Modeling On Discharge Headway With Heterogeneous Traffic At Signalized Intersections

ABSTRACT:Most cities in China are characteristiced by heterogeneous traffic. Under the heterogeneous traffic condition, motorized vehicles, non-motorized vehicles and pedestrians all have their own characteristics, and interfere with each other, which cause the decrease of road facilities utilization and operation quality, and challenge the road transport management and control system. The intersection is the basic node of the road network in a city, and also the bottleneck of network capacity and traffic safety. Therefore, the intersection capacity has a great influence on the whole transport network.As a key parameter for traffic microscopic analysis, discharge headway of queuing vehicle in signalized intersection dircectly reflect driving behavior characteristic, as well as intersection capacity and service level. Based on the review of relavent research home and abroad, combined with heterogeneous traffic investigation data, several subjects, like discharge characteristics of queuing vehicles, the first discharge headway, successive discharge headway are analysed. Main works and conclusions of this dissertation are summarized as below:â‘ According to the video record data, we elaborately analyses the discharging process of queuing vehicles and its discharge headway. On this foundation, the four stage of discharging are proposed, i.e. the initial speedup phase, compaction platoon phase, platoon dispersion phase, and free flow phase. However, the four stages may not appear under some situation owing to non-motorized vehicles disturbance. By analyzing the discharge characteristic of heterogeneous traffic, this dissertation expressly instructs that the discharge headways on lane type are in the following descending order:the right-turn-only-lane, the left-turn-only-lane, the off-side straight lane, and the kerb-side straight lane. And then, we also make a quantative analysis on the effects on discharge headway for non-motorized vehicles disturbance and vehicle type.â‘¡Hazard-based analysis method is introduced into traffic flow field after adaptability analysis, and for the first time first discharge headway is modeled basing on hazard-based analysis method. The partial likelihood function and parameters' evaluation method is explored deeply next. Then a case study of typical signalized intersections at Beijing is conducted. The results provided that in Beijing city the first discharge headway arrives at 4.54s, which is obviously longer than in other equivalent foreign cities. And the factor analysis results also reveal the influence degree of the starting disturbance and the moving disturbance, which causes an increase in the average first discharge headway to 37.09 percent and 60.24 percent, respectively.â‘¢The defects of existing top-three widly-used headway models, which are Deterministic Model (DM), Bonneson Model (BM), and Neural Network Model of discharge headway (NNM), are analysed, and the principle of Statistical Learing Theory and Support Vector Machine (SVM) is represented next. In addition, a SVM-based discharge headway model at signalized intersection is constructed for the first time, and the related analytical frameworks and process are presented. In the model, subject vehicle type, preceding vehicle type, lane type, discharging headway of the preceding vehicle, queuing position, and disturbance are input, and discharge headway of the subject vehicle is output. Besides, three indexes, i.e. relative percentage error (RPE), mean absolute percentage error (MAPE), and root mean square error (RMSE), are introduced to evaluate the model perfoemance. At last, performances of three models, namely SVM-based discharge headway model (SVMM), DM, and NNM, are evaluated by case studies. The results indicate that the SVMM is better than the others.â‘£Based on the discharge stability analysis of queuing vehicles at signalized intersections, the saturation flow rate defined in Highway Capacity Manual is pointed out that can hardly happen under the heterogeneous traffic condition at Beijing. This means that the HCM capacity model based on the saturation flow rate is not adaptive. After introduction of two variables, i.e. the expected number of vehicles that can be discharged during green interval of usable phase,, and the expected number of vehicles that can be discharged during green time of usable phase,, a modified intersection capacity model is presented and the related parameters is calibrated by cumulative curve method. Finally, the eastbound of Zhichunlukou is conducted as an empirical analysis. The results show that the modified model is better than HCM model in accuracy, simplicity and universality.