|Table of Contents|

Bus-following model based on multi-source data fusion(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2023年4期
Page:
95-105
Research Field:
交通工程
Publishing date:

Info

Title:
Bus-following model based on multi-source data fusion
Author(s):
HAO Xin-jun1;  XU Yu-jie2;  LU Yong-chun3;  JI Can2;  YU Shao-wei2
(1. School of Management, Xi'an University of Finance and Economics, Xi'an 710100, Shaanxi, China; 2. School of Transportation Engineering, Chang'an University, Xi'an 710086, Shaanxi, China; 3. School of Information Engineering, Chang'an University, Xi'an 710086, Shaanxi, China)
Keywords:
traffic engineering;  intelligent transportation;  bus-following model;  parameter calibration;  bus;  multi-source data fusion
PACS:
U491.112
DOI:
10.19721/j.cnki.1671-8879.2023.04.010
Abstract:
Aiming at the two current problems that lack that bus-following model parameters and the inability to obtain complete bus-following process data by a single data acquisition method, a bus-following model based on multi-source data fusion was proposed, and measured data was used for parameter calibration and model verification. The bus trajectory data was collected with the mobile GPS data acquisition equipment and the parking distance of the bus was collected with the aerial hovering video of unmanned aerial vehicle. The complete process of bus-following driving data was obtained by data fusion processing. The mean square error was used to measure the difference between the actual measured value and the simulated value of the model, the parameter calibration problem of bus-following model was transformed into a general optimization problem. Through statistical analysis of the measured data, the average parking spacing parameters of buses were obtained. Particle swarm optimization algorithm was used to solve the comfortable braking deceleration and acceleration coefficient of the intelligent driver model, and the optimal parameters of the model were obtained. The measured value in the verification set was compared with the simulated value of the model to verify the effect of the model parameters. Finally, the effect of bus-following model was further verified by taking the multi-platoon operation control of bus rapid transit corridor in Xiamen as an example. The leading bus was controlled by the speed optimization model and the following buses were controlled by the bus-following model calibrated above. The results show that the simulation data curve generated by the bus-following model was basically consistent with the measured data curve. The motion trajectory curves of the following bus and the leading bus in the two stages of driving on the road section, and the bus in and out of the stop were basically consistent. It accords with the following features of bus-following model, which further proves the validity of the above-mentioned calibration model parameters.5 tabs, 11 figs, 29 refs.

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Last Update: 2023-08-20