2. Big Data Big Data in Seoul s Transportation Policy: Designing Late Night Bus Routes Based on Big 2. 빅데이터 빅데이터를활용한서울시교통계획 : 빅데이터를이용한심야버스노선설계

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1 2. Big Data Big Data in Seoul s Transportation Policy: Designing Late Night Bus Routes Based on Big Data 2. 빅데이터 빅데이터를활용한서울시교통계획 : 빅데이터를이용한심야버스노선설계 A city that never sleeps, Seoul is a place where economic activity takes place 24 hours a day. 24 시간깨어있는도시로불리는서울시는 24 시간경제활동이이루어지고있는곳입니다. However, commuting at night after normal bus service operating hours is inconvenient, and taking a taxi at night is constrained by various factors, such as safety issues, high cost, and refusal of drivers to provide service, causing significant inconvenience to citizens who have to engage in economic activities at night, such as low-income workers, small-scale self-employed workers, office workers, and students. 그러나, 버스서비스가중단되는심야시간대에는이동이불편하고, 택시를타는경우, 안전성, 비용부담, 승가거부등의문제가있어야간경제활동이불가피한저소득근로자, 영세자영업자, 회사원, 학생등 시민들은많은불편을겪고있었습니다. Citizens have consistently complained about such inconvenience via Seoul City s 120 Dasan Call Center and various social networking services. 이로인해, 서울시가운영하고있는다산콜센터, 각종 SNS 등을통해다음과같은시민들의불편신고가 지속적으로있어왔는데요 Now that Seoul City has decided to solve these problems, let s take a look at what the city is doing toward that end. 서울시가이러한문제를해결하기로결정했으므로이제그도시가무엇을하고있는지살펴보겠습니다. [Late night bus service] [ 심야버스서비스 ] In order to solve the late night transportation problem, Seoul City started offering an affordable late night bus service known as the Night Owl in 2013 for the convenience of citizens. 심야교통문제를해결하기위해서울시는시민들의편의를위해 2013 년올빼미버스 (Night Owl) 라는 저렴한야간버스서비스를제공하기시작했습니다.

2 From April to July of 2013, Seoul City operated two late night bus routes in Gyeonggi-do and the outskirts of Seoul, the areas with the most serious late night transportation problems, on a trial basis. 서울시는 2013 년 4 월부터 7 월까지심야에서가장심각한교통문제가발생한지역인경기도와서울 외곽에서심야 2 개의버스노선을시험운행했습니다. In June 2013, Seoul City named its late night bus service the Night Owl based on the results of a public contest and created the Night Owl logo, which features an owl driving a bus 년 6 월서울시는공모전결과를바탕으로야간버스서비스 2 번을 " 올빼미버스 " 로명명하고버 스를운전하는올빼미가등장하는 3 번밤올빼미로고를제작했습니다. The Night Owl logo is displayed next to the bus number on the LED displays at the front and on the side of the bus. 밤올빼미로고는버스의앞면과측면에있는 LED 디스플레이의버스번호옆에표시됩니다. After the city had operated the two pilot routes for three months, it was found that the cumulative ridership on the buses hit 218,212 passengers, surpassing expectations. 도시에서 3 개월동안두개의시험비행로를운행한후, 버스의누적승객은 218,212 명의승객을쳐 서예상을뛰어넘는것으로나타났습니다. This means that each late night bus carried an average of 175 passengers a day, which is 65 more than its regular counterpart. 이것은매일늦은밤버스가하루평균 175 명의승객을태운다는것을의미합니다. 이는일반승객보다 65 명이더많습니다. By day of the week, Seoulites used the Night Owl service most early Saturday morning, especially during the two hours from 1 a.m. to 3 p.m., when 58 percent of the total number of passengers used the service. 요일별로, 서울시민들은토요일아침에밤올빼미서비스를가장많이사용했다. 특히, 승객수의 58 % 가오전 1 시부터오후 3 시까지 2 시간동안사용되었다. Relatively fewer people used the late night buses between midnight and 1 a.m. and between 4 a.m. and 5 a.m., when the subway and city buses were still operating. 지하철과시내버스가여전히운행중일때심야버스는자정에서오전 1 시사이, 오전 4 시부터오전 5 시사이에상대적으로적었습니다. By passenger category, workers accounted for 64.6 percent of all passengers, while substitute drivers

3 made up 23.5 percent and students accounted for 11.9 percent. 승객종류별로전체승객의 64.6 % 를차지했으며대체운전자는 23.5 %, 학생은 11.9 % 를차지했습니다. Despite concerns, there were few drunk passengers. 우려에도불구하고술에취한승객은거의없었습니다. In a survey of 500 passengers that was conducted after the pilot operation was completed, the Night Owl service received a score of for customer satisfaction, which is higher than score of received by the regular city bus service. 시험작업이완료된후 500 명의승객을대상으로실시한설문조사에서올빼미버스서비스는일반도 시버스서비스에서받은 점보다높은 점의고객만족도를보였습니다. In addition, in a follow-up survey of 1,000 passengers, 88.8 percent of the respondents wanted the operation of the Night Owl service to be expanded. 또한 1,000 명의승객을대상으로실시한후속조사에서응답자의 88.8 % 는 Night Owl 서비스의운영을확대하기를원했습니다. Motivated by the favorable responses and growing satisfaction with the service among citizens, Seoul City added more late night bus routes after September 2013 and is now operating nine routes. 서울시는시민들의호의적인반응과서비스에대한만족감에힘입어 2013 년 9 월이후밤늦게까지 버스노선을추가했으며현재 3 번노선을운영하고있습니다. As of December 2016, an average of 9,883 Seoul citizens are using the Night Owl service a day 년 12 월현재서울시민 9,883 명중 2 명은하루종일 Night Owl 서비스를이용하고있습니다. The late night bus schedule of each route is accessible through the bus information terminal (BIT) installed at every bus stop, mobile website of the Traffic Information Center, website of the Seoul Transport Operation and Information Service (TOPIS), and Seoul Traffic Portal smartphone app. 각노선의심야버스일정은모든버스정류장에설치된버스정보단말기 (BIT), 교통정보센터모바일 웹사이트, 서울교통정보서비스 (TOPIS) 웹사이트및서울시교통정보센터트래픽포털 " 스마트폰 앱을통해이용할수있습니다. Transfer information is available as well.

4 환승정보도사용할수있습니다. Of particular note regarding Seoul City s introduction of the Night Owl service is that the city used big data in the planning of the late night bus routes. 서울시의나이트올빼미 (Night Owl) 서비스도입과관련하여특히심야는심야버스노선계획에큰데 이터를사용했다는점에주목해야합니다. Seoul City already had a world-class public transportation service, but it needed to design the late night bus routes to meet the demands of potential passengers without spending excessive amounts of money on customer surveys. 서울시는이미세계적인수준의대중교통서비스를제공하고있지만고객조사에과도한돈을지출하지 않고잠재고객의요구사항을충족하기위해밤늦게까지버스노선을설계해야했습니다. To do so, Seoul City used big data technology, the applicability of which was a hot topic at home and abroad. Driven by this trend, Seoul City launched a big data analytics project. 그렇게하기위해서울시는국내외에서화제가되었던빅데이터기술을사용했고, 이러한추세에힘입 어서울시는거대한데이터분석프로젝트를시작했습니다. Now, let s take a closer look at how Seoul City used big data in designing and operating its late night bus routes. 서울시가심야버스노선을설계하고운영할때빅데이터를어떻게사용했는지자세히살펴보겠습니 다. The most important factor in introducing the late night bus service was accurately identifying the destinations of potential users. 심야버스서비스를도입할때가장중요한요소는잠재사용자의목적지를정확하게파악하는것이었 습니다. To determine user demand accurately, Seoul City used floating population information provided by the mobile carrier KT and taxi trip destinations. 서울시는사용자요구를정확히파악하기위해이동통신사인 KT 에서제공하는유동인구정보와택시 여행지를사용했습니다. To elaborate, Seoul City analyzed phone-use data collected from KT mobile phone subscribers over a

5 period of one month and taxi trip destination data collected over a period of seven days. 서울시는 1 개월동안 KT 휴대전화가입자로부터수집된전화사용데이터와 7 일동안수집된택시 여행목적지데이터를분석했습니다. In total, it analyzed three billion items of data created by KT mobile phone subscribers over a period of one month, or around 100 million items of data a day, to ensure data accuracy. KT 휴대전화가입자가만든데이터 30 억개를 1 개월동안분석한결과데이터정확성을보장하기 위해하루에약 1 억개의데이터항목을분석했습니다. The data collected from cell phone communications included departure data, which refers to data on where cell phones were used, and destination data, which refers to billing address data. 휴대전화통신에서수집된데이터에는휴대전화가사용된위치의데이터를나타내는출발데이터와 청구서수신주소데이터를참조하는목적지데이터가포함됩니다. To do so, Seoul City signed an MOU with the mobile carrier KT to receive the data it needed without sacrificing the privacy of KT cell phone subscribers. 이를위해이동통신사인 KT 와 MOU 를체결해 KT 휴대전화가입자의사생활을침해하지않으면서 필요한데이터를제공했습니다. The data on taxi trip destinations were collected using digital tachographs installed in taxis. 택시여행목적지에대한데이터는택시에설치된디지털타코그래프를사용하여수집되었습니다. Now, let s take a look at how Seoul City used big data to design the late night bus routes. 이제서울시가심야버스노선설계에큰데이터를사용하는방법을살펴보겠습니다. The Bus Policy Division, which is responsible for late night bus management, created late night bus route design drafts based on public transportation information. 심야버스관리를담당하는버스정책부서는대중교통정보를기반으로심야버스노선설계초안을 만들었습니다. It created the bus route designs by analyzing big data related to traffic volume on arterial roads, traffic volume, and transportation card use, collecting citizens opinions via social networking services, and conducting surveys on the floating population size in major areas late at night. 간선도로의교통량, 교통량, 교통카드사용량과관련된큰데이터를분석하고, 소셜네트워크서비스를 통해시민들의의견을수집하고, 밤늦게주요지역의인구변동에관한설문조사를실시하여버스노선

6 디자인을만들었습니다. Next, the Bus Policy Division consulted with the Data & Statistics Division to verify the practicality of the drafts by comparing two types of drafts, one based on mobile phone communication big data collected by KT and the other based on taxi trip destination data. 다음으로, 버스정책과는데이터통계학과와협의하여 KT 에서수집한휴대전화통신대용량데이터와 택시여행지데이터를기반으로한두가지유형의초안을비교하여초안의실용성을검증했습니다. Let s take a closer look at the process. 프로세스를자세히살펴보겠습니다. Finally, Seoul City mapped the population density during late night hours using the data on cell phone subscribers provided by KT. 마지막으로서울시는심야시간동안인구밀도를 KT 가제공한휴대전화가입자의데이터를사용하여 매핑했습니다. It then compared that information with the bus route design draft to optimize the routes and finalized the route design by adjusting the bus intervals and stops. 그런다음그정보를버스노선설계초안과비교하여경로를최적화하고버스간격및정지를조정하여 경로설계를완료했습니다. After completing the route map, Seoul City made a floating population distribution chart by analyzing the destinations of taxi trips taken by citizens at night. 서울시는노선도를마친후야간에시민들이택시를타는목적지를분석하여유동인구분포도를작성했 습니다. It then compared the distribution chart with the previous route design draft and analyzed the distance of each route and population density of each area to revise the routes so that they serve the most densely populated areas. 그런다음배포차트를이전경로설계초안과비교하여각경로의거리와인구밀도를분석하여경로가 가장밀집된지역에서비스되도록수정했습니다. Following the comparative analysis of the late night bus route drafts, Seoul City analyzed seven routes and revised five of them to finalize the route design. 심야버스노선초안비교분석을통해서울시는 7 개노선을분석하고 5 개노선을수정하여노선설계

7 를완료했습니다. [Policy effect] [ 정책효과 ] What, then, was the impact of the big data-based design of the late night bus routes on Seoul City s transportation policy, and what is its importance? 심야버스노선의빅데이터기반디자인이서울시교통정책에미친영향은무엇이고그리고그중요성 은무엇입니까? First, Seoul City reflected customers demand and its understanding of their behavior patterns in designing the new transportation service using new technology, that is, big data. 첫째, 서울시는신기술, 즉빅데이터를이용한새로운운송서비스설계에서고객의요구와행동패턴에 대한이해를반영했습니다. As the first example of applying big data to transportation service in Korea, Seoul City s big data-based bus route design has opened up new possibilities for applying big data to other administrative areas. 한국의교통서비스에큰데이터를적용한첫번째사례로서, 서울시의빅데이터기반버스노선설계는 다른행정구역에큰데이터를적용하는새로운가능성을열었습니다. Although there is a lack of public data, big data-based policy has proven to be highly applicable in large cities with high mobile phone penetration rates. 공개데이터가부족하지만큰데이터기반정책은휴대전화보급률이높은대도시에매우적합하다는 것이입증되었습니다. Second, it is noteworthy that, unlike other policies developed based mainly on public data, Seoul City s big data-based bus route design incorporated public information into private information. 둘째, 대중데이터를중심으로개발된다른정책과달리서울시의빅데이터기반버스노선설계는공 공정보를개인정보에통합한다는점은주목할만합니다. Seoul City signed an MOU with KT on using its cell phone subscribers location data to design the late night bus routes.

8 서울시는 KT 와휴대전화가입자의위치정보를사용하여심야버스노선을설계하는 MOU 를 체결했습니다. Third, and most importantly, Seoul City used the latest big data to predict end-user demand for the late night bus service and optimize the bus route design, thus increasing the impact of the project and improving service quality. 셋째, 서울시는늦은밤버스서비스에대한최종사용자수요를예측하고버스경로설계를최적화하여 프로젝트의영향력을높이고서비스품질을향상시키기위해최신데이터를사용했습니다. For instance, the Night Owl service was chosen by Seoulites as the best Seoul City policy in 2013 and achieved a score of for citizens satisfaction. 예를들어 Night Owl 서비스는서울시민이 2013 년최고의서울시정책으로선정하여시민만족도 점을달성했습니다. This slide shows Seoul citizens responses to the Night Owl service that were posted on social networking services. 이슬라이드는소셜네트워킹서비스에게시된 Night Owl 서비스에대한서울시민의반응을보여줍니 다. These positive responses ultimately prove that Seoul City s late night bus service is a cost-effective and innovative administrative policy that has reduced inconvenience for citizens. 이러한긍정적인반응은궁극적으로서울시의심야버스가비용효과적이고혁신적인행정정책으로시 민들의불편을덜어주었다는것을증명합니다. Last but not least, since the operation of the Night Owl bus service was expanded, the number of complaints against taxi drivers for refusing to provide service has decreased dramatically, falling by 37.7 percent compared to the previous year and ultimately improving the taxi service and increasing the convenience of passengers. 최초는아니지만마침내올빼미버스서비스의운영이확대된이후로서비스제공거부에대한택시 운전자에대한불만건수가대폭감소하여전년대비 37.7 % 감소하여궁극적으로택시서비스를 개선하고승객의편의가증가되었습니다. Seoul City s big data-based late night bus service is an exemplary policy that has been benchmarked by

9 numerous cities and organizations around the world. 서울시의대규모데이터기반야간버스서비스는전세계여러도시와기관에서벤치마킹한모범적인 정책입니다. Seoul City will continue its efforts to apply big data technology to diverse administrative areas as a means of encouraging administrative innovation. 서울시는행정혁신을촉진하기위해다양한행정구역에빅데이터기술을적용하려는노력을계속할 것입니다. As we have seen here, Seoul City uses big data to improve its public transportation service. 여기에서보았듯이서울시는대중교통서비스개선을위해큰데이터를사용합니다. In the next session, we will take an in-depth look at how Seoul City uses big data to reduce traffic accidents. 다음세션에서는서울시가교통사고를줄이기위해큰데이터를사용하는방법을심층적으로살펴볼것 입니다. Thank you. 감사합니다.