity filed from the GPS-derived orbits and K-band rangerate measurements in a second step. In this way, the monthly gravity field solutions complete to degree and order 96 are produced for the period Jan. 2005 to Dec. 2010. Their performance is assessed by comparing them with the official solutions, i.e., CSR RL05, GFZ RL05 a and JPL RL05. A comparison in the spectral domain in terms of geoid heights reveals that the obtained solutions present the smallest degree amplitudes at degree 30-75. A further analysis of mass changes in the spatial domain demonstrates that the main signals observed from the obtained solutions are in great agreement with those from the official solutions. Remarkably, the correlation coefficients of mass changes in large river basins from the official solutions with respect to those from the obtained solutions are all above 0.97. These results demonstrate that the obtained solutions are comparable to the official solutions.
