چکیده مقاله
Car following models are among the most important components of micro traffic flow simulation which is studied by transportation experts to evaluate new applications of intelligent transportation systems Until now, several car following models have been proposed An obvious disadvantage of the former models is the great number ofparameters which are difficult to calibrate In this paper, a car following model was modeled and developed by combining an Adaptive Neuro Fuzzy Inference System ANFIS and a Classification And Regression Tree CART to simulate and predictfuture behavior of each driver vehicle unit DVU In this model, the reaction time was instantaneously calculated based on the time interval between acceleration and relativevelocity by proposed model and was regarded as a new input The results were compared with the fixed reaction time and the reaction time proposed by Ozaki To evaluate the performance of the model, we compared the proposed model's output data with realconditions and it was found that the precision of the proposed model was significantly high with regard to the instantaneous reaction time According the implemented simulation, the proposed model reached a good validity on the basis of proximity to a real situation of car following
کلیدواژهها
نویسندگان
شیوه ارجاع
Poor Arab Moghadam, Mohsen and Pahlavani, Parham and Naseralavi, Saber,1394,Applying Adaptive Neuro Fuzzy Inference system and Regression Tree for Prediction Car Following Behavior Based on Instantaneous Reaction Time,The 15th International Conference on Traffic and Transportation Engineering,Tehran
ارائهشده در
مجموعه مقالات پانزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک11 اسفند 1394 · تهران