The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify t...The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify the vibration characteristics of this coupled system through field tests.To this end,dynamic performance tests were conducted on a vehicle–turnout coupled system in a medium–low-speed maglev test line.Firstly,the dynamic response data of the coupled system under various operating conditions were obtained.Then,the natural vibration characteristics of the turnout were analysed using the free attenuation method and the finite element method,indicating a good agreement between the simulation results and the measured results;the acceleration response characteristics of the coupled system were analysed in detail,and the ride quality of the vehicle was assessed by Sperling index.Finally,the frequency distribution characteristics of the coupled system were discussed.All these test results could provide references for model validation and optimized design of medium–low-speed maglev transport systems.展开更多
This paper presents an in-vehicle stereo vision system as a solution to accidents involving large good vehicle due to blind spots using Nigeria as a case study. In this paper, a stereo-vision system was attached to th...This paper presents an in-vehicle stereo vision system as a solution to accidents involving large good vehicle due to blind spots using Nigeria as a case study. In this paper, a stereo-vision system was attached to the front of Large Good Vehicles (LGVs) with a view to presenting live feeds of vehicles close to the LGV vehicles and their distance away. The captured road images using the stereo vision system were optimized for effectiveness and optimal vehicle maneuvering using a modified metaheuristics algorithm called the simulated annealing Ant Colony Optimization (saACO) algorithm. The concept of simulated annealing is strategies used to automatically select the control parameters of the ACO algorithm. This helps to stabilize the performance of the ACO algorithm irrespective of the quality of the lane images captured in the in-vehicle vision system. The system is capable of notifying drivers through lane detection techniques of blind spots. This technique enables the driver to be more aware of what surrounds the vehicle and make decisions early. In order to test the system, the stereo-vision device was mounted on a Large good vehicle, driven in Zaria (a city in Kaduna state in Nigeria), and data were in the record. Out of 180 events, 42.22% of potential accident events were caused by Passenger Cars, while 27.22%, 18.33% and 12.22% were caused by two-wheelers, Large Good Vehicles and road users, respectively. In the same vein, the in-vehicle lane detection system shows a good performance of the saACO-based lane detection system and gives a better performance in comparison with the standard ACO method.展开更多
An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement syst...An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system （PEMS） under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics （speed and acceleration） of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.展开更多
In an earlier paper （Tien 2015）, the author defmed the concept of a servgood, which can be thought of as a physical good or product enveloped by a services-oriented layer that makes the good smarter or more adaptabl...In an earlier paper （Tien 2015）, the author defmed the concept of a servgood, which can be thought of as a physical good or product enveloped by a services-oriented layer that makes the good smarter or more adaptable and customizable for a particular use. Adding another layer of physical sensors could then enhance its smartness and intelligence, especially if it were to be connected with each other or with other servgoods through the Internet of Things. Such sensed servgoods are becoming the products of the future. Indeed, autonomous vehicles can be considered the exemplar servgoods of the future; it is about decision informatics and embraces the advanced technologies of sensing （i.e., Big Data）, processing （i.e., real-time analytics）, reacting （i.e., real-time decision-making）, and learning （i.e., deep learning）. Since autonomous vehicles constitute a huge quality-of-life disruption, it is also critical to consider its policy impact on privacy and security, regulations and standards, and liability and insurance. Finally, just as the Soviet Union inaugurated the space age on October 4, 1957, with the launch of Sputnik, the first man-made object to orbit the Earth, the U. S. has inaugurated an age of automata or autonomous vehicles that can be considered to be the U. S. Sputnik of servgoods, with the full support of the U. S. government, the U. S. auto industry, the U. S. electronic industry, and the U.S. higher educational enterprise.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.51875483)the Independently Funded Research Project of State Key Laboratory of Traction Power(Grant Nos.2020TPL-T01 and 2020TPL-T04).
文摘The steel turnout is one of the key components in the medium–low-speed maglev line system.However,the vehicle under active control is prone to vehicle–turnout coupled vibration,and thus,it is necessary to identify the vibration characteristics of this coupled system through field tests.To this end,dynamic performance tests were conducted on a vehicle–turnout coupled system in a medium–low-speed maglev test line.Firstly,the dynamic response data of the coupled system under various operating conditions were obtained.Then,the natural vibration characteristics of the turnout were analysed using the free attenuation method and the finite element method,indicating a good agreement between the simulation results and the measured results;the acceleration response characteristics of the coupled system were analysed in detail,and the ride quality of the vehicle was assessed by Sperling index.Finally,the frequency distribution characteristics of the coupled system were discussed.All these test results could provide references for model validation and optimized design of medium–low-speed maglev transport systems.
文摘This paper presents an in-vehicle stereo vision system as a solution to accidents involving large good vehicle due to blind spots using Nigeria as a case study. In this paper, a stereo-vision system was attached to the front of Large Good Vehicles (LGVs) with a view to presenting live feeds of vehicles close to the LGV vehicles and their distance away. The captured road images using the stereo vision system were optimized for effectiveness and optimal vehicle maneuvering using a modified metaheuristics algorithm called the simulated annealing Ant Colony Optimization (saACO) algorithm. The concept of simulated annealing is strategies used to automatically select the control parameters of the ACO algorithm. This helps to stabilize the performance of the ACO algorithm irrespective of the quality of the lane images captured in the in-vehicle vision system. The system is capable of notifying drivers through lane detection techniques of blind spots. This technique enables the driver to be more aware of what surrounds the vehicle and make decisions early. In order to test the system, the stereo-vision device was mounted on a Large good vehicle, driven in Zaria (a city in Kaduna state in Nigeria), and data were in the record. Out of 180 events, 42.22% of potential accident events were caused by Passenger Cars, while 27.22%, 18.33% and 12.22% were caused by two-wheelers, Large Good Vehicles and road users, respectively. In the same vein, the in-vehicle lane detection system shows a good performance of the saACO-based lane detection system and gives a better performance in comparison with the standard ACO method.
基金supported by the State Environmental Protection Department of Public Welfare Projects(201409013)the National Natural Science Foundation of China(No.51576016 and No.41275133)
文摘An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system （PEMS） under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics （speed and acceleration） of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.
文摘In an earlier paper （Tien 2015）, the author defmed the concept of a servgood, which can be thought of as a physical good or product enveloped by a services-oriented layer that makes the good smarter or more adaptable and customizable for a particular use. Adding another layer of physical sensors could then enhance its smartness and intelligence, especially if it were to be connected with each other or with other servgoods through the Internet of Things. Such sensed servgoods are becoming the products of the future. Indeed, autonomous vehicles can be considered the exemplar servgoods of the future; it is about decision informatics and embraces the advanced technologies of sensing （i.e., Big Data）, processing （i.e., real-time analytics）, reacting （i.e., real-time decision-making）, and learning （i.e., deep learning）. Since autonomous vehicles constitute a huge quality-of-life disruption, it is also critical to consider its policy impact on privacy and security, regulations and standards, and liability and insurance. Finally, just as the Soviet Union inaugurated the space age on October 4, 1957, with the launch of Sputnik, the first man-made object to orbit the Earth, the U. S. has inaugurated an age of automata or autonomous vehicles that can be considered to be the U. S. Sputnik of servgoods, with the full support of the U. S. government, the U. S. auto industry, the U. S. electronic industry, and the U.S. higher educational enterprise.
