Night Bus: Route Design Using Big Data
Night Bus: Route Design Using Big Data
The night bus, or so-called ‘Owl Bus’, was first enforced in 2013. It provides bus services at night time, as needed by the citizens, at affordable prices by designing routes using big data. Already having an interest in the use of big data, Seoul city analyzed data obtained by the Dasan Call Center, which demonstrated that citizens had considerable interest in the traffic field. Furthermore, communication with citizens via the internet displayed that there was a demand for public transportation that could be safely used at night time when bus services normally end. These led to the initiation of this policy.
Two demonstrative routes were operated from April to July of 2013, and from September 12, 2013, the system was expanded to 9 routes.
Night Bus
1) By concentrating services in areas with high demand of night transportation, high bus usage is achieved in order to enhance user satisfaction and support night activities (this service can easily be cancelled if the usage rate is low)
2) Safe return of citizens to their homes during night time (midnight to 5am)
Reduction of Traffic Accidents
Reduction of fatal traffic accidents -> Deaths from traffic accidents is reduced by less than 1/6 (430-> 70)
1) Combined repair of the traffic environment in the residential zone / introduction of the garage verification system in the residential zone
2) Improved safety of public transportation / reinforced security (prevention of crime) in public transportation
3) Reinforced speed restriction of vehicles on the main roads in the city (60-> 50km) / Construction of a system that immediately responds to all fatal traffic accidents
4) Operation of ‘Seoul EYE’ the dynamic control management system / 24-hour operation of the Seoul safety situation room
Seoul Metropolitan Government
Economic activities in Seoul are carried out 24 hours a day, in reality. Countries that display a considerable amount of traffic at night time mostly rely on taxis. However, these are not a sufficient alternative due to a lack of supply compared to excessive demand, poor service (rejection of passengers), safety problems, and high costs during peak night hours. Some of the citizens that participate in night economic activities are service consumers, including restaurants and entertainments, and while others include low income workers, businessmen and company workers, as well as students. Thus, a lack of public transportation at night time signifies the restriction of economic activities at night.
In certain night service corporations, such as ‘clubs’ in large cities of England, leased buses are individually operated to provide transportation to the citizens who reside in adjacent suburbs or small cities. Seoul city is reputed as a ‘city that is not outdone’ by these European cities in terms of its active night economic activities, including entertainment and pleasure services. Thus, although the chauffeur service is broadly used and somewhat established based on a firm demand without depending only on taxis, taxis or chauffeurs are not reasonable means to the young class and those of a low income, and thus, the selection of night transportation means is insufficient.
The citizens expressed this inconvenience through an electronic governmental communication channel, and the city assessed the introduction of night buses.
Meanwhile, since Seoul city was interested in using big data in administration, the intention of the application of big data in the transportation field was a reflection of the citizens’ interest. Upon analyzing 600 thousand cases at the ‘120 Dasan Call Center’, one of the Seoul citizens’ complaint channels, it was displayed that the citizens had the greatest interest (25.5%) in the transportation field. Other than establishing the night bus route, big data was also used in the reduction of traffic accidents.
Big data analysis for bus operations optimization
Night Bus
1) The night bus route, which was designed with the use of big data, achieved an amount of transportation that exceeds 5 to 10% of existing routes.
2) The citizens that participated in night activities saved transportation costs, and the usefulness of a safe, convenience, and affordable night transportation means is estimated to have increased the participants’ night activities (verified by the research of sales at night spots near the routes). In fact, the female population participating in night activities increased by 11% (Seoul City 2014).
3) There is the effect of preventing night crime (possibility of collecting substantive data).
4) The rejection of passengers by taxis reduced by 8.9% as an additional effect.
5) Within the increasing domestic and international interest in the usability of big data, this became a very practical case that noticeably relieved the inconvenience of the citizens at a small cost. Thus, it displayed a future-oriented aspect of administration that moves with innovation and dynamicity.
6) This policy was selected as the second place in the top 10 policy vote during the first half of 2013, and was reported in various national and international media outlets.
Currently, there are increasing domestic and foreign organizations and public officials that wish to share Seoul city’s big data administration and place Seoul city as an informatization benchmarking city model. As an example, the CEO of NESTA, the British National Science, Technology and Arts Foundation visited Seoul city to inspect the night bus route establishment system, and visited other cities and organizations, including Taipei in Taiwan, Jakarta in Indonesia, and the to disclose a case publication in relation to using big data.
Reduction of traffic accidents
- Traffic accidents involving child pedestrians
- Traffic accidents involving elderly pedestrians
- Traffic accidents in island bus road stations
- Accidents from drunk driving
- Analysis of dangerous driving behaviors
| Attachment | Size |
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| SMG-05_NightBusRouteDesignUsingBigData.pdf | 483.66 KB |