本文選題：交通流理論 + 優(yōu)化速度　； 參考：《哈爾濱工業(yè)大學(xué)》2016年碩士論文

【摘要】：車輛跟馳理論既是微觀交通流理論最基本的仿真模型,也是理解宏觀交通流形成的理論基石,而且具有指導(dǎo)交通組織和管理、緩解交通擁堵的現(xiàn)實(shí)意義。隨著智能交通系統(tǒng)和智能車載設(shè)備的發(fā)展,駕駛員在駕駛過程中獲取的道路、交通和環(huán)境信息越來越豐富和準(zhǔn)確,必然對駕駛員的駕駛行為產(chǎn)生一定的影響,而車輛行駛中的跟馳行為,是駕駛員主要的駕駛行為之一,因此研究多前車影響下的車輛跟馳行為具有重要的意義。首先,搭載高精度車載GPS設(shè)備獲取了大量的車輛跟馳數(shù)據(jù)。以加速度變化為依據(jù)將車輛跟馳分為啟動(dòng)加速、穩(wěn)定跟馳以及減速停車三個(gè)狀態(tài),并分別分析了每個(gè)狀態(tài)下車輛速度和加速度變化規(guī)律。分析了車頭間距-速度的數(shù)量關(guān)系,結(jié)果表明指數(shù)曲線能夠較好地描述車頭間距隨速度的變化趨勢;分析了加速度隨后車速度和相對速度的變化趨勢,結(jié)果表明加速度和相對速度呈現(xiàn)出較強(qiáng)的線性正相關(guān)關(guān)系。然后構(gòu)建了基于修正優(yōu)化速度函數(shù)的多前車跟馳模型�；趯�(shí)測數(shù)據(jù)對原優(yōu)化速度函數(shù)進(jìn)行了修正,基于多前車駕駛特性的考慮對原多前車跟馳模型進(jìn)行了修正,構(gòu)建了基于修正優(yōu)化速度函數(shù)的多前車跟馳模型。應(yīng)用物理和數(shù)學(xué)方法對模型進(jìn)行了穩(wěn)定性求解,得到模型的穩(wěn)定方程和穩(wěn)定條件。應(yīng)用實(shí)測數(shù)據(jù)對修正的優(yōu)化速度函數(shù)和修正的多車跟馳模型進(jìn)行了參數(shù)標(biāo)定,確定速度-車頭間距的數(shù)量關(guān)系以及駕駛員對期望速度差和前后車速度車的敏感系數(shù)。最后通過理論推導(dǎo)和數(shù)值仿真分析了修正的多前車跟馳模型對交通現(xiàn)象的解釋以及模型穩(wěn)定性,并與原多前車跟馳模型進(jìn)行了對比。理論推導(dǎo)結(jié)果表明修正的優(yōu)化速度函數(shù)推導(dǎo)的交通流參數(shù)關(guān)系與實(shí)測數(shù)據(jù)擬合精度更高。數(shù)值仿真結(jié)果表明修正的多前車跟馳模型能夠較好地描述車輛在啟動(dòng)加速和減速停車時(shí)的速度和加速度變化趨勢,且在遇到人為干擾以及多駕駛特性造成的擾動(dòng)時(shí)能夠以更小的波動(dòng)幅度和更快的速度達(dá)到均衡狀態(tài)。
[Abstract]:The car following theory is not only the most basic simulation model of the microscopic traffic flow theory, but also the theoretical foundation for understanding the formation of the macro traffic flow, and has the practical significance of guiding the traffic organization and management and alleviating traffic congestion. With the development of intelligent transportation system and intelligent vehicle equipment, the driver gets the road and traffic during the driving process. And the environment information is more and more abundant and accurate, and the driving behavior of the driver is bound to have a certain influence, and the following behavior in the vehicle is one of the main driving behavior of the driver. Therefore, it is of great significance to study the car following behavior under the influence of the multi front vehicle. First, carrying a high precision vehicle GPS equipment has obtained a large amount. The vehicle heel data, based on the acceleration change, divides the car following into three states of starting acceleration, steady and slow stopping and decelerating and stopping, and analyses the law of vehicle speed and acceleration in each state, and analyzes the number relation of the distance velocity of the head. The result shows that the index curve can describe the distance of the head better. The trend of velocity change is analyzed. The trend of the acceleration and relative velocity is analyzed. The result shows that the acceleration and relative velocity have a strong linear correlation. Then a multi front car following model based on the modified optimization velocity function is constructed. Based on the measured data, the original optimization speed function is modified, based on the more. In the consideration of the driving characteristics of the front car, the model of the multiple front car following the original multi front car is corrected, and a multi front car following model based on the modified optimization velocity function is constructed. The stability of the model is solved by the physical and mathematical methods, the stability equation and the stability condition of the model are obtained. The modified optimization speed function and the correction are used by the measured data. The parameters of the multi car following model are calibrated to determine the relationship between the speed and the head distance and the driver's sensitivity to the expected speed difference and the front and back speed car. Finally, the theory and numerical simulation are used to explain the traffic phenomenon and the model stability. The model is compared. The theoretical derivation shows that the traffic flow parameters derived from the modified optimization speed function are more accurate than the measured data. The numerical simulation results show that the modified multi front car following model can describe the speed and acceleration trend of the vehicle in the acceleration and deceleration. Disturbance caused by human interference and multiple driving characteristics can achieve a smaller state of fluctuation and faster speed.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：U491
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本文編號：1943412