Abstract: A method for estimating road travel time based on the built environment and low-frequency floating car data belongs to the technical field of urban traffic management and traffic system evaluation. The method takes built environment as an explanatory variable of the road travel time. The interpretability of this variable is proved by a numerical example. In addition, the method determines distribution parameters of road travel time using the number distribution of vehicles instead of distance. The benefits of the method are that: (1) it explains the positive effect of built environment on road travel time; and (2) it reflects the speed difference among different road sections, which can improve the precision of estimating road travel time.

Abstract: The present invention relates to a method for estimating distribution of urban road travel time in considering operation state of taxi, and belongs to the technical field of urban transportation planning and management. The distributions of path travel time are respectively estimated according to different operation states of the taxi. When the distribution of the path travel time is estimated, adjacent road sections in the road network are not independent. In the present invention, the Markov model is added to describe the correlation of the travel time distribution between the adjacent road sections, so as to increase science and accuracy of the estimation result. In the present invention, the weight is set according to the proportion of the number of the vehicles under two different operation states to obtain the final distribution of the path travel time.

Abstract: The invention belongs to the research technology field of urban transportation planning and traffic big data, and provides a method to quantitatively analyze the impact of urban built environment on road travel time. Firstly, the average speed and the built environment attribute information of each small road section are extracted, based on the taxi GPS data and the spatial geographic information data on the research route. Then, taking the average speed of each small section as the dependent variable, the built environment attribute of the road section is used as the key independent variable, and the virtual variable of the nearest intersection type of the road section is used as the adjustment variable. The regression analysis is carried out with considering the interaction between the key independent variable and the adjustment variable, and the key independent variables which significantly affect the average speed of the road sections are selected from the obtained regression results.

Abstract: A method for estimating road travel time based on the built environment and low-frequency floating car data belongs to the technical field of urban traffic management and traffic system evaluation. This invention takes built environment as an explanatory variable of the road travel time. The interpretability of this variable is proved by a numerical example. In addition, this invention develops a method to determine distribution parameters of road travel time using the number distribution of vehicles instead of distance. The benefits of this invention are that: (1) it explains the positive effect of built environment on road travel time; (2) it reflects the speed difference among different road sections, which can improve the precision of estimating road travel time.

Abstract: The present invention relates to a method for estimating distribution of urban road travel time in considering operation state of taxi, and belongs to the technical field of urban transportation planning and management. The distributions of path travel time are respectively estimated according to different operation states of the taxi. When the distribution of the path travel time is estimated, adjacent road sections in the road network are not independent. In the present invention, the Markov model is added to describe the correlation of the travel time distribution between the adjacent road sections, so as to increase science and accuracy of the estimation result. In the present invention, the weight is set according to the proportion of the number of the vehicles under two different operation states to obtain the final distribution of the path travel time.