The phenomenon of car-following is special in traffic operations. Traditional car-following models can well describe the reactions of the movements between two concessive vehicles in the same lane within a certain dis...The phenomenon of car-following is special in traffic operations. Traditional car-following models can well describe the reactions of the movements between two concessive vehicles in the same lane within a certain distance. With the invention of connected vehicle technologies, more and more advisory messages are in development and applied in our daily lives, some of which are related to the measures and warnings of speed and headway distance between the two concessive vehicles. Such warnings may change the conventional car-following mechanisms. This paper intends to consider the possible impacts of in-vehicle warning messages to improve the traditional car-following models, including the General Motor (GM) Model and the Linear (Helly) Model, by calibrating model parameters using field data from an arterial road in Houston, Texas, U.S.A. The safety messages were provided by a tablet/smartphone application. One exponent was applied to the GM model, while another one applied to the Linear (Helly) model, both were on the stimuli term “difference in velocity between two concessive vehicles”. The calibration and validation were separately conducted for deceleration and acceleration conditions. Results showed that, the parameters of the traditional GM model failed to be properly calibrated with the interference of in-vehicle safety messages, and the parameters calibrated from the traditional Linear (Helly) Model with no in-vehicle messages could not be directly used in the case with such messages. However, both updated models can be well calibrated even if those messages were provided. The entire research process, as well as the calibrated models and parameters could be a reference in the on-going connected vehicle program and micro/macroscopic traffic simulations.展开更多
Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning are...Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning areas, transition areas, and activity areas of work zone, than the termination areas, where drivers might play less attention to safety threats. In this study, the vehicle-to-vehicle communication based left turn warning system was applied at a work zone termination area, which is immediately followed by a T-intersection. The work-zone is located on the minor road side, while left turn vehicles will be appearing from the major street through the said T-intersection. A smart phone application was designed using Android coding system to provide several types of warning messages to drivers. Corresponding scenarios were designed in a driving simulator, and 20 subjects were recruited to participate in the simulation test followed by a questionnaire survey. The subjects received a warning message when driving to the termination area of a work zone on the coming left turn vehicles. Twenty test drivers’ driving speed, acceleration rates, and break reaction distance to the warning messages were studied in four different scenarios. Results show that the smartphone application has a great impact on driving behaviors, especially the female voice and the beep tone warning, which are recommended for possible field tests. Besides, the developed smartphone applications can be further updated for practical applications of similar needs.展开更多
In the operational forecasting of tropical cyclones(TCs),decoding TC warning messages from global centers,along with extracting,organizing,and storing useful track observations and forecasts,are fundamental tasks.The ...In the operational forecasting of tropical cyclones(TCs),decoding TC warning messages from global centers,along with extracting,organizing,and storing useful track observations and forecasts,are fundamental tasks.The technical core lies in accurately identifying distinct TC individuals through automated programming methods.Based on the statistical characteristics of historical distances between TC individuals,this study designs a novel method for automatic identification of TC individuals and establishes a database of TC track observations and forecasts by integrating the persistent features from various elements in TC warning messages.This method accurately identifies each TC individual and assigns it a unique database number through a two-step process:initially,through the'Same Center same Number Comparison(SCNC)'identi-fication method,followed by the'Spatio-Temeporal Distance Comparison(STDC)'identification method.On this basis,we obtain a well-organized and comprehensive dataset that covers entire TC life time.Over the past decade,the operational practice has demonstrated that this method is accurate and efficient,providing solid data support for the TC forecasting operation,the assessment of TC forecasting accuracy,the compilation of TC yearbook,and TC-related research.展开更多
Knowledge regarding how people obtain,understand,and use warning information is critical to saving lives and protecting property,yet scientifically valid and reliable research to support this part of the tropical cycl...Knowledge regarding how people obtain,understand,and use warning information is critical to saving lives and protecting property,yet scientifically valid and reliable research to support this part of the tropical cyclone(TC)warning process has been limited.This is due in part to misconceptions about the social sciences and the theories,knowledge and methodologies they offer.To help fill this gap,we highlight some topics and issues where social science research offers valuable contributions to the TC forecast and warning process,and present findings from some recent TC-related research projects.A range of studies(albeit limited in number)includes social science research on how individuals interpret risk,the importance and impact of delivering clear messages,the communication of uncertainty;and,more specifically,on the TC forecast and warning process,including the effective communicating of storm surge risk.We also discuss some findings related to promoting appropriate protective actions,and understanding economic and societal impacts.We conclude by identifying some shortcomings in empirical research in this area,and offer recommendations for improved integration of social sciences into the TC forecast and warning process.展开更多
文摘The phenomenon of car-following is special in traffic operations. Traditional car-following models can well describe the reactions of the movements between two concessive vehicles in the same lane within a certain distance. With the invention of connected vehicle technologies, more and more advisory messages are in development and applied in our daily lives, some of which are related to the measures and warnings of speed and headway distance between the two concessive vehicles. Such warnings may change the conventional car-following mechanisms. This paper intends to consider the possible impacts of in-vehicle warning messages to improve the traditional car-following models, including the General Motor (GM) Model and the Linear (Helly) Model, by calibrating model parameters using field data from an arterial road in Houston, Texas, U.S.A. The safety messages were provided by a tablet/smartphone application. One exponent was applied to the GM model, while another one applied to the Linear (Helly) model, both were on the stimuli term “difference in velocity between two concessive vehicles”. The calibration and validation were separately conducted for deceleration and acceleration conditions. Results showed that, the parameters of the traditional GM model failed to be properly calibrated with the interference of in-vehicle safety messages, and the parameters calibrated from the traditional Linear (Helly) Model with no in-vehicle messages could not be directly used in the case with such messages. However, both updated models can be well calibrated even if those messages were provided. The entire research process, as well as the calibrated models and parameters could be a reference in the on-going connected vehicle program and micro/macroscopic traffic simulations.
文摘Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning areas, transition areas, and activity areas of work zone, than the termination areas, where drivers might play less attention to safety threats. In this study, the vehicle-to-vehicle communication based left turn warning system was applied at a work zone termination area, which is immediately followed by a T-intersection. The work-zone is located on the minor road side, while left turn vehicles will be appearing from the major street through the said T-intersection. A smart phone application was designed using Android coding system to provide several types of warning messages to drivers. Corresponding scenarios were designed in a driving simulator, and 20 subjects were recruited to participate in the simulation test followed by a questionnaire survey. The subjects received a warning message when driving to the termination area of a work zone on the coming left turn vehicles. Twenty test drivers’ driving speed, acceleration rates, and break reaction distance to the warning messages were studied in four different scenarios. Results show that the smartphone application has a great impact on driving behaviors, especially the female voice and the beep tone warning, which are recommended for possible field tests. Besides, the developed smartphone applications can be further updated for practical applications of similar needs.
基金support of the Innovation and Development Special Program of the China Meteorological Administration(CXFZ2024J006)Shanghai Science and Technology Commission Project(23DZ1204701)+1 种基金the National Key Research and Development Program of China(2021YFC3000805)the Typhoon Scientific and Technological Innovation Group of the China Meteorological Administration(CMA2023ZD06).
文摘In the operational forecasting of tropical cyclones(TCs),decoding TC warning messages from global centers,along with extracting,organizing,and storing useful track observations and forecasts,are fundamental tasks.The technical core lies in accurately identifying distinct TC individuals through automated programming methods.Based on the statistical characteristics of historical distances between TC individuals,this study designs a novel method for automatic identification of TC individuals and establishes a database of TC track observations and forecasts by integrating the persistent features from various elements in TC warning messages.This method accurately identifies each TC individual and assigns it a unique database number through a two-step process:initially,through the'Same Center same Number Comparison(SCNC)'identi-fication method,followed by the'Spatio-Temeporal Distance Comparison(STDC)'identification method.On this basis,we obtain a well-organized and comprehensive dataset that covers entire TC life time.Over the past decade,the operational practice has demonstrated that this method is accurate and efficient,providing solid data support for the TC forecasting operation,the assessment of TC forecasting accuracy,the compilation of TC yearbook,and TC-related research.
文摘Knowledge regarding how people obtain,understand,and use warning information is critical to saving lives and protecting property,yet scientifically valid and reliable research to support this part of the tropical cyclone(TC)warning process has been limited.This is due in part to misconceptions about the social sciences and the theories,knowledge and methodologies they offer.To help fill this gap,we highlight some topics and issues where social science research offers valuable contributions to the TC forecast and warning process,and present findings from some recent TC-related research projects.A range of studies(albeit limited in number)includes social science research on how individuals interpret risk,the importance and impact of delivering clear messages,the communication of uncertainty;and,more specifically,on the TC forecast and warning process,including the effective communicating of storm surge risk.We also discuss some findings related to promoting appropriate protective actions,and understanding economic and societal impacts.We conclude by identifying some shortcomings in empirical research in this area,and offer recommendations for improved integration of social sciences into the TC forecast and warning process.
