STUDY ON START-UP LOST TIME AT SIGNALIZED INTERSECTIONS CONSIDERING DOWNSTREAM CONDITIONS

Abstract

Start-up lost time (SLT, hereinafter) is one of the basic parameters for evaluating the capacities of signalized intersections. In the urban area, intersections are closely spaced and traffic demand is high. Drivers’ ambitions for the quick startup are demotivated by negative downstream traffic conditions, for example, limited available storage length, long queue and/or poorly coordinated traffic signals. The performance of upstream intersection is deteriorated including the growth in the SLT. In this paper, the influence of downstream conditions over SLT is analyzed by empirical study. The result indicates that SLTs at subject intersections are mainly influenced by downstream queue length, offset, segment length, and clearing vehicles. Short downstream segment length, long queue, positive offset, and long clearing time will lead to a high SLT value. Regarding this finding, the effect is further investigated by developing a new car-following model. The new model is built by improving the intelligent driver model and calibrated it with empirical data by a genetic algorithm. Through scenario simulation and comparison with empirical data, it is proved that the new model not only can reproduce the SLT increase under different downstream conditions but also have a good fit with real-world data.