Abstract
This study compares three selected navigation applications which are Google Maps, Waze and HERE WeGo, through the study of each application’s Application Programming Interface (API). The study is focusing on the aspect of Estimated Time of Arrival (ETA) accuracy, in an attempt to determine which API are suitable to be integrated and implemented in the development of a shuttle bus application. To date, there are currently lacking studies that discuss or compare the implementation of API in the development of shuttle bus tracking and ETA application. This study focuses on finding which API is the best suitable for such development from an ETA perspective, using the navigation application where the APIs were implemented or based on as a tool of testing. An experiment was conducted in a city in Kuala Lumpur, Malaysia, by collecting the ETA of the navigation applications from multiple points while riding a scheduled shuttle bus. The ETA will be compared with actual arrival time (ATA) using RMSE, MAE and PE metric. Comparison results showed Google Maps app provides the most consistent ETA prediction accuracy in a conservative manner and is the most suitable to be incorporated into a simple bus tracking and ETA app. The significant contribution of this study is to provide a result of comparison of the ETA accuracy through selected navigation applications and comparison of their navigation API.
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Aljedaani, W., Nagappan, M., Adams, B., Godfrey, M.: A comparison of bugs across the iOS and Android platforms of two open source cross platform browser apps. In: 2019 IEEE/ACM 6th International Conference on Mobile Software Engineering and Systems (MOBILESoft), pp. 76–86. IEEE, May 2019
Amin-Naseri, M., Chakraborty, P., Sharma, A., Gilbert, S.B., Hong, M.: Evaluating the reliability, coverage and added value of crowdsourced traffic incident reports from Waze. Transp. Res. Rec. 2672(43), 34–43 (2018)
Anderson, K.J.: Mobile app recommendations: travel apps. Library Hi Tech News (2016)
Armstrong, J.S., Green, K.C., Graefe, A.: Golden rule of forecasting: be conservative. J. Bus. Res. 68(8), 1717–1731 (2015)
Bauer, T.P., Edinger, J., Becker, C.: A qualitative and quantitative analysis of real time traffic information providers. In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 113–118. IEEE, March 2019
Bećirspahić, L., Karabegović, A.: Web portals for visualizing and searching spatial data. In: 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 305–311. IEEE, May 2015
Borhan, M.N., Ibrahim, A.N.H., Syamsunur, D., Rahmat, R.A.: Why public bus is a less attractive mode of transport: a case study of Putrajaya. Malaysia. Periodica Polytechnica Transp. Eng. 47(1), 82–90 (2019)
Chai, T., Draxler, R.R.: Root mean square error (RMSE) or mean absolute error (MAE) – Arguments against avoiding RMSE in the literature. Geoscientific Model Dev. 7(3), 1247–1250 (2014)
Cheung, P., Sengupta, U.: Analysis of journey planner apps and best practice features. Manchester Metropolitan University, Manchester, England (2016)
Chien, S.I.J., Ding, Y., Wei, C.: Dynamic bus arrival time prediction with artificial neural networks. J. Transp. Eng. 128(5), 429–438 (2002)
Chit, S.M., Chaw, L.Y., Thong, C.L., Lee, C.Y.: A pilot study: Shuttle bus tracker app for campus users. In: 2017 International Conference on Research and Innovation in Information Systems (ICRIIS), pp. 1–6. IEEE, July 2017
Dziekan, K., Kottenhoff, K.: Dynamic at-stop real-time information displays for public transport: effects on customers. Transp. Res. Part A: Policy Practice 41(6), 489–501 (2007)
Géza, K.: Analysis of the routing results and it’s usage
Global smartphone market Q3 2020. (n.d.). https://www.canalys.com/newsroom/canalys-worldwide-smartphone-market-q3-2020
Goodall, N., Lee, E.: Comparison of Waze crash and disabled vehicle records with video ground truth. Transportation Research Interdisciplinary Perspectives, 100019 (2019)
Google Maps API (2020). https://developers.google.com/maps/documentation. Accessed Oct 2020
Google Maps (2020). https://www.google.com/maps
Google Play Store: Maps - Navigate & Explore- Apps on Google Play (2020A). https://play.google.com/store/apps/details?id=com.google.android.apps.maps. Accessed Oct 2020
Google Play Store: Waze - GPS, Maps, Traffic Alerts & Live Navigation - Apps on Google Play (2020B). https://play.google.com/store/apps/details?id=com.waze&hl=en. Accessed Oct 2020
Google Play Store: HERE WeGo – City Navigation - Apps on Google Play (2020C). https://play.google.com/store/apps/details?id=com.here.app.maps&hl=en. Accessed Oct 2020
Google Play Store. MAPS.ME – Offline maps, travel guides & navigation- Apps on Google Play (2020D). https://play.google.com/store/apps/details?id=com.mapswithme.maps.pro&hl=en. Accessed Oct 2020
Google Play Store. (2020E). MapQuest: Directions, Maps & GPS Navigation- Apps on Google Play. https://play.google.com/store/apps/details?id=com.mapquest.android.ace&hl=en. Accessed Oct 2020
Google Privacy Terms, How Google uses location information – Privacy & Terms. (2020). https://policies.google.com/technologies/location-data?hl=en-US
HERE API (2020). https://developer.here.com/. Accessed Oct 2020
HERE Technologies. (2020). https://www.here.com/. Accessed Oct 2020
HERE WeGo, HERE application or HERE Maps Privacy Supplement (updated): Legal, security, privacy and compliance (2020). https://legal.here.com/en-gb/privacy/here-wego-here-application-or-here-maps-privacy-supplement-updated
Hiroi, K., Imai, H., Kawaguchi, N.: Dynamic arrival time estimation model and visualization method for bus traffic. In: Mine, T., Fukuda, A., Ishida, S. (eds.) Intelligent Transport Systems for Everyone’s Mobility, pp. 155–173. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-7434-0_9
HUAWEI Community: HERE WeGo: Your Google Maps alternative for Huawei and Honor phones. (n.d.). https://consumer.huawei.com/en/community/details/HERE-WeGo:-Your-Google-Maps-alternative-for-Huawei-and-Honor-phones/topicId_102513/
Kadam, A. J., Patil, V., Kaith, K., Patil, D., Sham.: Develo** a smart bus for smart city using IOT technology. In: 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) (2018)
Li, F., Yu, Y., Lin, H., Min, W.: Public bus arrival time prediction based on traffic information management system. In: Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics (2011). https://doi.org/10.1109/soli.2011.5986581
Mapbox API (2020). https://docs.mapbox.com/api/. Accessed Oct 2020
MapQuest Business (2020). https://developer.mapquest.com/documentation/open/. Accessed Oct 2020
Maps.ME Mobile Offline Maps (2020). https://maps.me/#gsc.tab=0. Accessed Oct 2020
Morgul, E.F., et al.: Virtual sensors: Web-based real-time data collection methodology for transportation operation performance analysis. Transp. Res. Rec. 2442(1), 106–116 (2014)
Nair, D.J., Gilles, F., Chand, S., Saxena, N., Dixit, V.: Characterizing multicity urban traffic conditions using crowdsourced data. PLoS One 14(3), e0212845 (2019)
Noor, R.M., et al.: Predict Arrival Time by Using Machine Learning Algorithms to Promote Utilization of Urban Smart Bus (2020)
OpenStreetMap API. (2020). https://www.openstreetmap.org/#map=7/4.116/109.455. Accessed Oct 2020
Pant, K., Talukder, D., Biyani, P.: TrafficKarma: estimating effective traffic indicators using public data. In: Proceedings of the 2nd IKDD Conference on Data Sciences, p. 6. ACM (2015)
Petrovska, N., Stevanovic, A.: Traffic congestion analysis visualization tool. In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pp. 1489–1494 (2015)
Petrovska, N., Stevanovic, A., Furht, B.: Visualization tools for traffic congestion estimation. In: Innovative Web Applications for Analyzing Traffic Operations, pp. 23–31. Springer, Cham (2016)
Privacy Policy of Waze, the GPS Navigation App. (2020). https://www.waze.com/legal/privacy#information-that-is-being-collected
Pylarinos, D., Pellas, I.: Incorporating open/free GIS and GPS software in power transmission line routine work: the case of Crete and Rhodes. Eng. Technol. Appl. Sci. Res. 7(1), 1316–1322 (2017)
Sangkhapan, S., Wannapiroon, P., Nilsook, P.: Smart Bus Management System Architecture Using Mesh App and Service Architecture. J. Softw., 130–137 (2020). https://doi.org/10.17706/jsw.15.5.130-137
Saputra, O.A., Ramdani, F., Saputra, M.C.: Comparison analysis of Google Maps, Wisepilot and Here-WeGo with user-centered design (UCD): approach & cartography. In: 2018 4th International Symposium on Geoinformatics (ISyG), pp. 1–5. IEEE (2018)
Sarraf, J., Priyadarshini, I., Pattnaik, P.K.: Real time bus monitoring system. In: Satapathy, S.C., Mandal, J.K., Udgata, S.K., Bhateja, V. (eds.) Information Systems Design and Intelligent Applications. AISC, vol. 433, pp. 551–557. Springer, New Delhi (2016). https://doi.org/10.1007/978-81-322-2755-7_57
Sharad, S., Sivakumar, P.B., Narayanan, V.A.: The smart bus for a smart city – A real-time implementation. In: 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (2016). https://doi.org/10.1109/ants.2016.7947850
Stradling, S., Carreno, M., Rye, T., Noble, A.: Passenger perceptions and the ideal urban bus journey experience. Transp. Policy 14(4), 283–292 (2007)
Sygic API: (2020). https://www.sygic.com/developers/maps-api-services/javascript-map-api. Accessed October 2020
Tan, K., Wong, K.: Low-cost campus bus tracker using WiFi access points. In: 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW) (2016). https://doi.org/10.1109/icce-tw.2016.7520904
Thong, C.L., Chaw, L.Y., Chit, S.M., Lee, C.Y.: User evaluation on mobile application for shuttle bus service. In: SoMeT, pp. 422–429, September 2019
Watkins, K.E., Ferris, B., Borning, A., Rutherford, G.S., Layton, D.: Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders. Transp. Res. Part A Policy Practice 45(8), 839–848 (2011). https://doi.org/10.1016/j.tra.2011.06.010
Waze: About the Waze Transport SDK. Retrieved in October 2020, (2020). https://developers.google.com/waze/intro-transport
Willmott, C.J., Matsuura, K.: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate Res. 30(1), 79–82 (2005)
**ung, J., **ung, J., Wong, A., Wong, A.: Canalys: Vivo overtakes Samsung as Malaysia's #1 smartphone vendor in Q2 2020, August 07 2020. https://www.soyacincau.com/2020/08/07/malaysia-top-5-smartphone-vendor-vivo-canalys-q2-2020/
Yim, Y.B., Ceder, A.: Smart feeder/shuttle bus service: consumer research and design. J. Public Transp. 9(1), 5 (2006)
Yu, H., **ao, R., Du, Y., He, Z.: A bus-arrival time prediction model based on historical traffic patterns. In: 2013 International Conference on Computer Sciences and Applications (2013). https://doi.org/10.1109/csa.2013.87
Yue, W.S., Hoy, C.W., Chye, K.K.: A preliminary survey analysis of school shuttle bus system towards smart mobility solutions. In: AIP Conference Proceedings, vol. 1891, No. 1, p. 020146. AIP Publishing LLC, October 2017
Zhou, P., Jiang, S., and Li, M.: Urban traffic monitoring with the help of bus riders. In: 2015 IEEE 35th International Conference on Distributed Computing Systems, 21–30 (2015). Author, F.: Article title. Journal 2(5), 99–110 (2016)
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The authors would like to thank CERVIE (Centre of Excellence for Research, Value Innovation and Entrepreneurship), UCSI University Kuala Lumpur, Malaysia for sponsoring this publication.
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Shu Qian, G. et al. (2022). A Comparative Study of Navigation API ETA Accuracy for Shuttle Bus Tracking. In: Salvendy, G., Wei, J. (eds) Design, Operation and Evaluation of Mobile Communications. HCII 2022. Lecture Notes in Computer Science, vol 13337. Springer, Cham. https://doi.org/10.1007/978-3-031-05014-5_37
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