By means of the relationship between speed and distance headway, this paperattempts to directly determine the road capacity based on a new concept. At first it makes acomprehensive analysis of distance headway, includ...By means of the relationship between speed and distance headway, this paperattempts to directly determine the road capacity based on a new concept. At first it makes acomprehensive analysis of distance headway, including safe distance headway and desired one. Theformer is decided by the demand for the degree of safety, and the latter depends on the motorists'behavior, i.e. the model of traffic flow. Both of them are functions of speed. According to thecharacteristics of their curves, we can find a crossing point that is the capacity of a roadsegment. This capacity represents the maximum flow rate meeting the minimum safety requirement.展开更多
A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approa...A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.展开更多
Many studies have been conducted by analyzing crash data that included road profile, site conditions, vehicle configurations and weights, driver behavior, etc.. However, limited studies have been conducted evaluating ...Many studies have been conducted by analyzing crash data that included road profile, site conditions, vehicle configurations and weights, driver behavior, etc.. However, limited studies have been conducted evaluating the impact of these factors on crashes and/or rollover through simulations. This is mainly due to lack of availability of verified full vehicle flexible-body models. The verification process is costly as it requires instrumentation of a heavy vehicle, scanning of road surfaces, and collection of data by running the vehicle over different road conditions, performing various maneuvering, etc. This paper presents the reverse engineering process of a class-8 truck and validation of a full flexible-body simulation model of a Wabash 53-foot trailer against the strain data recoded from proving ground testing of an instrumented truck. Simulation results show that, with the exception of the noise from the strain gage data from instrumented test run at 30 mph, there is a good agreement in periodicity and relative amplitude with the ADAMS model. A comparison of strain data from the flex-body model and the instrumented truck shows that the modeling and verification approach presented in this paper can be confidently used to validate the full flexible-body models developed for specific analyses.展开更多
Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider bot...Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory （GT） and linear regression analysis （LRA） is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle＇s speed at the lower road if the vehicle＇s speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the final result, thus calculating the vehicle＇s traveling time. The method also considers such factors as dwell time, thus making the prediction more accurate.展开更多
Objective： To analyze the crash and injury data in forensic medicine for years of 2004-2007. Methods： A sample of over 567 accident cases （9 pedestrians, 116 bicyclists, and 442 motor vehicle occupants） was consi...Objective： To analyze the crash and injury data in forensic medicine for years of 2004-2007. Methods： A sample of over 567 accident cases （9 pedestrians, 116 bicyclists, and 442 motor vehicle occupants） was considered from the Department of Forensic Medicine, Shahid Bahonar University of Kerman, involving drivers of all ages and covering a four-year period. Results： The male fatality rates were significantly higher than female ones. The groups at 15-30 years old and at 30-55 years old had the first and second highest numbers of deaths （40% and 34%, respectively）. There were substantial differences in distribution of injuries in motor vehicle occupants and pedestrians and bicyclists. Among motor vehicle occupants, there were more head injuries, such as skull fracture, brain contusion, subdural haemorrhage, and epidural haemorrhage. Nearly 77% of fatalities occurred during 08：00-22：00 in Sirjan. Internal bleeding was also higher in motor vehicle occupants. Pedestrians and bicyclists also had head injuries frequently. Conclusions： In spite of reduction of road traffic fatalities in Sirjan in 2007, it is still one of the cities with high road traffic fatality in the world. These results underline the importance of preventive strategies in transportation, suggesting that different methods are necessary to reduce fatalities of various traffic participants.展开更多
Rapid path planner plays an important role in autonomous ground vehicle （AGV） operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring ...Rapid path planner plays an important role in autonomous ground vehicle （AGV） operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree （RRT） can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and efficient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 mx 170 m area with moderate obstacle complexity.展开更多
文摘By means of the relationship between speed and distance headway, this paperattempts to directly determine the road capacity based on a new concept. At first it makes acomprehensive analysis of distance headway, including safe distance headway and desired one. Theformer is decided by the demand for the degree of safety, and the latter depends on the motorists'behavior, i.e. the model of traffic flow. Both of them are functions of speed. According to thecharacteristics of their curves, we can find a crossing point that is the capacity of a roadsegment. This capacity represents the maximum flow rate meeting the minimum safety requirement.
基金Project(90820302) supported by the National Natural Science Foundation of China
文摘A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.
文摘Many studies have been conducted by analyzing crash data that included road profile, site conditions, vehicle configurations and weights, driver behavior, etc.. However, limited studies have been conducted evaluating the impact of these factors on crashes and/or rollover through simulations. This is mainly due to lack of availability of verified full vehicle flexible-body models. The verification process is costly as it requires instrumentation of a heavy vehicle, scanning of road surfaces, and collection of data by running the vehicle over different road conditions, performing various maneuvering, etc. This paper presents the reverse engineering process of a class-8 truck and validation of a full flexible-body simulation model of a Wabash 53-foot trailer against the strain data recoded from proving ground testing of an instrumented truck. Simulation results show that, with the exception of the noise from the strain gage data from instrumented test run at 30 mph, there is a good agreement in periodicity and relative amplitude with the ADAMS model. A comparison of strain data from the flex-body model and the instrumented truck shows that the modeling and verification approach presented in this paper can be confidently used to validate the full flexible-body models developed for specific analyses.
基金the National Natural Science Foundation of China (No. 50575145)the National High Technology Research and Development Program (863) of China(Nos. 2006AA04Z432 and 2007AA04Z419)
文摘Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory （GT） and linear regression analysis （LRA） is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle＇s speed at the lower road if the vehicle＇s speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the final result, thus calculating the vehicle＇s traveling time. The method also considers such factors as dwell time, thus making the prediction more accurate.
文摘Objective： To analyze the crash and injury data in forensic medicine for years of 2004-2007. Methods： A sample of over 567 accident cases （9 pedestrians, 116 bicyclists, and 442 motor vehicle occupants） was considered from the Department of Forensic Medicine, Shahid Bahonar University of Kerman, involving drivers of all ages and covering a four-year period. Results： The male fatality rates were significantly higher than female ones. The groups at 15-30 years old and at 30-55 years old had the first and second highest numbers of deaths （40% and 34%, respectively）. There were substantial differences in distribution of injuries in motor vehicle occupants and pedestrians and bicyclists. Among motor vehicle occupants, there were more head injuries, such as skull fracture, brain contusion, subdural haemorrhage, and epidural haemorrhage. Nearly 77% of fatalities occurred during 08：00-22：00 in Sirjan. Internal bleeding was also higher in motor vehicle occupants. Pedestrians and bicyclists also had head injuries frequently. Conclusions： In spite of reduction of road traffic fatalities in Sirjan in 2007, it is still one of the cities with high road traffic fatality in the world. These results underline the importance of preventive strategies in transportation, suggesting that different methods are necessary to reduce fatalities of various traffic participants.
文摘Rapid path planner plays an important role in autonomous ground vehicle （AGV） operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree （RRT） can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and efficient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 mx 170 m area with moderate obstacle complexity.
