發(fā)布時(shí)間：2018-11-26 13:23

【摘要】：機(jī)動(dòng)車(chē)保有量激增,導(dǎo)致交通供需矛盾日益突出,交通信息服務(wù)作為調(diào)整交通流時(shí)空分布、提高路網(wǎng)通行能力的有效手段,廣泛應(yīng)用于城市交通管理。研究表明現(xiàn)實(shí)生活中約80%的信息與位置息息相關(guān),因此將位置服務(wù)與交通信息服務(wù)結(jié)合已經(jīng)成為交通信息服務(wù)的發(fā)展趨勢(shì)。基于LBS的交通信息主動(dòng)推送模型將有效解決行車(chē)環(huán)境中信息過(guò)載問(wèn)題,減少出行者時(shí)間資源浪費(fèi),緩解交通供需矛盾。借助所提出的融合定位算法提供位置信息,本文提出了基于LBS的交通信息主動(dòng)推送模型,并完成了主動(dòng)推送系統(tǒng)總體設(shè)計(jì)及軟硬件設(shè)計(jì),結(jié)合兩種主動(dòng)推送場(chǎng)景驗(yàn)證了主動(dòng)推送模型的有效性。首先,從信息推送、位置獲取等方面總結(jié)國(guó)內(nèi)外研究現(xiàn)狀,提出了本文的研究?jī)?nèi)容和技術(shù)路線(xiàn)。接著,在介紹位置服務(wù)系統(tǒng)的體系結(jié)構(gòu)、關(guān)鍵技術(shù)基礎(chǔ)上,總結(jié)分析了目前國(guó)內(nèi)外交通信息服務(wù)系統(tǒng)應(yīng)用現(xiàn)狀及問(wèn)題。然后,分析現(xiàn)有定位方法的不足,充分利用各個(gè)定位方法在時(shí)空上互補(bǔ)特性,提出了基于BP神經(jīng)網(wǎng)絡(luò)的融合定位算法,利用卡爾曼濾波和量子粒子群實(shí)現(xiàn)GPS、DR、WIFI的多源融合定位;借助融合定位算法提供的位置信息,從位置服務(wù)角度出發(fā)設(shè)計(jì)了基于推送狀態(tài)、推送優(yōu)先級(jí)、推送強(qiáng)度以及推送時(shí)長(zhǎng)等特征參數(shù)的主動(dòng)推送模型。為驗(yàn)證模型有效性構(gòu)建了主動(dòng)推送系統(tǒng),詳細(xì)給出了系統(tǒng)的硬件、軟件、數(shù)據(jù)庫(kù)等設(shè)計(jì)。最后,基于設(shè)計(jì)的主動(dòng)推送系統(tǒng)對(duì)所提出的融合定位算法和主動(dòng)推送模型進(jìn)行了實(shí)車(chē)驗(yàn)證,考慮推送內(nèi)容設(shè)計(jì)事故預(yù)警、路況提示兩種場(chǎng)景,通過(guò)分析主動(dòng)推送模型特征參數(shù)等來(lái)驗(yàn)證推送模型有效性。并對(duì)主動(dòng)推送響應(yīng)時(shí)間進(jìn)行分布特征分析,同時(shí)進(jìn)行了推送距離、行駛速度對(duì)響應(yīng)時(shí)間的敏感性分析。利用所設(shè)計(jì)系統(tǒng)對(duì)模型進(jìn)行分析實(shí)驗(yàn)結(jié)果表明,相較于其他兩種定位算法,所提出的融合定位算法定位精度分別提高87.06%和68.71%,可為主動(dòng)推送模型提供有效位置信息。所設(shè)計(jì)的主動(dòng)推送系統(tǒng)可在1-3s內(nèi)為車(chē)輛提供實(shí)時(shí)的基于LBS的交通信息服務(wù),并且該系統(tǒng)可隨車(chē)輛位置、路網(wǎng)熟悉度以及行駛速度實(shí)時(shí)調(diào)整主動(dòng)信息服務(wù)策略;此外,主動(dòng)推送模型特征參數(shù)敏感性分析表明,推送距離、行駛速度對(duì)響應(yīng)時(shí)間有影響,響應(yīng)時(shí)間隨推送距離增加呈現(xiàn)先遲緩增長(zhǎng)后快速增長(zhǎng)再穩(wěn)定的變化趨勢(shì),行駛速度也呈現(xiàn)類(lèi)似的影響規(guī)律。隨著行駛速度以及推送距離的逐漸增大,響應(yīng)時(shí)間逐漸增大并趨近于3s。
[Abstract]:The increasing number of motor vehicles leads to the increasingly prominent contradiction between supply and demand. As an effective means to adjust the space-time distribution of traffic flow and improve the capacity of road network, traffic information service is widely used in urban traffic management. The research shows that about 80% of the information is closely related to the location in real life, so the combination of location service and traffic information service has become the development trend of traffic information service. The active push model of traffic information based on LBS will effectively solve the problem of information overload in traffic environment, reduce the waste of time and resources of travelers, and alleviate the contradiction between traffic supply and demand. With the help of the proposed fusion location algorithm to provide location information, this paper proposes an active push model of traffic information based on LBS, and completes the overall design of active push system and the design of software and hardware. Combining two kinds of active push scenarios, the validity of the active push model is verified. Firstly, this paper summarizes the status quo of information push and location acquisition at home and abroad, and puts forward the research content and technical route of this paper. Then, on the basis of introducing the architecture and key technologies of the location service system, this paper summarizes and analyzes the current situation and problems of the application of the transportation information service system at home and abroad. Then, by analyzing the shortcomings of the existing localization methods and making full use of the complementary characteristics of each localization method in time and space, a fusion localization algorithm based on BP neural network is proposed. The GPS,DR, is realized by using Kalman filter and quantum particle swarm optimization (QPSO). Multi-source fusion localization of WIFI; Based on the location information provided by the fusion location algorithm, an active push model based on push state, push priority, push intensity and push time is designed from the point of view of location service. In order to verify the validity of the model, the active push system is constructed, and the hardware, software and database design of the system are given in detail. Finally, based on the design of the active push system, the proposed fusion location algorithm and the active push model are verified by the actual vehicle, considering the push content design accident early warning, the road situation hint two kinds of scenarios, The validity of the push model is verified by analyzing the characteristic parameters of the active push model. The distribution characteristics of active push response time and the sensitivity of push distance and travel speed to response time are analyzed. The experimental results show that compared with the other two localization algorithms, the accuracy of the proposed fusion localization algorithm is increased by 87.06% and 68.71%, respectively. It can provide effective location information for active push model. The designed active push system can provide real-time traffic information service based on LBS for vehicles within 1-3s, and the system can adjust the active information service strategy in real time with vehicle location, road network familiarity and driving speed. In addition, the sensitivity analysis of the characteristic parameters of the active push model shows that the push distance and the driving speed have an effect on the response time, and the response time increases slowly first and then steadily with the increase of the push distance. The driving speed also presents the similar influence law. With the increase of driving speed and push distance, the response time increases and approaches to 3 s.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：U495

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本文編號(hào)：2358682