Real-time Priority Control Of Bus Signals Without Dedicated Lanes Based On Right-turn Lane Sharing Strategy

Advocating public transportation priority,improving the operational efficiency of the urban public transportation system,and giving full play to the service efficiency of the public transportation system has always been the strategic goal of my country’s transportation development.As an important means of public transportation,buses have the advantages of large passenger capacity,high transportation efficiency,and green environmental protection.Therefore,implementing the strategy of prioritizing public transportation signals within the city is of great significance to improving the level of public transportation services and improving the urban passenger transportation system.Aiming at the limitations of current bus signal priority control methods such as poor real-time performance and difficulty in adapting to the random characteristics of bus arrivals,this paper constructs a traffic organization strategy based on the real-time stepby-step prediction of bus travel time and the right-turn ridesharing strategy.A real-time priority control model for public transport signals,and the implementation effect of the model is evaluated.Considering that the time when the bus arrives at the intersection is highly random,in order to adjust the signal timing scheme in real time according to the operating state of the bus and reserve enough response time for the control system,the paper proposes a bus itinerary based on spatial Kalman filtering.Time real-time step-by-step prediction method.That is to say,the intersection is used as a spatial state update node,and the state equation and observation equation are established according to the travel time relationship of the bus traveling between the intersections,and then the predicted value and the observation value are merged according to the principle of minimum mean square error,and the bus arrives at the downstream intersection.The optimal estimated value of the travel time of the intersection,and the step-by-step iterative prediction is realized as the bus travels at the intersection.The prediction results show that the root mean square error(RMSE)between the optimal estimated value and the actual value is less than 25 seconds,and the average percentage error MAPE value is mostly less than20%.This model can achieve a more accurate prediction of bus travel time.In terms of the bus signal real-time priority control model,the paper improves the traditional inductive bus signal priority control method,combined with the aforementioned bus travel time prediction model,and adopts the strategies of green time extension,red light interruption and phase insertion to provide bus priority access.And take intersection saturation,maximum and minimum green hours,and intersection performance indicators as the strategy execution conditions,set up qualified signal priority strategies for downstream intersections in the direction of public traffic.The bus signal real-time priority control model and the bus travel time real-time step prediction together realize the iterative process of prediction-control-update,forming a sensorcontrol interactive bus signal priority control system.Finally,the paper takes part of Qianjin Road in Kunshan City as the research object.Based on the actual data of traffic status and signal timing,SUMO traffic simulation software is used to evaluate the effect of the real-time priority control of public transport signals proposed in this paper.Compared with the original time-divided fixed signal timing,after adopting the bus priority strategy proposed in this paper,the total travel time of public transportation vehicles on the research section is reduced by about 17.6%on average,the signal delay at the intersection is reduced by about 74.8%,and the number of stops.An average reduction of 46.5%;because the extension of green hours and early red light breaks are also effective for social vehicles in the same phase,the delays and the number of parking times for vehicles in the same phase are also reduced slightly.The results of multiple experiments have a better distribution.