Good driving skill parameter obtaining method based on critical areas

Abstract

The invention provides a good driving skill parameter obtaining method based on critical areas. The method includes the following steps of collecting physical data of a reference vehicle to form a data set D, scanning the accumulated oil consumption Ao in each array in the data set D, ranking the values of the accumulated oil consumption Ao in different arrays from low to high, marking each array according to the size of the value of accumulated oil consumption Ao, enabling the longitude and latitude range Z of the measured critical areas to be used for filtering the data set D to obtain a data set D' of the driving critical area, dividing the data set D' into n data pieces according to the different critical areas and different time period features, conducting parallel processing on the n data pieces through the Mapreduce parallel processing framework to obtain the good driving skill parameters of the certain critical area during the certain time period, and gathering the good driving skill parameters excavated by all the n data pieces. According to the method, real-time driving suggestions can be provided for a driver in the critical areas, the driving skill can be improved, the oil consumption can be reduced, and the comfortable degree can be improved.

Description

Technical field [0001] The invention relates to the field of intelligent traffic control, in particular to a method for obtaining good driving technical parameters based on key areas. Background technique [0002] Traffic problems are a common problem faced by all countries in the world. Various traffic problems have caused a huge waste of time, increased environmental pollution, and also caused huge economic losses. In order to alleviate the pressure on transportation caused by economic development and make full use of existing resources as much as possible, all countries have increased the research and construction of intelligent transportation systems. Among them, energy-saving driving technology can not only effectively avoid traffic accidents, ensure personal and property safety and reduce economic losses, but more importantly, it can effectively improve energy utilization and reduce environmental pollution in the form of increasingly depleted resources and increasing enviro...

AI Technical Summary

Problems solved by technology

[0006] It can be seen that there have been in-depth studies on vehicle driving modeling and evaluation, especially in the state of special road conditions or emergencies. The above research has analyzed the driving conditions of vehicles under different decisions and given evaluations one by one. However, in real life, vehicles are basically in a normal driving state, and fuel consumption and comfort are key indicators for evaluating vehicle driving skills. However, there are almost no studies on evaluation methods and mining of good driving technical parameters in this aspect in existing research. The path of a vehicle under normal driving conditions can be regarded as a combination of key areas with different characteristic road sections. The driving state of key areas has a more obvious impact on fuel consumption and comfort. However, existing studies only separately study vehicles under different special road conditions. The driving conditions, without linking them together to study as a whole

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