Predicting Bus Arrival Time with Mobile Phone Based Participatory Sensing
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How Long to Wait?: Predicting Bus Arrival Time with Mobile Phone based Participatory Sensing Pengfei Zhou, Yuanqing Zheng, Mo Li Nanyang Technological University, Singapore [email protected], [email protected], [email protected] ABSTRACT General Terms The bus arrival time is primary information to most city Design, Implementation, Experimentation, Measurement, Per- transport travelers. Excessively long waiting time at bus formance stops often discourages the travelers and makes them re- luctant to take buses. In this paper, we present a bus ar- Keywords rival time prediction system based on bus passengers’ par- ticipatory sensing. With commodity mobile phones, the bus Bus arrival time prediction, Participatory sensing, Mobile passengers’ surrounding environmental context is effectively phones collected and utilized to estimate the bus traveling routes and predict bus arrival time at various bus stops. The pro- 1. INTRODUCTION posed system solely relies on the collaborative effort of the Public transport, especially the bus transport, has been participating users and is independent from the bus operat- well developed in many parts of the world. The bus trans- ing companies, so it can be easily adopted to support uni- port services reduce the private car usage and fuel consump- versal bus service systems without requesting support from tion, and alleviate traffic congestion. As one of the most particular bus operating companies. Instead of referring to comprehensive and affordable means of public transport, in GPS enabled location information, we resort to more gener- 2011 the bus system serves over 3.3 million bus rides every ally available and energy efficient sensing resources, includ- day on average in Singapore with around 5 million residents ing cell tower signals, movement statuses, audio recordings, [1]. etc., which bring less burden to the participatory party and When traveling with buses, the travelers usually want to encourage their participation. We develop a prototype sys- know the accurate arrival time of the bus. Excessively long tem with different types of Android based mobile phones waiting time at bus stops may drive away the anxious travel- and comprehensively experiment over a 7 week period. The ers and make them reluctant to take buses. Nowadays, most evaluation results suggest that the proposed system achieves bus operating companies have been providing their timeta- outstanding prediction accuracy compared with those bus bles on the web freely available for the travelers. The bus company initiated and GPS supported solutions. At the timetables, however, only provide very limited information same time, the proposed solution is more generally available (e.g., operating hours, time intervals, etc.), which are typi- and energy friendly. cally not timely updated. Other than those official timeta- bles, many public services (e.g., Google Maps) are provided for travelers. Although such services offer useful informa- tion, they are far from satisfactory to the bus travelers. For Categories and Subject Descriptors example, the schedule of a bus may be delayed due to many C.2.4 [Computer Communication Networks]: Distributed unpredictable factors (e.g., traffic conditions, harsh weather Systems – Distributed Applications;C.3.3[Special-Purpose situation, etc). The accurate arrival time of next bus will and Application-based Systems]: Real-time and embed- allow travelers to take alternative transport choices instead, ded systems; H.5.3 [Information Interfaces and Presen- and thus mitigate their anxiety and improve their experi- tation]: Groups and Organization Interfaces – Collaborative ence. Towards this aim, many commercial bus information Computing providers offer the realtime bus arrival time to the public [20]. Providing such services, however, usually requires the cooperation of the bus operating companies (e.g., installing special location tracking devices on the buses), and incurs substantial cost. Permission to make digital or hard copies of all or part of this work for In this paper, we present a novel bus arrival time predic- personal or classroom use is granted without fee provided that copies are tion system based on crowd-participatory sensing. We in- not made or distributed for profit or commercial advantage and that copies terviewed bus passengers on acquiring the bus arrival time. bear this notice and the full citation on the first page. To copy otherwise, to Most passengers indicate that they want to instantly track republish, to post on servers or to redistribute to lists, requires prior specific the arrival time of the next buses and they are willing to permission and/or a fee. MobiSys’12, June 25–29, 2012, Low Wood Bay, Lake District, UK. contribute their location information on buses to help to Copyright 2012 ACM 978-1-4503-1301-8/12/06 ...$10.00. establish a system to estimate the arrival time at various bus stops for the community. This motivates us to design able fingerprints of public transit buses and utilize the mi- a crowd-participated service to bridge those who want to crophone on mobile phones to detect the audio indication know bus arrival time (querying users) to those who are on signals of bus IC card reader. We further leverage the ac- the bus and able to share their instant bus route information celerometer of the phone to distinguish the travel pattern of (sharing users). To achieve such a goal, we let the bus pas- buses to other transport means. Thus we trigger the data sengers themselves cooperatively sense the bus route infor- collection and transmission only when necessary (§3.3). We mation using commodity mobile phones. In particular, the let the mobile phone instantly sense and report the nearby sharing passengers may anonymously upload their sensing celltower IDs. We then propose an efficient and robust top-k data collected on buses to a processing server, which intelli- celltower set sequence matching method to classify the re- gently processes the data and distributes useful information ported celltower sequences and associate with different bus to those querying users. routes. We intellectually identify passengers on the same bus Our bus arrival time prediction system comprises three and propose a celltower sequence concatenation approach to major components: (1) Sharing users: using commodity mo- assemble their celltower sequences so as to improve the se- bile phones as well as various build-in sensors to sense and quence matching accuracy (§3.4). Finally, based on accumu- report the lightweight cellular signals and the surrounding lated information, we are then able to utilize both historical environment to a backend server; (2) Querying users: query- knowledge and the realtime traffic conditions to accurately ing the bus arrival time for a particular bus route with mo- predict the bus arrival time of various routes (§3.5). bile phones; (3) Backend server: collecting the instantly re- We consolidate the above techniques and implement a pro- ported information from the sharing users, and intellectually totype system with the Android platform using two types processing such information so as to monitor the bus routes of mobile phones (Samsung Galaxy S2 i9100 and HTC De- and predict the bus arrival time. No GPS or explicit location sire). Through our 7-week experimental study, the mobile services are invoked to acquire physical location inputs. phone scheme can accurately detect buses with 98% detec- Such a crowd-participated approach for bus arrival time tion accuracy and classifies the bus routes with up to 90% prediction possesses the following several advantages com- accuracy. As a result, the prototype system predicts bus pared with conventional approaches. First, through directly arrival time with average error around 80 seconds. Such a bridging the sharing and querying users in the participa- result is encouraging compared with current commercial bus tory framework, we build our system independent of the bus information providers in Singapore. operating companies or other third-party service providers, In the following of this paper, we first introduce the back- allowing easy and inexpensive adoption of the proposed ap- ground and motivation in §2. In §3, we detail the chal- proach over other application instances. Second, based on lenges of our system and describe our technical solutions. the commodity mobile phones, our system obviates the need The evaluation results are presented in §4. The limitations for special hardware or extra vehicle devices, which substan- and possible improvements are discussed in §5followedby tially reduces the deployment cost. Compared with conven- the description of related works in §6. We summarize this tional approaches (e.g., GPS supported ones [12, 29]), our paper in §7. approach is less demanding and much more energy-friendly, encouraging a broader number of participating passengers. Third, through automatically detecting ambient environ- 2. BACKGROUND AND MOTIVATION ments and generating bus route related reports, our ap- The bus companies usually provide free bus timetables on proach does not require the explicit human inputs from the the web. Such bus timetables, however, only provide very participants, which facilitates the involvement of participa- limited information (e.g., operating hours, time intervals, tory parties. etc.), which are typically not timely updated according to Implementing such a participatory sensing based system, instant traffic conditions. Although many commercial bus however, entails substantial challenges. (1) Bus detection: