隨著都會人口的快速增長，上下班通勤與交通運輸成為我們日常生
活中不可或缺的一部分，因此，共乘(也稱作合夥用車或計程車共享)
已經成為最近紓緩交通壓力的熱門議題之一。這種新興的運輸方式，利
用與他人共搭一輛車的特性，使得道路上的交通資源可以更妥善運用，
並降低整體行車時的碳排放量。目前的共乘服務為單次共乘，每位乘客
從起點到目的地由一輛車服務。因為沒有提供轉乘的機制，減少了可能
共乘的機會，無法進一步提升車輛共乘率。
本篇論文提出了一個基於公共計程車派遣系統的即時轉乘機制，根
據中央伺服器的車輛即時路線資訊，旅途中的乘客可以更換所搭乘的車
輛，用更少的時間到達目的地，藉此提高整體的運輸效率。此機制能夠
即時為適合轉乘的乘客尋找合適的轉乘地點，並且計算出轉乘前與轉乘
後兩台車的後續路線。效能評估模擬採用曼哈頓中城地區道路，與沒有
轉乘機制的共乘相比，結果顯示轉乘方案能有效提升共乘效率，多數乘
客藉由轉乘省下旅行時間與旅途距離，並且道路上的公共計程車也能得
到更多載客機會。

Daily commute and personal travel are an indispensable part of our lives. Due to convenience and flexibility, the ridesharing (also referred as carpooling or taxi-sharing) has become one of the most popular issues to relieve the huge traffic demands in urban areas. Carpooling, an emerging transport service, can share the vehicle with other passengers. Therefore, higher traffic resource sharing and lower carbon emission are foreseeable. However, the existing ridesharing services usually support one-hop delivery. Each passenger arrives at the destination by taking only one vehicle. This thesis develops a real-time transfer approach based on a centralized pubic taxicab scheduling system. The approach can improve the traffic efficiency by leveraging real-time trajectory information of vehicles maintained in the system. The system can search for a suitable location for the passenger who could be transferred, and calculate the subsequent routes for original and transfer taxicabs. The simulation results based on the Manhattan Midtown road networks demonstrate the effectiveness of the developed scheme compared to the transfer-disallowed scheme. Several passengers can be transferred to other vehicles to save more travel time and travel distance. Taxicabs on the roads can be used more efficiently.

[1] “Statistics on the 2016 National Travel Survey.” [Online]. Available:
https://www.gov.uk/government/statistics/national-travel-survey-2016, 2018.
[2] G. Dimitrakopoulos and P. Demestichas, “Intelligent Transportation Systems,”
IEEE Vehicular Technology Magazine, vol. 5, no. 1, pp. 77–84, Mar. 2010.
[3] “IEEE News Releases,” Sept. 2012. [Online]. Available:
https://www.ieee.org/about/news/2012/5september-2-2012.html, 2018.
[4] W. He, K. Hwang, and D. Li, “Intelligent Carpool Routing for Urban Rideshar-
ing by Mining GPS Trajectories,” IEEE Transactions on Intelligent Transportation
Systems, vol. 15, no. 5, pp. 2286–2296, Oct. 2014.
[5] S. Ma, Y. Zheng, and O. Wolfson, “T-Share: A Large-Scale Dynamic Taxi Rideshar-
ing Service,” in Proceedings of the IEEE International Conference on Data Engineer-
ing, Apr. 2013, pp. 410–421.
[6] D. Zhang, Y. Li, F. Zhang, M. Lu, Y. Liu, and T. He, “coRide: Carpool Service
with a Win-Win Fare Model for Large-Scale Taxicab Networks,” in Proceedings of
the ACM Conference on Embedded Networked Sensor Systems, Nov. 2013, pp. 1–14.
[7] D. Zhang, T. He, Y. Liu, and J. A. Stankovic, “CallCab: A Unified Recommendation
System for Carpooling and Regular Taxicab Services,” in Proceedings of the IEEE
International Conference on Big Data, Oct. 2013, pp. 439–447.
[8] M. Zhu, X. Y. Liu, F. Tang, M. Qiu, R. Shen, W. Shu, and M. Y. Wu, “Pub-
lic Vehicles for Future Urban Transportation,” IEEE Transactions on Intelligent
Transportation Systems, vol. 17, no. 12, pp. 3344–3353, Dec. 2016.
[9] M. Zhu, X. Y. Liu, and X. Wang, “An Online Ride-Sharing Path-Planning Strat-
egy for Public Vehicle Systems,” IEEE Transactions on Intelligent Transportation
Systems, pp. 1–12, May 2018.
[10] M. Zhu, L. Kong, X. Y. Liu, R. Shen, W. Shu, and M. Y. Wu, “A Public Vehicle
System with Multiple Origin-Destination Pairs on Traffic Networks,” in Proceedings
of the IEEE Global Communications Conference, Dec. 2015, pp. 1–6.
[11] Y. Lai, F. Yang, L. Zhang, and Z. Lin, “Distributed Public Vehicle System Based
on Fog Nodes and Vehicular Sensing,” IEEE Access, vol. 6, pp. 22 011–22 024, Apr.
2018.
[12] M. Ota, H. Vo, C. Silva, and J. Freire, “STaRS: Simulating Taxi Ride Sharing at
Scale,” IEEE Transactions on Big Data, vol. 3, no. 3, pp. 349–361, Sept. 2017.
[13] S. Ma, Y. Zheng, and O. Wolfson, “Real-Time City-Scale Taxi Ridesharing,” IEEE
Transactions on Knowledge and Data Engineering, vol. 27, no. 7, pp. 1782–1795,
July 2015.
[14] M. Zhu, R. Shen, W. Shu, and M. Y. Wu, “Traffic Efficiency Improvement and
Passengers Comfort in Ridesharing Systems in VANETs,” in Proceedings of the In-
ternational Conference on Connected Vehicles and Expo, Oct. 2015, pp. 116–121.
[15] M. Zhu, X. Y. Liu, M. Qiu, R. Shen, W. Shu, and M. Y. Wu, “Transfer Problem in a
Cloud-based Public Vehicle System with Sustainable Discomfort,” Mobile Networks
and Applications, vol. 21, no. 5, pp. 890–900, Oct. 2016.
[16] H. H. Peng, “A Multi-Pool Transferring Carpooling System,” Master’s thesis, Na-
tional Chiao Tung University, July 2011.
[17] Y. Hou, X. Li, and C. Qiao, “TicTac: From Transfer-Incapable Carpooling to
Transfer-Allowed Carpooling,” in Proceedings of the IEEE Global Communications
Conference, Dec. 2012, pp. 268–273.
[18] P. Bouros, D. Sacharidis, T. Dalamagas, and T. Sellis, “Dynamic Pickup and Deliv-
ery with Transfers,” in Proceedings of the International Symposium on Spatial and
Temporal Databases, Aug. 2011, pp. 112–129.
[19] R. Masson, F. Lehu´ed´e, and O. P´eton, “The Dial-A-Ride Problem with Transfers,”
Computers and Operations Research, vol. 41, pp. 12–23, Jan. 2014.
[20] Y. Hou, W. Zhong, L. Su, K. Hulme, A. W. Sadek, and C. Qiao, “TASeT: Im-
proving the Efficiency of Electric Taxis With Transfer-Allowed Rideshare,” IEEE
Transactions on Vehicular Technology, vol. 65, no. 12, pp. 9518–9528, Dec. 2016.
[21] “SUMO - Simulation of Urban MObility.” [Online]. Avail-
able: http://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931 read-41000/,
2018.
[22] “TraCI - Traffic Control Interface.” [Online]. Available:
http://sumo.dlr.de/wiki/TraCI, 2018.