Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two gr...Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two groups is critical for developing targeted safety interventions.Considering that the zero-truncated characteristic of the data is uncertain,the results of the zero-truncated negative binomial models and traditional negative binomial models are calculated to seek the better model.The result revealed that the road surface conditions and vertical and horizontal curvature have greater influence on both pedestrian and driver compared to number of lanes and speed limit.And speed limits were more pronounced for pedestrian crash frequency than driver group.Conversely,the effect of different types of intersections was stronger for driver crash frequency.The differential influences of road physical design attributes on traffic crash frequencies for pedestrians versus drivers highlight the importance of adopting a user-centric approach to transportation safety planning and infrastructure design.Tailoring interventions to address the unique needs and vulnerabilities of different road user groups can lead to more effective safety improvements and better overall traffic safety outcomes.展开更多
Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization mode...Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.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
基金Projects(52102407,52472354)supported by the National Natural Science Foundation of China。
文摘Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two groups is critical for developing targeted safety interventions.Considering that the zero-truncated characteristic of the data is uncertain,the results of the zero-truncated negative binomial models and traditional negative binomial models are calculated to seek the better model.The result revealed that the road surface conditions and vertical and horizontal curvature have greater influence on both pedestrian and driver compared to number of lanes and speed limit.And speed limits were more pronounced for pedestrian crash frequency than driver group.Conversely,the effect of different types of intersections was stronger for driver crash frequency.The differential influences of road physical design attributes on traffic crash frequencies for pedestrians versus drivers highlight the importance of adopting a user-centric approach to transportation safety planning and infrastructure design.Tailoring interventions to address the unique needs and vulnerabilities of different road user groups can lead to more effective safety improvements and better overall traffic safety outcomes.
基金Project(2009AA11Z220)supported by National High Technology Research and Development Program of ChinaProjects(61070112,61070116)supported by the National Natural Science Foundation of China+1 种基金Project(2012LLYJTJSJ077)supported by the Ministry of Public Security of ChinaProject(KYQD14003)supported by Tianjin University of Technology and Education,China
文摘Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.
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.
