畢業(yè)論文外文文獻(xiàn)翻譯模板1.doc

廣東工業(yè)大學(xué)華立學(xué)院本科畢業(yè)設(shè)計(jì)（論文）外文參考文獻(xiàn)譯文及原文 系 部 建設(shè)學(xué)部 專(zhuān) 業(yè) 土地資源管理 年 級(jí) 2008級(jí) 班級(jí)名稱(chēng) 08土地資源管理1班 學(xué) 號(hào)學(xué)生姓名 指導(dǎo)教師 陳 靜 2012 年 5 月 目錄、外文文獻(xiàn)譯文1、外文文獻(xiàn)原文12微觀仿真在城市停車(chē)設(shè)施規(guī)劃中的應(yīng)用作者簡(jiǎn)介：Pete Sykes(1956 )，男，英國(guó)愛(ài)丁堡人，工商管理碩士（MBA），微觀仿真市場(chǎng)和開(kāi)發(fā)部主任，主要研究方向：S-Paramics 微觀仿真軟件開(kāi)發(fā)。摘要為研究停車(chē)場(chǎng)規(guī)劃和可達(dá)性對(duì)城市路網(wǎng)的影響，在世界范圍內(nèi)的三個(gè)不同城市應(yīng)用微觀仿真模型模擬停車(chē)設(shè)施規(guī)劃。描述了三個(gè)城市采用的不同研究方法及得到的研究結(jié)果。三項(xiàng)研究都試圖找到由駕駛?cè)藢ふ彝＼?chē)位而造成的城市交通擁堵的解決方法。同時(shí)，在測(cè)試設(shè)計(jì)方案時(shí)，都使用了S-Paramics微觀仿真模型。關(guān)鍵詞：交通模型；微觀仿真；矩陣細(xì)化；停車(chē)場(chǎng)；規(guī)劃對(duì)市區(qū)駕駛?cè)藖?lái)說(shuō)，停車(chē)設(shè)施供給是最具爭(zhēng)議的問(wèn)題之一。停車(chē)位難找、停車(chē)費(fèi)用昂貴是主要問(wèn)題。距離最近、最方便的停車(chē)場(chǎng)往往有很多車(chē)輛排隊(duì)等候，駕駛?cè)吮仨氜D(zhuǎn)而找尋其他停車(chē)場(chǎng)。城市中心區(qū)的一些商家認(rèn)為，缺乏合適的停車(chē)設(shè)施已成為顧客選擇市外購(gòu)物中心的重要原因。2002 年，在美國(guó)紐黑文(New Haven)市最大的停車(chē)場(chǎng)改造慶典上，該市市長(zhǎng)Rowland 先生說(shuō)：“如果沒(méi)有停車(chē)場(chǎng)，什么措施都不會(huì)有效”1。駕駛?cè)嗽诘缆飞涎h(huán)駕駛尋找停車(chē)位，可能是城市中心區(qū)擁堵的主要原因。2006 年， 曼哈頓(Manhattan)的調(diào)查顯示，道路上行駛的車(chē)輛中，正在尋找停車(chē)位的小汽車(chē)比例達(dá)26%， 在布魯克林區(qū)(Brooklyn，位于紐約市西南部)則高達(dá)46%。這種狀況并不是近期才出現(xiàn)。1927 年，底特律(Detroit)市有兩個(gè)區(qū)做了類(lèi)似調(diào)查，相關(guān)數(shù)據(jù)分別為19% 和34%2。這一由來(lái)已久的問(wèn)題現(xiàn)在或許可以借助技術(shù)手段解決：移動(dòng)網(wǎng)絡(luò)電話(huà)(iPhone)用戶(hù)可以彼此告知停車(chē)位信息3；交通規(guī)劃人員則可以利用交通模型領(lǐng)域的最新研究成果微觀仿真來(lái)輔助停車(chē)場(chǎng)的規(guī)劃設(shè)計(jì)。城市規(guī)劃政策中的停車(chē)場(chǎng)選址主要側(cè)重于優(yōu)化停車(chē)場(chǎng)、駕駛?cè)思捌渑c目的地間的關(guān)系。優(yōu)化停車(chē)場(chǎng)選址獲得的潛在利益之一是通過(guò)改善目標(biāo)消費(fèi)群體的可達(dá)性，實(shí)現(xiàn)對(duì)城市商業(yè)中心的改善。制定的政策既包含以供應(yīng)為主導(dǎo)對(duì)停車(chē)位進(jìn)行積極管理，也包含以需求為主導(dǎo)簡(jiǎn)單增加停車(chē)位數(shù)量4。積極的管理政策正在被廣泛采用，以限制停車(chē)位數(shù)量、鼓勵(lì)可持續(xù)的交通方式5。城市規(guī)劃政策考慮停車(chē)場(chǎng)的收費(fèi)機(jī)制，交通規(guī)劃政策則對(duì)此加以補(bǔ)充，著重關(guān)注停車(chē)場(chǎng)的可達(dá)性以及停車(chē)場(chǎng)與路網(wǎng)、交通擁堵的關(guān)系。收費(fèi)機(jī)制可用來(lái)降低停車(chē)設(shè)施對(duì)當(dāng)?shù)卦斐傻牟槐?，并且在分配停?chē)位時(shí)區(qū)別對(duì)待不同停車(chē)類(lèi)型的駕駛?cè)恕Ｓ?guó)道路設(shè)計(jì)指南對(duì)停車(chē)場(chǎng)的可達(dá)性做了說(shuō)明。英國(guó)交通部關(guān)于停車(chē)誘導(dǎo)信息系統(tǒng)的建議中包含的案例報(bào)告表明，通過(guò)安裝可變信息標(biāo)志(VMS)顯示停車(chē)位狀態(tài)可獲得量化效益6。量化效益可用時(shí)間節(jié)省表示，非量化效益則表現(xiàn)為公共形象和駕駛?cè)说陌踩?。英?guó)交通部交通分析指南(WebTAG)7簡(jiǎn)要地提及了這一問(wèn)題，即在討論出行成本時(shí)應(yīng)包含停車(chē)成本(理論上包括尋找和排隊(duì)等待停車(chē)位以及步行到達(dá)最終目的地的時(shí)間)。停車(chē)場(chǎng)的可達(dá)性通常在城市設(shè)計(jì)完成以及停車(chē)政策確定后考慮。目前缺乏的環(huán)節(jié)是，在城市早期規(guī)劃階段交通規(guī)劃政策對(duì)停車(chē)場(chǎng)設(shè)施及其可達(dá)性的影響研究。最近，在世界范圍內(nèi)的三個(gè)不同城市對(duì)這一明顯不足進(jìn)行了探討，目的是尋求停車(chē)場(chǎng)規(guī)劃政策和可達(dá)性對(duì)路網(wǎng)影響的研究方法，探討內(nèi)容的共同之處集中在兩方面：1)試圖找到降低因駕駛?cè)藢ふ彝＼?chē)位造成的城市交通擁堵的解決方法；2)使用S-Paramics 微觀仿真模型測(cè)試設(shè)計(jì)方案。荷蘭新維根市(Nieuwegein) 所做的一項(xiàng)研究模擬了交通量大幅增長(zhǎng)時(shí)，在城市中心區(qū)一個(gè)重要的重建項(xiàng)目增加停車(chē)設(shè)施后其周邊交通情況；為使駕駛?cè)双@悉停車(chē)場(chǎng)停車(chē)情況和到達(dá)路線(xiàn)，該研究在微觀仿真模型中引入了智能交通系統(tǒng)(ITS)。另一項(xiàng)在英格蘭羅克代爾市(Rockdale)的研究(見(jiàn)圖1)仿真了停車(chē)位分布與城市中心區(qū)發(fā)展規(guī)劃的關(guān)系，其目標(biāo)是優(yōu)化停車(chē)設(shè)施與其周邊土地利用的關(guān)系；在設(shè)計(jì)過(guò)程的早期階段，通過(guò)改變停車(chē)場(chǎng)車(chē)位的供應(yīng)情況來(lái)控制城市中心區(qū)的交通擁堵?tīng)顩r。第三項(xiàng)是在新西蘭北岸市(North ShoreCity)的塔卡普納區(qū)(Takapuna)進(jìn)行的城市中心區(qū)擴(kuò)張對(duì)城市交通的影響研究；該研究使用專(zhuān)門(mén)的軟件仿真停車(chē)場(chǎng)需求，并使用微觀交通仿真模型將其需求分配到路網(wǎng)中；其目的同樣是了解停車(chē)政策效果，緩解城市中心區(qū)交通擁堵?tīng)顩r。1 停車(chē)場(chǎng)交通狀況微觀仿真典型的微觀仿真設(shè)計(jì)方案包括：改變道路布局、公交優(yōu)先措施、信號(hào)優(yōu)化、交通需求變化等，仿真中任一車(chē)輛在駛向目的地時(shí)，都會(huì)對(duì)采取的設(shè)計(jì)方案及其造成的擁堵做出反應(yīng)。對(duì)停車(chē)政策效果的仿真測(cè)試重點(diǎn)從路網(wǎng)變化帶來(lái)的影響，轉(zhuǎn)到車(chē)輛出行目的地變化對(duì)交通造成的影響。因此，仿真模型必須具有區(qū)別駕駛?cè)四康牡睾蛙?chē)輛停車(chē)位置的能力，并能在停車(chē)場(chǎng)間進(jìn)行動(dòng)態(tài)選擇。1.1 車(chē)輛到達(dá)停車(chē)場(chǎng)在微觀仿真模型中是一個(gè)整體，與目的地小區(qū)相連，且一個(gè)停車(chē)場(chǎng)可服務(wù)多個(gè)小區(qū)。通過(guò)限定使用停車(chē)場(chǎng)的車(chē)輛出行目的，對(duì)停車(chē)位進(jìn)行分配。由于每一類(lèi)型車(chē)輛可能會(huì)有不同的成本系數(shù)， 因此， 模型中以一般化出行成本(the generalised trip cost)來(lái)表示停車(chē)費(fèi)用以及停車(chē)場(chǎng)與相關(guān)小區(qū)間的距離。建模人員可據(jù)此區(qū)分接受較長(zhǎng)步行距離和較高費(fèi)用的駕駛?cè)恕Ｈ绻惩＼?chē)場(chǎng)已滿(mǎn)，模型中的駕駛?cè)嗽谌肟谔幍却欢〞r(shí)間后，會(huì)重新進(jìn)行停車(chē)場(chǎng)選擇評(píng)估，并可能駛向其他停車(chē)場(chǎng)。通過(guò)外部軟件控制器可以監(jiān)控模型中停車(chē)場(chǎng)的占有率，并能在車(chē)輛到達(dá)停車(chē)場(chǎng)等待隊(duì)列之前改變其行駛方向。下面用一個(gè)例子說(shuō)明在停車(chē)政策模型中如何應(yīng)用這種方法。假設(shè)某零售業(yè)和商業(yè)混合的城市中心區(qū)有多個(gè)停車(chē)場(chǎng)在合理的步行距離內(nèi)，根據(jù)停車(chē)時(shí)間和停車(chē)費(fèi)用結(jié)構(gòu)，駕駛?cè)藭?huì)優(yōu)先考慮某一停車(chē)場(chǎng)，且某些駕駛?cè)丝赡苡型＼?chē)許可證。一個(gè)停車(chē)場(chǎng)可能有多個(gè)相鄰的入口，為讓車(chē)輛支付適當(dāng)?shù)耐＼?chē)費(fèi)用，每個(gè)入口都有相應(yīng)的限制條件。仿真結(jié)果顯示，短暫停留的車(chē)輛，駕駛?cè)藭?huì)使用距離目的地較近且停車(chē)費(fèi)用較低的停車(chē)場(chǎng)。長(zhǎng)時(shí)間停留的車(chē)輛，駕駛?cè)藭?huì)使用費(fèi)用較高的入口進(jìn)入停車(chē)場(chǎng)或能接受較長(zhǎng)的步行時(shí)間。通過(guò)調(diào)整不同停車(chē)場(chǎng)的入口費(fèi)用或停車(chē)許可證的許可水平可以測(cè)試駕駛?cè)藢?duì)停車(chē)條件變化的反應(yīng)。通過(guò)調(diào)整使用某特定區(qū)域相關(guān)停車(chē)場(chǎng)的駕駛?cè)撕蛙?chē)輛類(lèi)型的比例，可以仿真停車(chē)場(chǎng)對(duì)土地利用變化的影響。1.2 車(chē)輛離開(kāi)在S-Paramics 微觀仿真模型中，路網(wǎng)的車(chē)輛分配是通過(guò)詳細(xì)的(5 min)時(shí)間釋放分布圖控制的。應(yīng)用于停車(chē)場(chǎng)規(guī)劃時(shí)，最簡(jiǎn)單的情形是依據(jù)最低出行成本(包括最短出行時(shí)間)或停車(chē)場(chǎng)面積確定車(chē)輛始發(fā)停車(chē)場(chǎng)。對(duì)于更復(fù)雜的情形，如為使同一停車(chē)場(chǎng)到達(dá)和駛離車(chē)輛相匹配，可通過(guò)與模型相連的外接控制器來(lái)控制車(chē)輛出發(fā)，并與停車(chē)場(chǎng)占有率監(jiān)測(cè)系統(tǒng)相連，利用特定算法確定車(chē)輛的離開(kāi)時(shí)間和地點(diǎn)，從而達(dá)到到達(dá)和駛離車(chē)輛相匹配的目標(biāo)。2 仿真對(duì)策2.1 數(shù)據(jù)收集新維根市交通需求矩陣來(lái)自于已有宏觀模型，并使用調(diào)查數(shù)據(jù)進(jìn)行調(diào)整。同時(shí)，通過(guò)進(jìn)一步調(diào)查確定主要停車(chē)場(chǎng)的使用情況，如車(chē)輛平均停放時(shí)間和商店停止?fàn)I業(yè)后停車(chē)場(chǎng)存留的車(chē)輛。羅克代爾市和塔卡普納區(qū)的要求較為復(fù)雜，有必要收集更為全面的數(shù)據(jù)。羅克代爾市的交通需求矩陣數(shù)據(jù)主要來(lái)自路邊訪(fǎng)問(wèn)，顯示了出行的真實(shí)目的。由訪(fǎng)問(wèn)數(shù)據(jù)可確定停車(chē)種類(lèi)(如長(zhǎng)時(shí)間/短暫停留、路邊/專(zhuān)用停車(chē)場(chǎng)停車(chē)、是否有停車(chē)許可證等)和可能的停車(chē)時(shí)間(基于出行目的)。為了將停車(chē)場(chǎng)和目的地小區(qū)聯(lián)系起來(lái)，需利用市中心所有停車(chē)場(chǎng)的數(shù)據(jù)清單及各停車(chē)場(chǎng)的占有率建立停車(chē)場(chǎng)位置模型。首先采用簡(jiǎn)易幾何方法確定每一停車(chē)場(chǎng)到每個(gè)目的地小區(qū)的步行時(shí)間，并以此作為模型校準(zhǔn)參數(shù)。停車(chē)場(chǎng)數(shù)據(jù)清單對(duì)準(zhǔn)確估計(jì)不同類(lèi)型停車(chē)場(chǎng)(如長(zhǎng)時(shí)間/短暫停留、路邊/專(zhuān)用、私人/公共、收費(fèi)/免費(fèi)停車(chē)場(chǎng)等)的容量十分必要。數(shù)據(jù)清單包含市中心和周邊的所有停車(chē)場(chǎng)，同時(shí)還包括鄰近市中心的居民停車(chē)區(qū)。由于不收取停車(chē)費(fèi)用，盡管居民停車(chē)區(qū)距目的地有較長(zhǎng)的步行距離，通勤車(chē)輛仍常常使用。建模時(shí)，對(duì)接送車(chē)輛下客率較高的區(qū)域以私人停車(chē)場(chǎng)類(lèi)型對(duì)其進(jìn)行模擬。若需要對(duì)模型做進(jìn)一步改進(jìn)，可通過(guò)在需求矩陣中同時(shí)包含接送車(chē)輛的往返方向?qū)崿F(xiàn)。停車(chē)場(chǎng)數(shù)據(jù)清單也包括每一停車(chē)場(chǎng)的收費(fèi)信息。結(jié)合各停車(chē)場(chǎng)實(shí)際調(diào)查數(shù)據(jù)，發(fā)現(xiàn)停車(chē)場(chǎng)收費(fèi)情況可簡(jiǎn)單歸為短暫停留和長(zhǎng)時(shí)間停留兩種。這種簡(jiǎn)化較適用于羅克代爾市，但若不同停車(chē)場(chǎng)的收費(fèi)差異十分顯著，則須區(qū)別對(duì)待。仿真時(shí)，羅克代爾市的停車(chē)場(chǎng)數(shù)據(jù)較適用于高峰時(shí)段，若對(duì)停車(chē)場(chǎng)進(jìn)出車(chē)輛進(jìn)行全天詳細(xì)調(diào)查，則會(huì)對(duì)模型更加有益。在塔卡普納區(qū)和新維根市，收集的停車(chē)場(chǎng)數(shù)據(jù)包括車(chē)輛到達(dá)時(shí)間、停留時(shí)間和停車(chē)場(chǎng)占有率。這些數(shù)據(jù)與收費(fèi)信息一起用于仿真駕駛?cè)藢?duì)停車(chē)場(chǎng)的選擇情況。2.2 需求矩陣細(xì)化停車(chē)需求矩陣細(xì)化使建模人員能夠控制不同類(lèi)型車(chē)輛駛離停車(chē)場(chǎng)的時(shí)間。細(xì)化程度取決于已有調(diào)查數(shù)據(jù)，同時(shí)，停車(chē)場(chǎng)分類(lèi)的詳細(xì)程度應(yīng)與模型輸入數(shù)據(jù)相適應(yīng)。在羅克代爾市，小汽車(chē)分為通勤車(chē)輛、非通勤車(chē)輛和公務(wù)車(chē)輛，停車(chē)需求矩陣可由此導(dǎo)出。根據(jù)調(diào)查數(shù)據(jù)，可把通勤車(chē)輛、公務(wù)車(chē)輛進(jìn)一步分為非居民私人停車(chē)(Private Non Residential, PNR)和合同停車(chē)（contract parking)。由于需求矩陣已被明確定義，對(duì)于難以估計(jì)的PNR 車(chē)位供應(yīng)量，模型不予限定，并假設(shè)市中心周邊地區(qū)所有駕駛?cè)司谄淠康牡赝＼?chē)。塔卡普納區(qū)采用了類(lèi)似方法，停車(chē)需求細(xì)分為長(zhǎng)時(shí)間和短暫停車(chē)兩類(lèi)。依據(jù)工作場(chǎng)所是否有停車(chē)位，將長(zhǎng)時(shí)間停車(chē)進(jìn)一步分為工作場(chǎng)所就地停車(chē)(on site)或公共停車(chē)場(chǎng)停車(chē)兩類(lèi)。長(zhǎng)時(shí)間和短暫停車(chē)的需求量可由宏觀交通模型的出行目的矩陣導(dǎo)出，并通過(guò)停車(chē)場(chǎng)記錄的車(chē)輛數(shù)進(jìn)行調(diào)整。2.3 出行鏈接為了仿真同一停車(chē)場(chǎng)的車(chē)輛到達(dá)和離開(kāi)，必須把進(jìn)入和駛離城市中心區(qū)的出行聯(lián)系起來(lái)，并基于車(chē)輛先前到達(dá)的停車(chē)場(chǎng)及停留時(shí)間選擇其始發(fā)停車(chē)場(chǎng)和駛離時(shí)間。傳統(tǒng)的OD矩陣法不能滿(mǎn)足此要求，需要使用更復(fù)雜的控制方法來(lái)確定車(chē)輛的駛離時(shí)間和地點(diǎn)。新維根市的模型研究時(shí)段為某周六下午的購(gòu)物高峰時(shí)段，并包含了一個(gè)前期準(zhǔn)備階段，以便為模型中的停車(chē)場(chǎng)預(yù)停一些車(chē)輛，同時(shí)對(duì)ITS 控制器進(jìn)行初始化。為了仿真相鏈接的車(chē)輛出行，需要從OD 矩陣中刪除所有從市中心始發(fā)的車(chē)輛。利用外部軟件控制器監(jiān)測(cè)模型中的停車(chē)場(chǎng)占有率，以確定車(chē)輛到達(dá)時(shí)間的分布情況，在停留一段合適的時(shí)間(如1 h)后，讓與到達(dá)車(chē)輛相匹配的返程車(chē)輛出發(fā)。塔卡普納區(qū)模型基于早高峰的停車(chē)場(chǎng)占有率，在仿真停車(chē)場(chǎng)晚高峰運(yùn)行情況之前，利用一個(gè)獨(dú)立的需求模型生成停車(chē)場(chǎng)晚高峰車(chē)輛出發(fā)時(shí)間分布圖。塔卡普納區(qū)每個(gè)分區(qū)包含有車(chē)輛出發(fā)時(shí)間分布情況的出行需求量，OD 矩陣即基于此生成。在車(chē)輛選擇某一特定停車(chē)場(chǎng)出發(fā)時(shí)，需求模型中的車(chē)輛出發(fā)分區(qū)與停車(chē)車(chē)輛所在分區(qū)相匹配。匹配關(guān)系基于停留時(shí)間長(zhǎng)短，并按照車(chē)輛到達(dá)時(shí)間分布預(yù)計(jì)出發(fā)時(shí)間。若此過(guò)程中發(fā)現(xiàn)某車(chē)輛的出發(fā)時(shí)間與預(yù)計(jì)出發(fā)時(shí)間的誤差在20%以?xún)?nèi)，則該車(chē)輛將被添加到出發(fā)時(shí)段分布圖中。若沒(méi)有找到匹配車(chē)輛，則轉(zhuǎn)到下一出發(fā)時(shí)段分布圖，并重復(fù)搜索過(guò)程。羅克代爾市模型對(duì)車(chē)輛到達(dá)和駛離停車(chē)場(chǎng)的仿真也劃分為早晚高峰兩個(gè)時(shí)段。模型對(duì)晚高峰時(shí)段出發(fā)停車(chē)場(chǎng)的選擇使用了一般化出行成本和“出口成本(exit cost)”，以幫助區(qū)分停車(chē)場(chǎng)選擇。通過(guò)與觀測(cè)數(shù)據(jù)進(jìn)行對(duì)比，發(fā)現(xiàn)使用“出口成本”可以更加成功地校準(zhǔn)模型。 2.4 停車(chē)場(chǎng)的尋找上述三個(gè)模型的研究對(duì)象均為停車(chē)場(chǎng)對(duì)城市交通擁堵的影響，因此，研究成功的關(guān)鍵是模型把車(chē)輛分配到停車(chē)場(chǎng)的策略以及車(chē)輛尋找停車(chē)場(chǎng)的過(guò)程。新維根市的研究項(xiàng)目是為測(cè)試停車(chē)誘導(dǎo)系統(tǒng)的效果而設(shè)計(jì)。停車(chē)場(chǎng)可變信息標(biāo)志指示牌(見(jiàn)圖2)分布于車(chē)輛進(jìn)入城市中心區(qū)的所有入口處(見(jiàn)圖3)，給進(jìn)城車(chē)輛提供停車(chē)場(chǎng)相關(guān)信息，以便車(chē)輛做出選擇。根據(jù)城市停車(chē)管理系統(tǒng)(the TownParking Manager)的經(jīng)驗(yàn)記錄，ITS 系統(tǒng)的設(shè)置是僅20%的駕駛?cè)俗裱＼?chē)誘導(dǎo)系統(tǒng)的建議，其余80%的駕駛?cè)藢Ⅰ傁蜃约旱氖走x停車(chē)場(chǎng)，若該停車(chē)場(chǎng)已滿(mǎn)，再改變方向駛向其他停車(chē)場(chǎng)。羅克代爾市和塔卡普納區(qū)的模型更加注重停車(chē)場(chǎng)的可達(dá)性，其次才是誘導(dǎo)功能。在羅克代爾市，停車(chē)場(chǎng)的位置選擇根據(jù)政策確定，即規(guī)劃分區(qū)時(shí)對(duì)停車(chē)場(chǎng)的位置予以限制，如：合同停車(chē)區(qū)域(contract parking areas)設(shè)于與工作有關(guān)而不是與購(gòu)物有關(guān)的分區(qū)。在塔卡普納區(qū)，停車(chē)限制政策較少，停車(chē)場(chǎng)可以與所有分區(qū)相連，因而減少了預(yù)先設(shè)定停車(chē)空間的情況。車(chē)輛到達(dá)某一停車(chē)場(chǎng)后會(huì)排隊(duì)等候，等待一定時(shí)間后，基于出行成本、步行成本以及停車(chē)成本會(huì)駛向其他停車(chē)場(chǎng)。塔卡普納區(qū)模型通過(guò)外接軟件控制器管理停車(chē)場(chǎng)車(chē)位，同時(shí)對(duì)車(chē)輛尋找停車(chē)場(chǎng)的條件進(jìn)行限定(尋找界限)，從而對(duì)車(chē)輛選擇停車(chē)場(chǎng)的過(guò)程進(jìn)行補(bǔ)充。尋找界限反映了駕駛?cè)嗽趯ふ彝＼?chē)位的過(guò)程中，在數(shù)量眾多的停車(chē)場(chǎng)間循環(huán)行駛的意愿，即設(shè)定駕駛?cè)藝L試找尋停車(chē)位的次數(shù)，之后，便放棄嘗試而駛向最有可能有空閑車(chē)位的停車(chē)場(chǎng)。車(chē)位控制器可監(jiān)測(cè)停車(chē)場(chǎng)的使用情況，任何停車(chē)場(chǎng)停滿(mǎn)車(chē)輛10 min 后會(huì)從控制器名單中清除。一旦有車(chē)輛從該停車(chē)場(chǎng)離開(kāi)，則會(huì)重新回到名單中供待停車(chē)輛選擇。3 首選停車(chē)場(chǎng)問(wèn)題首選停車(chē)場(chǎng)問(wèn)題出現(xiàn)在羅克代爾市和塔卡普納區(qū)模型中。當(dāng)車(chē)輛的首選停車(chē)場(chǎng)容量較小且很快就停滿(mǎn)時(shí)會(huì)出現(xiàn)首選停車(chē)場(chǎng)問(wèn)題。大多數(shù)駕駛?cè)嘶诔鲂谐杀咀钚∵x擇該停車(chē)場(chǎng)，但不得不改變路線(xiàn)駛向次選停車(chē)場(chǎng)?，F(xiàn)實(shí)生活中，即使知道該停車(chē)場(chǎng)通常停滿(mǎn)車(chē)輛，很多駕駛?cè)艘廊恢貜?fù)同樣的出行，因此不得不選擇一個(gè)有更多機(jī)會(huì)找到空閑車(chē)位的較大停車(chē)場(chǎng)作為首選。針對(duì)這一問(wèn)題，塔卡普納區(qū)提出了兩種解決方法：1)使用停車(chē)場(chǎng)車(chē)位使用情況控制器覆蓋駕駛?cè)说倪x擇，為駕駛?cè)颂峁┨娲＼?chē)場(chǎng)。2)對(duì)較小的停車(chē)場(chǎng)(車(chē)位數(shù)一般小于50 個(gè))進(jìn)行分組，同時(shí)調(diào)整停車(chē)場(chǎng)對(duì)出行目的地的覆蓋范圍和步行時(shí)間，以避免過(guò)多的駕駛?cè)税涯骋惶囟ㄍ＼?chē)場(chǎng)作為首選。羅克代爾市模型則通過(guò)細(xì)化需求矩陣來(lái)分配停車(chē)場(chǎng)，提供了另一種解決方法。按照駕駛?cè)藢?duì)出行目的地周邊停車(chē)場(chǎng)的熟悉度對(duì)矩陣做進(jìn)一步細(xì)化。若駕駛?cè)双@悉較小的停車(chē)場(chǎng)已停滿(mǎn)，便會(huì)避免使用它們，而把較大的停車(chē)場(chǎng)作為首選。4 仿真結(jié)果4.1 新維根市新維根市基礎(chǔ)模型基于周六下午的典型狀況進(jìn)行校準(zhǔn)，比較了未來(lái)年的兩個(gè)仿真，其測(cè)試方案包括城市中心區(qū)新規(guī)劃的開(kāi)發(fā)區(qū)。沒(méi)有停車(chē)誘導(dǎo)系統(tǒng)時(shí)，大量車(chē)輛在最有吸引力的停車(chē)場(chǎng)前排隊(duì)。有停車(chē)誘導(dǎo)系統(tǒng)的情況下，待停車(chē)輛則按照停車(chē)場(chǎng)容量更加均衡地分布，且大多數(shù)停車(chē)場(chǎng)會(huì)有空閑車(chē)位，從而減少尋找停車(chē)位的車(chē)輛，城市中心區(qū)道路上的車(chē)輛數(shù)也相應(yīng)減少。這一效果是在20%的駕駛?cè)俗裱＼?chē)誘導(dǎo)系統(tǒng)的情況下實(shí)現(xiàn)的。下一步進(jìn)行研究時(shí)，將擴(kuò)大ITS 系統(tǒng)的覆蓋范圍，并把某些路段設(shè)置為步行區(qū)。新維根市的仿真方案是基于2015 年的情況進(jìn)行的，城市中心區(qū)的詳細(xì)規(guī)劃可能會(huì)與仿真情況有所差異，所以，在評(píng)估設(shè)計(jì)方案的預(yù)期效果時(shí)進(jìn)行了保守解釋。盡管如此，仿真結(jié)果依然表明在新維根市投資建設(shè)停車(chē)誘導(dǎo)系統(tǒng)的方案是合理的，可以充分利用停車(chē)場(chǎng)的容量。4.2 羅克代爾市羅克代爾市模型針對(duì)計(jì)劃于2012 年實(shí)施的城市中心區(qū)改造的一部分進(jìn)行測(cè)試。主要包括：搬遷位于中心區(qū)的公共汽車(chē)站和政府辦公地點(diǎn)，拆除中心區(qū)的多層停車(chē)場(chǎng)，重新設(shè)計(jì)穿越中心區(qū)的A58 干路的主要交叉口。下一步研究將使用與塔卡普納區(qū)和新維根市模型類(lèi)似的外接軟件控制器，同時(shí)在路線(xiàn)選擇點(diǎn)安裝停車(chē)誘導(dǎo)設(shè)施，并考慮停車(chē)場(chǎng)車(chē)位的機(jī)會(huì)成本(opportunity cost)?？梢栽谠O(shè)置首選停車(chē)場(chǎng)之前將機(jī)會(huì)成本添加到每一停車(chē)場(chǎng)的一般化成本中，盡管需要通過(guò)數(shù)據(jù)調(diào)查對(duì)此進(jìn)行校準(zhǔn)，但在停車(chē)場(chǎng)選擇中考慮機(jī)會(huì)成本，可以將每一停車(chē)場(chǎng)可能的空閑車(chē)位完全納入選擇。4.3 塔卡普納區(qū)塔卡普納區(qū)S-Paramics 模型是塔卡普納中心區(qū)所有重要規(guī)劃申請(qǐng)和地區(qū)性規(guī)劃變更的交通運(yùn)行評(píng)估工具，以保證所有評(píng)估在同一仿真體系下完成。該方法已成功應(yīng)用于北岸市的另外兩個(gè)開(kāi)發(fā)區(qū)。已經(jīng)校準(zhǔn)的塔卡普納區(qū)停車(chē)場(chǎng)模型是其交通仿真模型的一部分，二者又是整個(gè)評(píng)估體系的一部分。不過(guò)，受最近經(jīng)濟(jì)滑坡的影響，該地區(qū)部分業(yè)主已停止?fàn)I業(yè)或是將物業(yè)出售，相關(guān)機(jī)構(gòu)也推遲了規(guī)劃、評(píng)估工作，但在經(jīng)濟(jì)復(fù)蘇時(shí)該體系即可使用。5 結(jié)論1) 停車(chē)設(shè)施規(guī)劃對(duì)減輕城市中心區(qū)的交通擁堵至關(guān)重要。新維根市研究表明，即便針對(duì)部分停車(chē)問(wèn)題采用某種解決方法，也能帶來(lái)相應(yīng)效果。羅克代爾市和塔卡普納區(qū)的測(cè)試結(jié)果顯示，在模型體系中同時(shí)包含停車(chē)策略，可以顯著影響設(shè)計(jì)方案的效果。2) 三項(xiàng)研究都表明把同一停車(chē)場(chǎng)的到達(dá)和出發(fā)車(chē)輛連接起來(lái)非常必要，但卻采用了三種不同的解決方法。三個(gè)模型中駕駛?cè)诉x擇停車(chē)場(chǎng)的方法也有差異，但都是以矩陣細(xì)化為基礎(chǔ)。通過(guò)設(shè)定停車(chē)費(fèi)用和限制條件來(lái)測(cè)試駕駛?cè)藢?duì)不同收費(fèi)政策的反應(yīng)。三項(xiàng)研究都設(shè)法解決首選停車(chē)場(chǎng)的問(wèn)題。3) 三個(gè)城市中心區(qū)從不同角度對(duì)停車(chē)場(chǎng)模型進(jìn)行了探討，對(duì)一些共同問(wèn)題提出了多種有創(chuàng)意的解決辦法，尤其是針對(duì)駕駛?cè)藢ふ彝＼?chē)位造成的交通擁堵問(wèn)題。這些研究表明利用微觀仿真，可以測(cè)試停車(chē)策略的效果。參考文獻(xiàn)：1 Joseph Straw. Rowland Dedicates Parking GarageN. New Haven Register, 20020911(B3).2 Donald Shoup. Cruising for Parking J. TransportPolicy, 2006, 13(6): 479486.3 Spotswitch Link, Spot Switch EB/OL. 201020100301. .4 Gaston Serge Tchang. Parking Policy to Improve Accessibility in Industrial AreasEB/OL. 20072010 03 01. /paper/parking-policy-to-improve-accessibility-in-industrialareas.5 SPP 172005 Scottish Planning Policy 17: Planning for Transport S.6 UKs Department for Transport. Traffic Advisory Leaflet ITS4/03 EB/OL. 20032010 03 01..uk/pgr/roads/tpm/tal/its/arkingguidanceandinformation.pdf.7 UKs Department for Transport. Transport Models TAG Unit 3.1.2 EB/OL. 20052010 03 01..uk/webtag/documents/expert/pdf/unit3.1.2.pdf.94_Planning urban car park provision usingMicrosimulationPete Sykes SIAS Ltd (UK), Falco De Jong Grontmij BV (NL), Richard Bradley ANSA Consultants (UK), GerardJennings MicroNet Limited (UK), Greig McDonnell North Shore Council (NZ)AbstractIn three different locations around the world, city planners have sought to investigate the effects on the road network of car park planning policy and accessibility. All have looked for methods to minimise urban congestion caused by drivers searching for a car park space. All have used an SParamics microsimulation model to test the design options. This paper describes how they went about it and what they achieved.104INTRODUCTIONThe provision of available car parking is one of the most contentious issues for city drivers. Car park spaces can be hard to find and expensive to use. There may be queues to get into the most convenient car parks which require drivers to move on to alternative car parks. Some city centre traders regard the lack of suitable car parking as a significant reason for shoppers to prefer out of town shopping centres. In New Haven Connecticut, Gov. Rowland at a ceremony celebrating the renovation of the citys largest car park in 2002 declared: if you dont have parking, nothing else works.1Car park hunting, the circulation of drivers looking for a parking space, can be a major contribution to city centre congestion. The proportion of cars searching for a space was found to be 26% when surveyed in Manhattan in 2006, while in Brooklyn it was 45%. The situation is not new. In 1927, a similar survey in Detroit found the figures to be 19% and 34% in separate locations 2. This long standing problem may at last be assisted by technology. While iPhone users can now notify each other as spaces become available 3, traffic planners can now take advantage of recent developments in traffic modelling, which demonstrate that car park access can be included in road traffic simulation models to support the design process. Car park location in urban planning policy is largely concerned with optimising the relationship between car parks, drivers and their destinations. Charging regimes may be used to reduce localised inconvenience caused by parked cars and to favour one class of driver over another in allocating spaces. The perceived benefits include improvements to a citys commercial centre through better accessibility for the target consumer. Policies may be supply- led by actively managing spaces or demand-led by simply increasing the number of spaces 4. Increasingly, active management policies are used to ration spaces and encourage sustainable travel patterns 5.Urban planning policy considers the charging regimes for car parks. Transport planning policy complements this and considers access to the car parks. It is concerned with the relationship between car parks, the road network and congestion.Accessibility of car parks is addressed in road design guidelines. UK Department for Transport advice on parking guidance and information systems includes reports of case studies that show that there are quantifiable benefits to be derived from installing variable message signs indicating car parking space availabilty 6. Benefits are described as quantitative, in terms of time saved, and qualitative in terms of public image and driver safety. WebTAG 7 guidance touches on the subject briefly in discussion of travel costs by including parking “costs”(which notionally include time spent searching and queuing for a space and walking to the final destination). The authors perception is that car park accessibility isnormally considered after the urban design is complete and car park policy has been determined. The missing link is in the transport planning policy contribution to the initial design of urban areas with respect to car park provision and accessibility. This apparent deficiency has recently been addressed in three different locations reported here. Each has sought ways to investigate the effects on the road network of car park planning policy and accessibility. All have looked for methods to minimize urban congestion caused by drivers searching for a car park space. All have used an S-Paramics microsimulation model to test the design options.A study in Nieuwegein (The Netherlands) modelled a large expansion in travel demand and the provision of car park spaces for a major town centre redevelopment, where Saturday afternoon shopping was the critical period. It incorporated ITS within the microsimulation model to deliver information to drivers on availability of spaces and routes to car parks. Another study, in Rochdale (England), models the distribution of spaces in conjunction with major town centre development plans. The goal is to optimise the provision of car parks with respect to adjacent land use and to minimise town centre congestion by considering car park access early in the design process. The third study, in Takapuna (New Zealand), is also investigating the effect of city centre expansion. It uses bespoke software to model the car park demand and a microsimulation model to assign the demand to the network. Once again the goal is to understand the effect of car park policy and minimise city centre congestion.CAR PARK MODELLING IN MICROSIMULATIONTypical design option tests for a microsimulation model include changes to road layout, public transport priority schemes, optimisation of signals, or changes in demand. Each individual vehicle in the simulation will react to these changes, and the congestion they cause, as it moves to its destination. When testing the effect of car park policy decisions, the emphasis moves from examination of the effect of changes to the road network to examination of the effect of changes in the destination for that part of the trip undertaken in a car. The simulation model must now include the capability to distinguish between the drivers destination and the vehicles parking location and make dynamic choices between these locations.Figutr 1：Rochdale city centre carparksArrivalsCar parks are an entity within the microsimulation model, and are linked to zone destinations and car parks may serve more than one zone. Allocation of vehicles to car parks is undertaken by limiting car park access to specific trip purposes. The model includes car parking charges and the distances between car parks and associated zones as components of the generalised trip cost. As each vehicle type may have different cost coefficients, the modeler may differentiate between drivers who will accept a longer walk and those who will accept a higher charge. If a car park is full then vehicle drivers within the simulation wait at the entrance for a predetermined time, after which they re-assess their choice of car park and possibly proceed to another. Using an external software controller it is possible to monitor car park occupancy within the simulation and change a vehicles destination before it reaches the queue.As an example of how this methodology can be used to implement a car park policy model, consider a city centre zone with a mix of retail and commercial use with several car parks available within reasonable walking distance. Drivers will have a preferred location based on their proposed length of stay and the car park charging structure.Some drivers may have a contract for permit parking. A car park may have multiple adjacent entrances, each coded with a restriction to force vehicles to accept the appropriate parking charge. The effect in the simulation is that short stay vehicles enter car parks closer to their destination or with a lower charge. The long stay vehicles enter via the entry links with the higher charges or accept a longer walk time. The modeller can test responses to car parking changes by adjusting entry charges for different car parks or by varying the level of permit parking. Land use changesmay be modelled by adjusting the proportion of driver and vehicle types using a particular zone and related car parks.DeparturesThe assignment of all vehicles to an S-Paramics road network is controlled by a detailed (5 minute) time release profile. In its simplest form of use, the journey origin car park is determined by finding the minimum journey cost,which includes the walk time, or vehicles may simply be released in proportion to the size of the car park.If more control is required, such as the ability to match departures to arrivals at the same car park, the release may be triggered by an external software controller linked to the simulation model which uses an algorithm to determine when to release vehicles and where they originate on the network. This may be associated with a car park occupancy monitoring system and be used to match vehicle arrivals with a subsequent departure.NIEUWEGEIN PLANNED DEVELOPMENTSNieuwegein is a town just to the south of the city of Utrecht in the centre of the Netherlands with good economic prospects. To make the most of this, the municipality wants to restructure their city centre to include new developments. New multi-story car parks are planned to cope with the increased demand for parking spaces and a system for dynamic parking advice will attempt to minimise queueing at the car park entrances.Grontmij was asked to build an S-Paramics model of the city centre to review the effects of the new developments on the citys road network including the parking advisory system. The results of the simulation showed congestion at the three car parks closest to the city centre. This w