Dynamic feedback control method of bus priority based on v2x

Abstract

The invention relates to the technical field of intelligent transportation, and the scheme is a V2X-based bus priority dynamic feedback control method. The method includes a travel time prediction based on Kalman filtering, a bus priority preliminary guidance scheme and a dynamic feedback control module; the V2X-based bus The priority dynamic feedback control method is based on the actual operation state of the bus at the intersection and the existing interference, and is based on the real-time nature of V2X communication; this method has good redundancy and anti-interference ability, and does not rely too much on the travel time of the bus At the same time, under the condition that the bus is greatly interfered, and the actual travel time and the predicted time have a large error, it can also pass the intersection well; greatly improve the travel efficiency, and have a wide range of social benefits and Practical value.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a V2X-based dynamic feedback control method for bus priority. Background technique [0002] The frequent occurrence of traffic jams and traffic accidents seriously restricts the rapid development of cities, and greatly reduces the travel quality and efficiency of urban residents. Public transport travel can effectively reduce traffic congestion and the occurrence of congestion events, and improve the travel efficiency of cities. Due to the emergence of the "bus priority" traffic strategy, the bus priority strategy has become the preferred choice for solving urban traffic development problems. [0003] However, the current bus priority control strategies, such as bus lanes, BRT, etc., have not truly achieved bus priority. Buses and social vehicles need to wait for the signal to release together at the intersection, so only through the signal priority control ca...

AI Technical Summary

Problems solved by technology

However, the algorithm related to the bus priority signal control has not achieved the ideal control effect. At present, most of the research focuses on how to improve the travel efficiency of the bus as a whole and reduce the interference to social vehicles. The problems caused by external interference and the deviation caused by the bus time prediction have not been studied, and the actual operation status of the bus itself has not been considered

[0004] In the current bus priority control methods, predictive control based on travel time is mostly used, but these control methods are limited by the accuracy of travel time prediction

However, the prediction accuracy of the travel time is greatly affected by the interference of the external environment, such as the deceleration of the vehicle in front, the congestion of the vehicle, etc., which will lead to a large error in the prediction of the travel time of the bus, resulting in a decrease in the effect of bus priority control

If the actual travel time is much longer than the predicted time, under the green light extension control strategy, the bus will not pass the intersection after the green light phase ends.

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