Pengfei Zhou, Yuanqing Zheng, Mo Li
The bus arrival time is primary information to most city transport travelers. Excessively long waiting time at bus stops often discourages the travelers and makes them reluctant to take buses. In this paper, we present a bus arrival time prediction system based on bus passengers' participatory sensing. With commodity mobile phones, the bus passengers' surrounding environmental context is effectively collected and utilized to estimate the bus traveling routes and predict bus arrival time at various bus stops. The proposed system solely relies on the collaborative effort of the participating users and is independent from the bus operating companies, so it can be easily adopted to support universal bus service systems without requesting support from particular bus operating companies. Instead of referring to GPS enabled location information, we resort to more generally available and energy efficient sensing resources, including cell tower signals, movement statuses, audio recordings, etc., which bring less burden to the participatory party and encourage their participation. We develop a prototype system with different types of Android based mobile phones and comprehensively experiment over a 7 week period. The evaluation results suggest that the proposed system achieves outstanding prediction accuracy compared with those bus company initiated and GPS supported solutions. At the same time, the proposed solution is more generally available and energy friendly.
Public Review uploaded by lzhong:
This public review was prepared by Rajesh Balan.
This paper addresses the problem of obtaining accurate bus timings without needing infrastructure provided by either the transport operators or the local government. Instead, the authors propose the use of participatory sensing to provide accurate bus timings. The system proposed comprises of three parts; 1) using the cell tower and accelerometer measurements from participating phones (held by people traveling on the buses) to determine the speed and location of a particular bus, 2) a backend server that knows where the various users are and can send the appropriate queries to determine the current location and speed of required buses, and 3) techniques to combine partial information from various users to achieve a required result.
However, the paper does have deficiencies that were pointed out by the various reviewers. 1) it requires buy-in from a large number of people to be effective. Otherwise, queries may not be successful for many routes. 2) it was evaluated with just a few bus routes that were mostly non-overlapping. It's not clear how this system would work in areas where bus routes overlap significantly. Finally, 3) it's not clear how this system would work in places other than Singapore. One of the key contributions of the paper was detecting entry onto a bus and that mechanism (identifying the beep of the card reader) is very Singapore-centric.
Overall, this was a very impressive piece of engineering and the authors have clearly spent a lot of time designing, building, and testing their system. It will be interesting to understand how to increase the take-up rate of these types of participatory sensing systems -- especially in developed areas where existing infrastructure and solutions (although possibly operating at lower fidelity due to various reasons) already exist.
Many thanks for the reviewer’s constructive comments.
The idea of predicting bus arrival time with participatory sensing is motivated from current lack of such services in most places in the world. In some developed areas, there are commercial bus information providers offering the realtime bus arrival time. Providing such information, however, usually requires the cooperation of the bus operators and incurs substantial cost. For example, in Singapore the LTA (Land Transport Authority) collaborates with IBM to provide the realtime bus arrival information. The two major transit operators SBS and SMRT are required to install location tracking devices on their buses and report the instant bus locations to LTA.
In this paper, we propose a crowd-participated approach that allows ordinary bus riders to query and share bus route information. The proposed system is built independent of the bus operators or other third-party service providers. Thus a particular feature of this system is its low cost and good generality. We will demonstrate how the system can be adapted to other places with slight modification during the conference demo session. Being participatory sensing based, our approach will have good performance with more people participation. Based on commodity mobile phones, the system does not require the use of GPS modules or explicit human inputs, which encourages people participation. Besides, we apply advanced techniques like concatenating celltower sequences of different passengers to enhance the system accuracy, especially against heavy bus route overlaps.