著：（巴西）瓦尼亞 · 切卡托 譯：黃鄧楷

機動性是當代城市高效運作與可持續(xù)發(fā)展的基本要求。盡管交通環(huán)境目前仍存在由犯罪和恐怖主義威脅等造成的安全問題，但公共交通仍是城市實現(xiàn)經(jīng)濟繁榮和可持續(xù)交通的關(guān)鍵。詳細了解安全環(huán)境的基本特征，對于城市公共交通可持續(xù)性，尤其是地鐵系統(tǒng)可持續(xù)性的深入討論至關(guān)重要。以往研究很少涉及地鐵站設(shè)計與發(fā)生犯罪活動及擾亂公共秩序行為概率的關(guān)系。切卡托等[1]利用地鐵站的整合數(shù)據(jù)將關(guān)注點聚焦于站點的犯罪案件，使我們留下了不同時空下城市整體風險的簡單印象。地鐵站及其出入口等附屬部分的環(huán)境設(shè)計會影響“監(jiān)視”（surveillance）作用及犯罪機會。這意味著地鐵站的事件發(fā)生不僅取決于其物理環(huán)境，也受個體在交通節(jié)點移動時的人類活動影響。

筆者通過評估瑞典斯德哥爾摩和巴西圣保羅地鐵系統(tǒng)的犯罪活動及擾亂公共秩序行為案例，探討相關(guān)經(jīng)驗教訓。對比2個國家的地鐵系統(tǒng)的時空犯罪模式及上述案例的研究結(jié)果，結(jié)合切卡托提出的概念性理論框架[2]，總結(jié)環(huán)境對犯罪活動及擾亂公共秩序行為的影響，這些都是至關(guān)重要的，因為預防地鐵犯罪的方法是防范于未然，其關(guān)鍵是確定特定時空下特定犯罪類型的潛在驅(qū)動因素。情景犯罪預防策略強調(diào)減少犯罪機會，即通過改變環(huán)境及其管理方式，從而預防犯罪的發(fā)生[3]。

筆者總結(jié)并借鑒切卡托及其同事在瑞典、巴西等國的研究工作[2,4-7]，探討了分析模型的理論原理，構(gòu)思2個案例研究并描述其研究方法與結(jié)果，最后強調(diào)犯罪水平及犯罪模式在2種交通環(huán)境中的共性和差異。

1 理論背景

1.1 犯罪的時間模式

犯罪機會的時空分布既不是均勻的，也不是隨機的[8]，但的確是遵循人類活動規(guī)律分布的。犯罪的時間分布與人們的日?；顒佑嘘P(guān)。地鐵站每天都會聚集大量人流。日常活動理論[9]認為個體活動與日常習慣是有規(guī)律的，且其活動模式不斷重復。大多數(shù)犯罪活動取決于空間和時間的相互作用：犯罪者的動機、合適的目標、缺乏有能力的監(jiān)察人。由于在特定時間地鐵站是人群聚集的地方，至少是在特定時段[1]容易成為犯罪地[10]。日?；顒永碚撜J為個體在戶外活動上所花的時間越多，越有可能創(chuàng)造更多犯罪機會。因此，交通節(jié)點等“犯罪吸引體”（crime attractors）時刻都在為犯罪行為的發(fā)生提供機會。既往研究早已證實犯罪行為隨著月份和季節(jié)而波動，但其模式取決于具體的犯罪類型[11]。

1.2 地鐵站犯罪的空間模式

地鐵站犯罪（及擾亂公共秩序行為）受站點的物理和社會環(huán)境特征、當下環(huán)境和社區(qū)環(huán)境特征、站點和社區(qū)在城市中的相對位置所影響。這一概念模型依賴于環(huán)境犯罪學、情境犯罪預防、環(huán)境設(shè)計預防犯罪（CPTED）理論[2]。

1.2.1 地鐵站的物理和社會特征

地鐵站點對犯罪活動的脆弱性（vulnerability）取決于其物理環(huán)境及特定環(huán)境下發(fā)生的社交類型。物理環(huán)境是指車站的硬件設(shè)施，包括所有肉眼可見的東西。地鐵站點可能會因尺度（例如，交通樞紐站點往往較大）、類型（例如，市中心地鐵站通常是地下的，而偏遠的站點通常建在地上）或樣式（例如，現(xiàn)代的透明墻）而有所差異，但仍然遵循一些基本標準。

地鐵站包括出入口區(qū)域（如隧道、樓梯、電梯、商店和餐廳），站廳（如售票亭、自動閘機和商鋪），過渡區(qū)域（如樓梯和電梯）和站臺 （如單站臺和多站臺），并通過周圍環(huán)境（如街道和停車場）與城市相連。不管布局如何，地鐵站通常由站臺、過渡區(qū)域、站廳、出入口區(qū)域和周圍環(huán)境5部分組成：站臺即列車到達、乘客進出車廂、候車的區(qū)域；過渡區(qū)域通常由連接站廳和站臺的樓梯和電梯組成；站廳一般包括自動閘機和售票亭組成的開放區(qū)域，并連接出入口；站廳和出入口區(qū)域一般都設(shè)有商鋪；出入口區(qū)域是直接從街道、門口、樓梯或隧道進入站廳的區(qū)域；周圍環(huán)境是從地鐵站出入口直接看到的，離出入口只有幾米距離的區(qū)域。皮薩和肯尼迪認為進出地鐵站的便捷性及乘客對站點的不熟悉，導致犯罪機會的增加[12]。長期研究表明站點（和公交站）的照明、設(shè)計、區(qū)位和安全硬件等物理特征可減少犯罪機會[6-7,13-16]。

1.2.2 地鐵站和社區(qū)環(huán)境

地鐵站安全受社區(qū)環(huán)境影響的因素有2種：1）周圍地區(qū)的土地利用類型及其吸引的社會活動；2）該社區(qū)居住或工作的人口和社會經(jīng)濟特征。肖和麥凱[17]最早在芝加哥開展鄰里條件和犯罪的關(guān)系研究，其成果后來成為社會解體論的主要參考。社會解體論將多種犯罪類型和非正式的社會弱控制力聯(lián)系起來，并認為犯罪的發(fā)生與其區(qū)位無關(guān)。因此，一般來說，社會控制力弱的貧困地區(qū)犯罪率較高，這些地區(qū)的地鐵站犯罪率也較高[2]。但也有例外，如拉維尼指出華盛頓地鐵站犯罪率與站點所在的人口普查區(qū)的犯罪率無關(guān)[14]。

1.2.3 城市環(huán)境中的地鐵站

地鐵站規(guī)劃通常都是盡可能地容納更大的客流承載量，站點的設(shè)置往往位于住宅區(qū)、工作地點、工業(yè)區(qū)或商業(yè)中心的步行距離內(nèi)。交通節(jié)點的這種中心性易導致犯罪。不同土地利用類型會影響該區(qū)域的社交活動，進而影響犯罪的空間分布。環(huán)境犯罪學已表明市中心比城市其他地區(qū)更易引起犯罪[7,18-21]。因此，可以推斷出市中心地鐵站比起市郊地鐵站更易導致犯罪活動和擾亂公共秩序行為的發(fā)生。或者說，地鐵終點站由于經(jīng)常連接大客流的交通節(jié)點，或與犯罪較頻發(fā)的停車場和商業(yè)區(qū)相連，比沿線其他中途站更易導致犯罪發(fā)生。

2 案例研究

2.1 2個地鐵系統(tǒng)

2.1.1 斯德哥爾摩地鐵系統(tǒng)

斯德哥爾摩地鐵由100個連接著巴士和通勤列車的車站組成，其中47個地下車站（大多位于市中心），53個地上車站，共3條地鐵線路：紅線、綠線和藍線（圖1-1）。本研究將分析整個斯德哥爾摩地鐵系統(tǒng)中的犯罪活動和擾亂公共秩序行為事件，但由于數(shù)據(jù)限制，在建模階段僅使用位于斯德哥爾摩市區(qū)的82個車站數(shù)據(jù)。斯德哥爾摩位于瑞典的東南岸，市區(qū)在群島上蔓延，因此水占據(jù)了大部分城市景觀。這些島嶼通過公路和高效的公共交通系統(tǒng)（包括公共汽車、地鐵、鐵路系統(tǒng)和通勤列車）連接起來；斯德哥爾摩由于地處北歐，寒冷黑暗的冬季限制市民的戶外生活，春夏季卻有相當長的白天時間。2016年斯德哥爾摩居民人口為910 000，它是瑞典的首都、人口最多的城市，也是斯堪的納維亞地區(qū)人口最多的城市。

2.1.2 圣保羅地鐵系統(tǒng)

研究對象為圣保羅地鐵（大都會圣保羅）的62個車站，不包括一些擴建車站（共65個車站）。它是圣保羅市主要的、巴西規(guī)模最大、南美洲第二規(guī)模的快速交通系統(tǒng)（圖1-2）。圣保羅于1968年興建第一條地鐵線，而今已有5條地鐵線路（74km，圖1-2），每天154輛列車從04：40運行到24：00（周六運營至次日01：00），日載客量高達4 600 000。地鐵在擁有1 200萬人口的圣保羅市內(nèi)運行，市內(nèi)也有一些公司提供通勤列車服務(wù)。圣保羅是巴西最大的城市、南美洲最大的大都市區(qū)，同時也是巴西、西半球及南半球人口最多的城市。

2.2 數(shù)據(jù)和方法

斯德哥爾摩地鐵的犯罪活動及擾亂公共秩序行為案件的數(shù)據(jù)通過斯德哥爾摩公共交通部（2006—2009年）和警方的統(tǒng)計數(shù)據(jù)（本研究不討論警方數(shù)據(jù)）獲取。根據(jù)每個站點客流量計算出每1 000名乘客的犯罪率，而不是直接使用犯罪案件的原始數(shù)據(jù)。通過將現(xiàn)場調(diào)研（清單）的數(shù)據(jù)輸入到電子表格，并將其與土地利用、犯罪數(shù)據(jù)、人口統(tǒng)計數(shù)據(jù)、社會經(jīng)濟數(shù)據(jù)等導入到地理信息系統(tǒng)（GIS），其中地鐵站點及犯罪數(shù)據(jù)被設(shè)置為點數(shù)據(jù)（point data），斯德哥爾摩人口統(tǒng)計和社會經(jīng)濟數(shù)據(jù)與小單元統(tǒng)計數(shù)據(jù)（small unit statistics）相關(guān)聯(lián)。為了評估周圍環(huán)境對每個站點的犯罪活動及擾亂公共秩序行為案件的影響，人工繪制了一些容易引發(fā)犯罪的土地利用類型的位置：ATM機、學校、警察局、國營酒類零售店。研究是基于全面的田野調(diào)查與地理信息系統(tǒng)的技術(shù)與建模[2]。

圣保羅地鐵的犯罪數(shù)據(jù)主要來自圣保羅地鐵運營商（按類型和站點匯總，2013—2015年），大都會警察局和民警掌握的（乘客2010—2015年報告的案件）的數(shù)據(jù)，以及短信服務(wù)（2014—2015年），該服務(wù)用于舉報乘坐地鐵期間發(fā)生的犯罪和其他事故。犯罪案件包括財產(chǎn)犯罪和暴力犯罪，如盜竊、搶劫和各種暴力行為（包括性侵及性騷擾）。為了案例數(shù)據(jù)的統(tǒng)一，乘客人數(shù)同樣通過地鐵運營商獲取，包括站點工作日高峰和非高峰時段的乘客人數(shù)以及工作人員總數(shù)（安保和總體）。研究將地理信息系統(tǒng)（GIS）與通過谷歌街景、其他二手數(shù)據(jù)收集的犯罪記錄整合成回歸模型[5]。

1-2 圣保羅地鐵系統(tǒng)S?o Paulo metro map

1-1 斯德哥爾摩地鐵線路圖Stockholm metro map

3 結(jié)果

3.1 犯罪和擾亂公共秩序罪的性質(zhì)

由于記錄方式的差異顯著影響地鐵系統(tǒng)的犯罪及擾亂公共秩序罪案件的水平，因此難以對不同地鐵系統(tǒng)的犯罪數(shù)據(jù)進行對比。犯罪案件的具體數(shù)量也因數(shù)據(jù)來源而異，例如，斯德哥爾摩官方警察統(tǒng)計數(shù)據(jù)中的財產(chǎn)犯罪比斯德哥爾摩公共交通公司記錄的要多。下文從2個公共交通公司提供的數(shù)據(jù)庫討論一些主要趨勢，但嚴格來說，由于記錄方式和數(shù)據(jù)收集時間的不同，對比數(shù)據(jù)時應謹慎。

總的來說，地鐵站的大多數(shù)事件（不一定是犯罪）都會影響乘客的安全感。較常見的違法行為是對旅客和工作人員的威脅恐嚇和人身攻擊，其中斯德哥爾摩地鐵的違法記錄比圣保羅更多一些。財產(chǎn)犯罪在圣保羅地鐵系統(tǒng)違法行為中占了最大的比例，可以分成2種：對人和對物。后者包括車廂和車站內(nèi)的盜竊行為（如手機盜竊相對來說在圣保羅更常見）、在商店和食品店偷竊以及在地鐵站周邊（停車場或街道）較常見的單車和汽車偷竊行為。

在圣保羅地鐵系統(tǒng)中，62%的案件是盜竊和搶劫等財產(chǎn)犯罪，打架斗毆及其他暴力犯罪約占20%，性侵犯及性騷擾也有記錄[5]。值得注意的是，這個數(shù)據(jù)庫不包括如對財產(chǎn)的物理傷害、乞討及其他擾亂公共秩序行為等犯罪類型（部分通過其他方式收集的，如短信服務(wù)）。被記錄的案件是斯德哥爾摩地鐵系統(tǒng)記錄不可缺少的一部分，約占整體案件的80%。向交通公司報告的案件中有20%是犯罪行為，其中多為打架斗毆（約40%）、破壞行為及威脅，其次是其他暴力行為。暴力行為的受害者基本上都是工作人員、警衛(wèi)、司機或乘客。警方數(shù)據(jù)顯示有相當一部分搶劫案件發(fā)生在地鐵站，盡管大多都是發(fā)生于地鐵站內(nèi)的商店或超市等地點。絕大多數(shù)都是非法活動或反社會行為的社會秩序混亂案件，如隨地小便、吸毒、街頭滯留、公共場所酗酒、車廂或車站內(nèi)的緊急剎車、滅火器或消防水帶等裝置的不正當使用[2]。

2 不同犯罪類型的時間分布情況 （按每小時計）Distribution of crime by hour of the day (counts per hour)

表1 不同季節(jié)的暴力犯罪情況，斯德哥爾摩，2006—2008年Tab. 1 Violent crimes by season, Stockholm, 2006—2008

表2 車站特征、社區(qū)環(huán)境及城市背景Tab. 2 Characteristics of the stations, neighbourhood surroundings and city context

3.2 犯罪和擾亂公共秩序罪的時間分布

分析交通環(huán)境中犯罪的時間分布是制定有效預防犯罪措施的基礎(chǔ)。2個地鐵系統(tǒng)高峰時段都有暴力和盜竊行為發(fā)生，但在時間分布上不盡相同。圣保羅地鐵的暴力和盜竊行為大多發(fā)生在早晨和傍晚（早晨08：00—09：00左右及傍晚18：00—19：00），而斯德哥爾摩地鐵犯罪行為的高峰時段隨犯罪類型而異：盜竊行為在下午14：00—15：00間達到峰值，而暴力行為往往發(fā)生于午夜后（圖2）。

斯德哥爾摩地鐵周末和節(jié)假日的違法行為比工作日要多得多，這可能是因為周末和節(jié)假日時人們經(jīng)常參加如派對、喝酒等更容易吸引犯罪的“隨機活動”，而工作日時其日常活動大多為“固定活動”[13]。圣保羅地鐵的犯罪案件數(shù)量因犯罪類型而異，但總體是遵循每天上下學、上下班等日常活動的固定模式。例如，性侵犯或性騷擾大多發(fā)生于工作日上下班途中（周一和周二占20%，而周六僅6%），其峰值在早晨08：00—09：00及傍晚18：00—19：00的高峰時段[5]，這期間大多數(shù)車廂和線路都擁擠不堪。

盡管圣保羅地鐵犯罪案件的季節(jié)性變化需要更長的時間來測得，但結(jié)果表明巴西冬季6、7月的案件數(shù)量略有增加。斯德哥爾摩地鐵暴力犯罪（如搶劫、打架斗毆、威脅）也呈季節(jié)性變化，且集中于瑞典溫度較高的月份（表1）[22]。值得注意的是2個城市的地理環(huán)境截然不同：瑞典斯德哥爾摩位于斯堪的納維亞半島，冬季漫長且黑夜時間長；而圣保羅位于年平均氣溫達21℃的熱帶國家巴西。這些氣候差異必然會對人們的日常活動的行為模式有影響，進而影響其交通環(huán)境的犯罪率。

3.3 犯罪和擾亂公共秩序罪的空間分布

上述2個城市的地鐵系統(tǒng)都表明市中心站點犯罪案件數(shù)量較多，但如果依據(jù)每個站點日客流量來計算，犯罪活動及擾亂公共秩序行為的比率卻有不一樣的結(jié)果。研究利用不同犯罪類型的數(shù)量與每1 000位乘客的比率得出相應犯罪率，而不是直接使用原始數(shù)據(jù)，因而獲得了更加有趣的犯罪空間分布。結(jié)果表明，地鐵線路終點站比起市中心的站點更容易引起犯罪（市民廣場站和斯堪斯圖爾站的盜竊類型除外）。更有趣的是，休斯塔、法斯塔灘、黑瑟碧灘、魏林比和哈格賽特拉等地鐵站（均為外圍站點）在各種犯罪類型上都顯示出較高的比例，這一點對預防犯罪措施的制定非常有用。圣保羅地鐵站的犯罪空間模式也是相似的，但各種犯罪類型都比較集中在市中心地鐵站。市中心3km范圍內(nèi)的地鐵站犯罪率較高，且犯罪率以市中心（例如帕拉伊蘇站和利貝爾達迪站）的塞（Sé）車站為中心發(fā)生距離衰減分布。區(qū)域交通樞紐站在以日客流量為基準計算犯罪率后也表現(xiàn)出較高的犯罪率（例如布拉斯站，帕爾梅拉斯——巴拉達豐站、塔圖普站）。

部分地鐵站對特定犯罪類型有較高的聚集性。如斯德哥爾摩的云客比站、韋斯特托普站和諾斯堡站分別存在較多的暴力、偷竊、破壞行為。其中部分地鐵站位于高犯罪率地區(qū)，這些地區(qū)往往屬于混合土地使用地區(qū)，靠近商業(yè)區(qū)，或是人流聚集的終點站。圣保羅的犯罪聚集性并不表現(xiàn)在地鐵站點上，而在性騷擾這一犯罪類型上，如性暴力案件大多聚集在最繁忙的中心站點及各種犯罪滋生的站點[5]。已有學者對上述2個地鐵系統(tǒng)不同線路的犯罪案件的變化進行對比研究[5,23]。

3.4 犯罪及擾亂公共秩序罪的水平

利用上述提到的概念模型，將2個地鐵系統(tǒng)的犯罪和擾亂公共秩序罪案件進行建模，建立地鐵站的物理和社會環(huán)境特征（由于數(shù)據(jù)限制，斯德哥爾摩的模型比圣保羅的詳細）、周圍環(huán)境特征及站點和社區(qū)在城市中的相對位置的函數(shù)。筆者探討2個案例研究結(jié)果的共性，值得注意的是在得出任何結(jié)論之前，由于數(shù)據(jù)的限制，斯德哥爾摩和圣保羅地鐵的建模策略稍有不同。

2個地鐵系統(tǒng)的結(jié)果均表明站點的環(huán)境屬性、其所在的社區(qū)類型及城市背景都影響犯罪機會，但這些影響因素因地鐵系統(tǒng)自身因素、犯罪類型及時間而有所差別。對一些獨立的或與其他因素糅合的影響交通節(jié)點犯罪機制的總體特征進行了總結(jié)（表2）。站點是否位于市中心是影響2個地鐵系統(tǒng)犯罪水平最重要的因素之一，市中心往往犯罪的發(fā)生更加集中。然而，斯德哥爾摩地鐵的線路終點站也容易導致犯罪發(fā)生。2個案例的另一個共性是地鐵站周邊土地利用的影響，特別是一些高風險的設(shè)施（如餐館）或能阻止犯罪和擾亂公共秩序罪的設(shè)施（如警察局）。值得注意的是，由于圣保羅地鐵站室內(nèi)設(shè)計的相關(guān)信息有限，其建模受到一定影響。然而，我們發(fā)現(xiàn)2個案例研究中有一些特征反復出現(xiàn)，如直接影響可視性（visibility）和監(jiān)視程度（surveillance）的黑暗角落。下面我們更詳細地討論每個案例研究的具體情況。

就斯德哥爾摩的犯罪活動及擾亂公共秩序行為的比率而言，監(jiān)控和照明特征的變量對犯罪率有30%的影響，當其他正式社會控制（formal social control，即100m范圍內(nèi)警察局的數(shù)量）、距離市中心的距離、城市背景被添加到模型時，其犯罪率上升到了52%。就暴力犯罪的比率而言，當?shù)罔F站周圍環(huán)境的變量（如開放的入口、距離市中心的距離、人口密度）被添加到模型時，模型的擬合度幾乎翻倍。這些變量對偷竊和搶劫等財產(chǎn)犯罪的波動也起到一定的影響[1,13]。

對于圣保羅總犯罪率來說，車站的室內(nèi)特征及其位置因素解釋了犯罪率30%的變化。比起暴力犯罪，市中心地鐵站更容易發(fā)生盜竊和搶劫等財產(chǎn)犯罪。大量閉路電視和工作人員、物理和社會干擾及黑暗角落的存在更容易造成暴力犯罪。同樣地，由于靠近購物中心的區(qū)域與城市網(wǎng)絡(luò)連接良好，可達性較高但規(guī)模相對較小，且被更富裕的社區(qū)包圍（可能更靠近自行車停車場或餐廳）[5]，這些站點也容易聚集暴力犯罪。

4 斯德哥爾摩和圣保羅地鐵系統(tǒng)的經(jīng)驗總結(jié)

地鐵車站是容易導致犯罪發(fā)生的地方，而且某些車站往往比其他車站更容易發(fā)生犯罪活動和擾亂公共秩序行為，且這種脆弱性（vulnerability）會隨時間而改變。地鐵站的大多數(shù)犯罪都是隨時間而波動的，他們往往在一天、一周或一年的特定時段更容易發(fā)生。這些時間上的波動往往和人們的日?；顒佑嘘P(guān)[24-25]。哈里斯[26]等對這種時間波動提出了另一種解釋，他認為人們壓力的表現(xiàn)可能存在滯后現(xiàn)象，壓力在白天積累，隨后在人們下班后去別的地方時壓力外化并爆發(fā)。這些發(fā)現(xiàn)與既往研究有著類似的結(jié)論：人們在閑暇時間相遇時更容易發(fā)生沖突。然而，這些沖突也會發(fā)生在工作日地鐵車廂內(nèi)上下班或上下學的乘客之間，如偷手機、扒竊等財產(chǎn)犯罪，或擁擠車廂內(nèi)的沖突（爭奪位置或性騷擾）等暴力犯罪。

地鐵站的犯罪機會取決于站點的環(huán)境屬性、社區(qū)環(huán)境及其區(qū)位。這些研究結(jié)果為環(huán)境犯罪理論提供了支持：環(huán)境特征（從站臺及車站的照明和閉路電視等微觀環(huán)境到社區(qū)與城市環(huán)境等宏觀環(huán)境）及犯罪行為之間是存在聯(lián)系的，即乘客在乘坐地鐵時暴露的環(huán)境及其特征與犯罪行為有關(guān)[7,9,17,27]。從2個案例研究可知，盡管地鐵系統(tǒng)的環(huán)境特征有所差異，地鐵載客量都會影響站點的犯罪機會。因此，在提出任何預防犯罪干預措施之前，我們必須非常詳細地記錄犯罪案件的時間和地點（例如高峰和非高峰時段、不同車站、站點不同的位置、車廂）[1]。

未來研究應重視信息通信技術(shù)的使用以提高機動性和安全性。移動傳感器及相關(guān)技術(shù)的使用帶來了一些新的研究問題，如特定個體的移動數(shù)據(jù)可能有助于了解地鐵站點環(huán)境與安全感之間的關(guān)系。通過移動傳感器收集的數(shù)據(jù)有助于研究特定時間特定地點乘客安全感低下的問題。

5 結(jié)論

研究在控制不同的案例數(shù)據(jù)和研究方法前提下，對比瑞典斯德哥爾摩和巴西圣保羅地鐵系統(tǒng)犯罪案件在時間和空間上的分布情況，其中最重要的結(jié)論是地鐵系統(tǒng)的安全不僅取決于地鐵站的自身條件，也受站點在城市中區(qū)位的影響。這意味著每個利益相關(guān)方都有責任確保乘客的安全得到法律的保障。他們必須保護乘客在整個乘車過程中的安全。這便需要通過各方合作來確保車廂內(nèi)、車站內(nèi)，以及乘客往返于交通節(jié)點的環(huán)境安全。然而，在車站層面仍有很多事情可以做，為此需要非常詳細地記錄犯罪案件的時間和地點，并考慮站點客流量的差異。這意味著我們需要對犯罪率高的特定地鐵站及時間段采取特別措施，尤其是高峰期，2個案例均表明市中心地鐵站在擁擠時更易發(fā)生犯罪。結(jié)果還表明，需改善環(huán)境的監(jiān)視作用（如消除黑暗的角落等），尤其是在商業(yè)區(qū)、中心及外圍站點。且無論采取何種預防犯罪措施都必須考慮到每種犯罪類型的時間和空間分布狀態(tài)。

除了處理地鐵系統(tǒng)安全問題的管理者之間的合作帶來的挑戰(zhàn)之外，還需要關(guān)注用戶需求，尤其是那些由性別、年齡及殘疾引起的特別需求。研究交通環(huán)境中的受害度和安全感不僅應考慮乘客的年齡或性別，更應考慮某些特殊群體的內(nèi)在特征。作為一名貧窮的殘疾人會使其“不利條件相互加成”從而影響其成為受害者的可能性和（或）他（她）體驗世界的方式。僅以性別為例，流動性和安全性在個體性別上是有差異的[28]，然而公共交通系統(tǒng)仍采用性別中性政策。

地鐵犯罪的預防必須考慮到具體的國家和城市問題。例如，圣保羅地鐵系統(tǒng)無法滿足客流承載量的需求，公共汽車、貨車、通勤列車和地鐵都無法滿足乘客的機動性。圣保羅地鐵站的安全狀況和擁擠程度反映了更為根本的問題，即保障每個人乘坐公共交通的權(quán)利。這不僅僅與巴西或南美的背景相關(guān)，更是關(guān)乎全世界數(shù)百萬乘客的現(xiàn)實問題。由于大多數(shù)的交通環(huán)境數(shù)據(jù)來自于北美和西歐的研究，因此迫切需要對那些城市不斷擴張的國家的安全狀況也進行評估，尤其是非洲和亞洲的國家。未來研究應揭示安全交通系統(tǒng)的具體挑戰(zhàn)并反映乘客的安全需求。

文章以斯堪的納維亞地區(qū)及南美地區(qū)為背景，對相關(guān)地區(qū)既往地鐵安全研究的缺失進行補充。筆者通過強調(diào)瑞典和巴西地鐵系統(tǒng)的共同點，為交通安全研究做出一定貢獻，但各地區(qū)安全環(huán)境措施的制定應當參照當?shù)靥囟ò踩珬l件的研究結(jié)果。盡管存在一定的局限性，但筆者考慮到地鐵站的環(huán)境屬性，社區(qū)環(huán)境及其在城市中的位置，向更好地了解地鐵系統(tǒng)安全狀況又邁進了一步。

注釋：

① 圖1–1由斯德哥爾摩地鐵運營商提供（2016年）；圖1–2由圣保羅地鐵運營商提供（2016年）；圖2來源于2006年3月—2009年2月斯德哥爾摩公共交通數(shù)據(jù)庫和2013—2015年圣保羅地鐵運營商數(shù)據(jù)庫。

② 表1數(shù)據(jù)來源于參考文獻[28]；表2數(shù)據(jù)來源于參考文獻[2, 5]。

（編輯/王晨宇 王一蘭）

Mobility is a basic requirement for efficient and sustainable modern cities. Public transportation is key for achieving economic prosperity and sustainable mobility in cities, despite current challenges such as safety concerns caused by crime and terrorist threats in these environments. Having detailed knowledge about the nature of the safety conditions is essential for an informed debate on urban sustainability in public transportation, in particular, in metro systems.A very limited number of studies have focused on the relationship between metro station design and rates of crime and disorder. Focusing on crime in metro stations provides us with snapshots of a city’s risk over time and space using aggregated data by station[1].The environmental design of a metro station and its auxiliary sections, such as entrances and exits, influences surveillance and may affect opportunities for crime.This means that what happens at the stations depends not only on their physical environments, but also on the human activities that take place at these transportation nodes when individuals are on the move.

In this article, we discuss lessons learned from assessing crime and public disorder in two major metro systems: Stockholm (Sweden) and S?o Paulo(Brazil). We compare temporal and spatial patterns of crime in these metro systems in two national contexts. We also attempt to compare findings from these two case studies to reason about the influence of the environment on crime and public disorder,drawing from a conceptual theoretical framework suggested by Ceccato[2]. This is important since one way to prevent crime in metro environments is by making it difficult to happen. In order to do that,a key element in this approach is identifying the underlying drivers of a particular type of offence in time, and in each particular environment. Situational crime prevention focuses on creating strategies to reduce crime opportunities. These strategies focus on changing the environment and how it is managed,thus closing off opportunities for crime[3].

This article summarises and builds on the work done by Ceccato and colleagues in Sweden, Brazil and elsewhere in international research[2,4-7]. The structure of the article is as follows. We start by discussing the theoretical principles of the analytical model, and then we frame the two case studies followed by a description of the methodology and results obtained. The article ends by highlighting commonalities and differences, in terms of crime levels and patterns and how they relate to these two major transit environments.

1 Theoretical background

1.1 Temporal patterns of crime

Crime opportunities are neither uniformly nor randomly distributed in space and time[8], but they do follow rhythmic patterns of human activities.Temporal variations of crime are related to people’s routine activity. Underground stations concentrate people on a daily basis. Routine activity theory[9]suggests that an individual’s activities and daily habits are rhythmic and consist of patterns that are constantly repeated. Most crimes depend on the interrelation of space and time—that is, on spatialtemporal variations in offenders’ motivation, and on the presence of suitable targets and responsible guardians. Since metro stations are places where people converge at particular times, they act as crime generators[10], at least during particular time windows[1].Routine activity theory suggests that the more outdoor activities in which individuals participate, the more criminal opportunities. Thus, areas that act as crime attractors, such as some transportation nodes,provide opportunities for criminal acts regardless of day of the week or month of the year. Monthly and seasonal variations in crime in transport nodes have long been documented in the international literature but patterns depend on the type of crime[11].

1.2 Spatial patterns of crime in metro stations

Crime (and public disorder) at a metro station is determined by its physical and social environmental attributes; the characteristics of the immediate environment and neighbourhood as well as the relative position of both the station and neighbourhood in the city. This conceptual model relies on principles of environmental criminology, situational crime prevention and Crime Prevention through Environmental Design(CPTED)[2].

1.2.1 The physical and social characteristics of metro stations

A station’s vulnerability to crime depends on its physical environment and the type of social interactions that take place at this particular setting.The physical environment refers to the hardware of the station; it is composed of everything that is present and visible to the human eye. Stations may vary by size (e.g., stations belonging to transportation hubs tend to be large), type (e.g.,central stations are often underground, while outlying stations tend to be above ground) or style(e.g., modern, see-through walls), but still they follow some basic standards.

Metro stations have entrance/exit areas (e.g.,tunnels, stairs, elevators, shops, and restaurants),lobbies (e.g., ticket booths, automatic controls, and commercial shops), transition areas (e.g., stairs and elevators), platforms (e.g., single and multiple),and they are connected to the city through the immediate surroundings (e.g., streets and parking lots). Regardless of their layout, metro stations are often composed of five settings: platform,transition, lobby, entrance/exit, and finally the immediate surroundings. The platforms are where trains arrive, and where passengers embark,disembark, or wait. The transition area commonly includes stairs and elevators from the platform up to the lobby, where control gates and ticket booths are located. The lobby may be an open area that ends at the entrances/exits. Commercial shops may be found in lobbies and entrance/exit areas.The entrances/exits are areas limited to entering the lobby directly from the street or via doorways,stairs, elevators, or tunnels. The immediate surroundings are what individuals see within a few meters’ distance from the entrances/exits. Piza and Kennedy describe how both easy entrance and exit from stations, as well as passengers’ lack of familiarity with metro stations, lead to increased opportunity for offenders to commit crimes[12].Research has long shown that those physical characteristics of stations (and bus stops), such as lighting, design, location and security hardware,reduce crime opportunities[6-7,13-16].

1.2.2 The metro station and neighborhood context

Safety conditions at a metro station are influenced by its neighborhood environment in two ways: 1) the type of land use in the immediate surrounding area as well as the social activities it may attract; 2) the demographic and socio-economic characteristics of the population residing or working in the neighborhood. The relationship between neighborhood conditions and crime was first assessed in the seminal work by Shaw and McKay[17]in Chicago, and later coined as the main reference to social disorganization theory. Social disorganization theory links many forms of crime with weak informal social control, often present in high-crime areas,regardless of their location in a city. Thus, in general,economically deprived areas with low social control run higher risk of crime, as do metro stations located in those areas[2], but there are exceptions. LaVigne[14]showed that Washington’s subway crime rates by station do not correlate with crime rates for the census tracts where Metro stations are located.

1.2.3 The station in the city context

A metro station is often planned to move as many passengers as possible. It tends to be within walking distance of a residential area, working place, industrial area, or commercial center. This centrality feature of transportation nodes has criminogenic implications. Different types of land use affect the social interactions at those places and, consequently, their geographies of crime.Environmental criminology has shown how city centers are more criminogenic than other parts of the city[7,18-21]. Thus, it could be expected that stations located in inner-city areas would tend to be more targeted by crime and acts of disorder than those in the outskirts. Alternatively, end stations(those at the ends of metro lines) can be more criminogenic than those found along the lines. These end stations are often linked to other transport modes, with large flows of passengers, and may adjoin parking lots and commercial areas, which are bound to create more crime opportunities.

2 The case studies

2.1 The two metro systems

2.1.1 Stockholm metro system

Stockholm is well supplied by its one hundred stations, connected to buses and commuter trains.47 are underground (most central) and 53 above ground. There are three lines: Red, Green and Blue (Fig. 1-1). In this study, we will report on crime and public disorder events in the whole Stockholm metro system, but because of data limitation the modelling section will use 82 per cent of the stations, those located in Stockholm municipality. Stockholm is part of an archipelago,and therefore water occupies a large part of the urban landscape as the city is spread over a set of islands on the southeast coast of Sweden. The islands are well connected by roads and an efficient public transportation system, comprising of buses,the metro system, rail systems and commuter trains. Stockholm is also peculiar because it is a Scandinavian city; the short days of its cold, dark winter limit life outdoors, but long daylight hours allow for days full of activity in the spring and summer. Stockholm is the capital and most populous city of Sweden, and the most populous city of Scandinavia, with 910,000 inhabitants in 2016.

2.1.2 S?o Paulo metro system

The study area is composed of 62 stations in the S?o Paulo metro (Metr? de S?o Paulo),excluding some expansion (65 stations total), which is the main rapid transit system in the city of S?o Paulo, the largest in Brazil and the second largest system in South America (Fig. 1-2). The system was founded in 1968 with one line, and today has five lines (74 km, Fig. 1-2) carrying 4,600,000 passengers per day on 154 trains operating from Sunday to Saturday, from 04:40 AM to midnight(01:00 AM on Saturdays). The Metro runs within S?o Paulo municipality—a municipality with 12 million inhabitants. The city is also served by a set of companies providing commuting train service. S?o Paulo’s size is unique even within Latin America. It is Brazil’s largest municipality and constitutes South America’s largest metropolitan area. The metropolis is a global city and the most populous city in Brazil, the Western Hemisphere and the Southern Hemisphere.

2.2 Data and methods

In Stockholm, crime and public disorder data were gathered from Stockholm Public Transport(2006—2009) in combination with Police recorded statistics (we will not discuss police data in this study).Instead of using crude data of crime events by stations, rates per 1000 passengers were calculated based on the passenger flow at each station. Data from the fieldwork inspection (checklists) were inputted in spreadsheets and then imported to GIS, together with data on land use, crime, and demographic and socioeconomic data of the population. Stations and crimes were mapped as point data, whereas the Stockholm demographics and socio-economic data were linked to small unit statistics. In order to assess the influence of the surroundings on crime and disorder events at each station, a number of criminogenic land-use indicators were manually mapped: the location of automated teller machines (ATMs), schools, police offices and state-operated alcohol retail outlets in Stockholm. The study is based on comprehensive fieldwork combined with Geographical Information Systems techniques and modelling[2].

In S?o Paulo, this study makes use of data from Delpom (Delegacia de Polícia Metropolitano)and Polícia Civil reports by passengers (2010—2015) obtained from S?o Paulo Metro company(aggregated by type and station and by time(2013—2015) as well as from an SMS-service (2014—2015), which allows for the reporting of crime and other incidents that happen during metro trips and/or on metro premises. Crime incidents include property and violent crimes, such thefts, muggings and any sort of violence, including sexual violence and sexual harassment. In order to standardise the levels of incidents, the number of passengers was also obtained from Metro, which are estimates of the number of passengers in a working day by station during peak and off-peak hours, as well as the total number of personnel (security and overall) by station. The methodology combines Geographical Information System (GIS) and crime records with data collected using Google street view and other secondary data into a set of regression models[5].

3 Results

3.1 The nature of crime and public disorder

Different recording practices significantly affect levels of crime and events of public disorder in metro systems, which makes any comparison of crime figures between systems a difficult task. The exact numbers of criminal incidents also vary by data source. In Stockholm, for instance, property crimes are more often recorded in official police statistics than the Stockholm Public Transport Company. Below we discuss some of the major trends from the datasets provided by both Public Transport Companies but strictly speaking,comparisons should be made with caution, both because of the different recording practices and because the datasets are not from the same time.

Overall, most events that take place at the metro stations are events that affect the perceived safety but may not be crimes. Common recorded offences are threats and physical assault among passengers and against personnel, more commonly in the Stockholm metro system than in S?o Paulo’s, where property crimes compose the largest share of records. Property crimes can generally be divided into two types: those against persons and of objects. The latter includes thefts in wagons and stations (mobile phones are more common in S?o Paulo than in Stockholm, for instance), shoplifting in shops and food stores, and the theft of bicycles and cars, which are common around metro stations, in parking lots, or on streets.

In S?o Paulo’s metro system, 62 per cent of reported incidents are property crimes such as thefts and robberies. Fights and other types of violence compose nearly a fifth of the records.Cases of sexual assault and sexual harassment are often under recorded[5]. It is important to note that there are other events that are not counted in this dataset (some of them are gathered elsewhere,e.g. via SMS-service), such as cases of physical damage against property, begging, and other types of public disorder. The incidents that are recorded are an integral part of the records in the Stockholm metro system, and constitute the large majority of recorded incidents (around 80 per cent). There, 20 per cent of reported incidents to the transportation company are considered crimes.The majority of these crimes are fights (about 40 per cent), vandalism, and threats, followed by other types of violence. Most reports of violence are against personnel, guards, drivers, or passengers.Police robbery data also show a large portion reported at stations, although the majority of all records at stations are related to places like shops and supermarkets. Public disorder events, which constitute the large majority of the incidents,include unlawful activities or acts of anti-social behaviour, such as public urination, drug use,loitering, public drunkenness, and unjustified use of emergency brakes, fire extinguishers, or fire hoses in wagons/stations[2].

Tab. 1 Violent crimes by season, Stockholm, 2006—2008

3.2 Temporal patterns of crime and disorder

Knowing when crime happens in transit environments is fundamental for tailoring effective crime prevention interventions. Violence and theft happen during rush hours in both metro systems,but these offences show different hourly patterns.In S?o Paulo, these offences reflect the crowdedness of the system in the morning and evening (around 08:00 and 09:00 and 18:00—19:00), while in Stockholm, the peaks vary by offence type: thefts take place between 14:00 and 19:00 and violence encounters occur after midnight (Fig. 2).

In Stockholm, significantly more incidents are recorded during weekends and holidays than weekdays, perhaps because people often engage in ‘unstructured activities’ during weekends and holidays, which tend to be more criminogenic (e.g.,going to parties, drinking) than those perform during ‘normal’ weekdays, which often involve more ‘structured activities’[13]. In the S?o Paulo metro, the amount of recorded crime events varies by type of crime, but overall follows a stricter pattern of daily weekdays’ routine activities, such as going to school/work, and then back home again.For example, for sexual harassment and/or sexual violence, most incidents are recorded from Monday to Friday (20 per cent on Mondays and Tuesdays and only 6 per cent on Saturdays) when people are going to or returning from work. The most significant peak happens during rush hour in the morning, between 08:00 and 09:00, and in the late afternoon between 18:00 and 19:00[5], when most trains and lines are overcrowded.

Data from a longer time period would be needed to test seasonal variations in the S?o Paulo metro, but despite this, results show that there are slight increases in the number of cases in June and July, which are the winter season in Brazil. In the Stockholm metro system, violent crimes are seasonal (e.g., robbery, fights, threats),concentrated in the Swedish hot months of the year(Tab. 1)[22]. Important to remember that our case studies are embedded in two different geographical contexts. The Stockholm metro system is located in Stockholm, Sweden, a Scandinavian country with long dark winters, while the S?o Paulo metro system is in Brazil, a tropical country with average annual temperatures above 21 degrees Celsius. These seasonal differences are bound to define particular patterns of routine activity that, in their turn, impact crime levels in these transit environments.

3.3 Spatial patterns of crime and disorder

In both metro systems, results show that the central stations might concentrate the highest number of incidents, but they do not keep their top position if crime and events of public disorder are standardized by daily passenger flow. Instead of using crude data of incidents by stations, rates per 1,000 passengers are calculated for all types of crime for both Stockholm and S?o Paulo,revealing a more interesting spatial pattern. As a result, the so-called “end-stations” show higher rates of events (crime and public disorder) than stations located in the inner-city areas (exceptions are the stations: Medborgarplasten and Skanstull,for thefts). More interestingly, stations such as Hjulsta, Farsta Strand, H?sselby Strand, V?llingby and Hags?tra (all peripheral stations) show high rates regardless of crime type, which is a relevant piece of information for safety interventions. In S?o Paulo, the pattern is similar but the centrality remains for all types of crimes. High rates of reporting are more often found at stations located within a 3 km radius from the city centre following a distance decay distribution from Sé station, in the inner city area (examples are stations Paraíso and Liberdade). Regional transportation hubs tend to also show high rates of recorded crime after standardising by daily passenger flow (e.g. stations Brás, Palmeiras-Barra Funda, Tatuapé).

Some stations are crime-specialized. For instance,in Stockholm, stations such as Rinkeby more often have problems with violence, while V?stertorp station more often has high theft rates, and Norsborg, has dominantly many records of vandalism. Some of these stations belong to areas with higher than average general crime rates, and they often belong to areas of mixed land use, near commercial areas, and/or are endstations, where people meet. In S?o Paulo, this crime specialization is not as clear as in the metro system but for sexual harassment, for instance, sexual violence is concentrated at the busiest central stations and at stations that also attract all sorts of violence and events of public disorder[5]. Variations of crime events per lines are also found in both metro systems[5,23].

Tab. 2 Characteristics of the stations, neighbourhood surroundings and city context

3.4 Explaining levels of crime and disorder at metro stations

Using the conceptual model discussed in section 2, crime and public disorder at stations in these two metro systems were modelled as a function of the physical and social environmental attributes at the station (more in detail in Stockholm than in S?o Paulo because of the data limitations), the characteristics of the immediate environment and neighbourhood,and finally, the relative position of both the station and neighbourhood in the city. Below we discuss the main commonalities of the two case studies’ findings.Before drawing any conclusion, please keep in mind that the modelling strategies are slightly different because of the differences in data availability for Stockholm and S?o Paulo metro systems.

In both metro systems, results show that opportunities for crime are dependent on stations’environmental attributes, the type of neighbourhood in which they are located, and city context—but the effect of these dimensions is dependent on the metro system itself, types of offences and time of the day. Table 2 summarises some general characteristics that alone, or combined with other factors, affect criminogenic conditions of these transit nodes. Whether the stations were central or not is one of the most important factors affecting the levels of crime in both metro systems; inner city areas tend to attract more crime. However, endstations can be highly criminogenic as the Stockholm case shows. Another commonality is the influence of land use around the stations, in particular the presence of risky facilities (e.g. restaurants) or a lack of facilities that discourage crime and public disorder (police stations). Note that information on the internal design of S?o Paulo’s metro stations was limited, which directly affects the modelling. Yet, we found that some features were recurrent in both case studies, such as the presence of dark corners, which directly affect the visibility and surveillance. Below we discussed in more detail the specifics of each case study.

In Stockholm, for instance, for rates of total crime and disorder, variables that indicate presence of guardianship and illumination explain 30 percent of the variation in crime rates; it goes up to 52 per cent when other variables that indicate formal social control (number of police stations within 100 meters), distance to city centre and city context are added to the model. For violence, the goodness of fit of the model nearly doubles when variables depicting the surroundings of the stations were added to the model (e.g. open entrances, distance to city centre, population density). These variables were also important to explain the variation of property crimes, such as thefts and robberies[1,13].

In S?o Paulo, for total crime rates, factors reflecting internal features of the stations and their location explain around 30 per cent of the variation of total crime in the S?o Paulo metro. For thefts and robberies, the conditions found at stations located in inner city areas are better predictors of property crimes than for violence. High rates of recorded violence tend to be more common at stations that have relatively large numbers of CCTVs and metro personnel, a presence of physical and social disturbance, and a presence of dark corners. Similarly, high rates of violence are observed in stations outside of inner city areas,most often those that are part of regional centres,close to shopping malls. These stations are well connected to the urban fabric, accessible but relatively small, and surrounded by more affluent neighbourhoods, and so might be closer to bicycle storage facilities or restaurants[5].

4 Lessons learned from Stockholm’s and S?o Paulo’s metro systems

Metro stations are criminogenic places,but certain stations are more often targeted by acts of crime and disorder than others and this vulnerability may change over time. Most crime in metro stations shows variations over time; they tend to occur more often during certain periods of the day, week or year. These temporal variations are often related in the literature to changes in people’s routine activities throughout the day, the week and year[24-25]. Calling for another interpretation of this temporal variation, Harries et al.[26]suggests that there might be a lag effect on people’s manifestations of stress. The stress is accumulated during the day and then blows up later, for instance, when people go somewhere else after work, where there is a possibility of externalizing stress. These findings mirror the literature that suggests that conflicts often reach a peak when people meet each other in their free time. However,some of these encounters happen during normal weekdays, as passengers are in the metro, inside of wagons, going to, or home from work or school.These encounters may lead to property crimes such as theft of mobile phones and pickpocketing, or to violence, such as conflicts inside wagons when crowded (fights for a place or sexual violence).

Opportunities for crime at the stations are dependent on the stations’ environmental attributes,neighbourhood context as well as the station’s location in the city. These findings provide support for environmental crime theories that claim a link between environmental features and crime at several geographical levels, from the micro-environment of the platform and stations (e.g. illumination, CCTVs)to neighbourhood and city contexts—namely environments that passengers are exposed to as they travel to/from these stations[7,9,17,27]. From both Stockholm and S?o Paulo case studies, we see that regardless differences in the environmental context of these systems, the flow of passengers regulates the amount of crime opportunities. It is therefore essential, before any intervention is suggested, that we map out where crime and disorder incidents occur in time and space, in very detailed level (e.g., peak and off peak hours, by stations, by sections of the stations,inside wagons). Example of how this is done see[1].

Future research should investigate the use of ICT - Information and Communication Technology to enhance mobility and safety. The use of mobile sensors and similar technologies opens up a number of new research questions. For instance, individuals’detailed movement data could help in understanding the link between station surroundings and fear of crime. Of particular importance is the need to investigate why people are afraid at particular times and at particular stations; here, data collection via mobile sensors could be of assistance.

5 Conclusions

In this study, we set out to compare the criminogenic conditions of two metro systems over time and space keeping in mind differences in data availability and methodology from these case studies: Stockholm, Sweden and S?o Paulo,Brazil. The most important message from these studies is that safety conditions in metro systems depend not only on the local conditions of the stations, but also the surroundings in which these stations are located. This means that each stakeholder has the responsibility to make sure passengers are safe within jurisprudence. They must also aim to safeguard passengers’ safety by adopting a door-to-door perspective, in other words, having a ‘whole journey approach’. This demands cooperation from those responsible for ensuring safety in the wagons, on station premises,and in the surrounding environments where people walk to and from transport nodes. Yet, there are things that can be done at the station level. In order to do that, we need to map out where crime and disorder incidents occur in time and space,in very detailed level, taking differences in flow of passengers into account. This means that we need to target particular stations and at certain‘time windows’ when most crime happens. In rush hours in particular, crowded conditions at core stations facilitate crime in both metro systems, as it was illustrated in Stockholm and in S?o Paulo.Findings also indicate the need for improvements in surveillance (e.g. eliminating dark corners),especially in areas with commercial land use, in central and peripheral stations. Regardless the type of interventions, actions must consider the temporal and spatial dynamics of each crime type.

On top of challenges with cooperation between actors that deal with safety in metro systems, there is also a lack of focus on users’needs, particular those determined by gender, age and disability. Victimisation and perceived safety in transit environments should not only consider users’ age or gender but reflect the intersection of a set of individuals’ characteristics. Being a disabled and poor individual creates ‘synergic layers of disadvantage’ that affect one’s likelihood to be a victim of crime and/or the way he or she experiences the world. Just taking gender as an example, we know that both mobility and safety are gendered[28], yet public transportation systems adopt gender-neutral policies.

Crime prevention programs in metro systems must account for city and country specific problems.In the case of S?o Paulo, for example, the metro system runs over-capacity; buses and vans, together with commuting trains and the metro system,do not provide sufficient mobility services for passengers. Safety conditions and crowded stations in the S?o Paulo metro reflect a more fundamental problem, namely, the need to ensure individuals’rights to public transportation. This evidence is not only relevant for the Brazilian or South American contexts, but it reveals the reality of millions of passengers around the world. Since most of the current evidence in transit environments comes from studies in North America and Western Europe,there is an urgent need to assess safety conditions in countries with growing cities, not least in Africa and Asia—these future studies should potentially reveal the specific safety challenges of these transit systems and/or their passengers’ safety needs.

This article brings together evidence from Scandinavian and South American contexts,which has so far been lacking in the international literature. Although this study contributes to the literature on transit safety by highlighting commonalities between the metro systems, any safety intervention elsewhere should be informed by evidence from specific local safety conditions of each particular transit system. Despite its limitations, this article is a step forward towards a better understanding of safety conditions in metro systems when taking into account the stations’environmental attributes, neighbourhood context as well as their location in the city.

(Editor / WANG Chenyu, WANG Yilan)