Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions

Abstract

Owing to the advancements in communication and computation technologies, the dream of commercialized connected and autonomous cars is becoming a reality. However, among other challenges such as environmental pollution, cost, maintenance, security, and privacy, the ownership of vehicles (especially for Autonomous Vehicles) is the major obstacle in the realization of this technology at the commercial level. Furthermore, the business model of pay-as-you-go type services further attracts the consumer, because there is no need for upfront investment. In this vein, the idea of car-sharing (aka carpooling) is getting ground due to, at least in part, its simplicity, cost-effectiveness, and affordable choice of transportation. Carpooling systems are still in their infancy and face challenges such as scheduling, matching passengers interests, business model, security, privacy, and communication. To date, a plethora of research work has already been done covering different aspects of carpooling services (ranging from applications to communication and technologies); however, there is still a lack of a holistic, comprehensive survey that can be a one-stop-shop for the researchers in this area to (i) find all the relevant information and (ii) identify the future research directions. To fill these research challenges, this article provides a comprehensive survey on carpooling in autonomous and connected vehicles and covers architecture, components, and solutions, including scheduling, matching, mobility, pricing models of carpooling. We also discuss the current challenges in carpooling and identify future research directions. This survey is aimed to spur further discussion among the research community for the effective realization of carpooling.

REFERENCES

1. [1] Abraham Hillary, Lee Chaiwoo, Brady Samantha, Fitzgerald Craig, Mehler Bruce, Reimer Bryan, and Coughlin Joseph F.. 2016. Autonomous vehicles, trust, and driving alternatives: A survey of consumer preferences. Massachusetts Inst. Technol, AgeLab, Cambridge 1 (2016), 16.
2. [2] Agatz Niels, Erera Alan, Savelsbergh Martin, and Wang Xing. 1 December 2012. Optimization for dynamic ride-sharing: A review. Eur. J. Operat. Res. 223, 2 (1 December 2012), 295–303.
3. [3] Agatz Niels, Erera Alan L., Savelsbergh Martin W. P., and Wang Xing. 2011. Dynamic ride-sharing: A simulation study in metro Atlanta. Proc. Soc. Behav. Sci. 17 (2011), 532–550.
4. [4] Aïvodji Ulrich Matchi, Gambs Sébastien, Huguet Marie-José, and Killijian Marc-Olivier. 2016. Meeting points in ridesharing: A privacy-preserving approach. Transport. Res. C: Emerg. Technol. 72 (2016), 239–253.
5. [5] Aïvodji Ulrich Matchi, Huguenin Kévin, Huguet Marie-José, and Killijian Marc-Olivier. 2018. Sride: A privacy-preserving ridesharing system. In Proceedings of the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks. 40–50.
6. [6] An Sunghi, Nam Daisik, and Jayakrishnan R.. 2019. Impacts of integrating shared autonomous vehicles into a Peer-to-Peer ridesharing system. Proc. Comput. Sci. 151 (1 2019), 511–518.
7. [7] Andersson Magnus, Hjalmarsson Anders, and Avital Michel. 2013. Peer-to-Peer service sharing platforms: Driving share and share alike on a mass-scale. In Proceedings of the 34th International Conference on Information Systems (ICIS’13).
8. [8] Androutsopoulos Konstantinos N. and Zografos Konstantinos G.. 2009. Solving the multi-criteria time-dependent routing and scheduling problem in a multimodal fixed scheduled network. Eur. J. Operat. Res. 192, 1 (2009), 18–28.
9. [9] Antoniou Constantinos, Efthymiou Dimitrios, and Chaniotakis Emmanouil Manos. 2019. Demand for Emerging Transportation Systems: Modeling Adoption, Satisfaction, and Mobility Patterns. Elsevier.
10. [10] Asghari Mohammad, Deng Dingxiong, Shahabi Cyrus, Demiryurek Ugur, and Li Yaguang. 2016. Price-aware real-time ride-sharing at scale: An auction-based approach. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 1–10.
11. [11] Bakkal F., Eken S., Savaş N. S., and Sayar A.. 2017. Modeling and querying trajectories using Neo4j spatial and TimeTree for carpool matching. In Proceedings of the IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA’17). 219–222.
12. [12] Balasubramanian Venkatraman, Aloqaily Moayad, Tunde-Onadele Olufogorehan, Yang Zhengyu, and Reisslein Martin. 2020. Reinforcing cloud environments via index policy for bursty workloads. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium (NOMS’20). IEEE, 1–7.
13. [13] Balasubramanian Venkatraman, Aloqaily Moayad, Zaman Faisal, and Jararweh Yaser. 2018. Exploring computing at the edge: A multi-interface system architecture enabled mobile device cloud. In Proceedings of the IEEE 7th International Conference on Cloud Networking (CloudNet’18). IEEE, 1–4.
14. [14] Balasubramanian Venkatraman, Otoum Safa, Aloqaily Moayad, Ridhawi Ismaeel Al, and Jararweh Yaser. 2020. Low-latency vehicular edge: A vehicular infrastructure model for 5G. Simul. Model. Pract. Theory 98 (2020), 101968.
15. [15] Balasubramanian Venkatraman, Zaman Faisal, Aloqaily Moayad, Ridhawi Ismaeel Al, Jararweh Yaser, and Salameh Haythem Bany. 2019. A mobility management architecture for seamless delivery of 5G-IoT services. In Proceedings of the IEEE International Conference on Communications (ICC’19). IEEE, 1–7.
16. [16] Balasubramanian Venkatraman, Zaman Faisal, Aloqaily Moayad, Alrabaee Saed, Gorlatova Maria, and Reisslein Martin. 2019. Reinforcing the edge: Autonomous energy management for mobile device clouds. In Proceedings of the IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS’19). IEEE, 44–49.
17. [17] Banerjee D. and Srivastava B.. 2015. Promoting carpooling with distributed schedule coordination and incentive alignment of contacts. In Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems. 1837–1842.
18. [18] Bertsimas Dimitris, Jaillet Patrick, and Martin Sébastien. 2019. Online vehicle routing: The edge of optimization in large-scale applications. Operat. Res. 67, 1 (2019), 143–162.
19. [19] Bonhomme C., Arnould G., and Khadraoui D.. 2012. Dynamic carpooling mobility services based on secure multi-agent platform. In Proceedings of the Global Information Infrastructure and Networking Symposium (GIIS’12). 1–6.
20. [20] Bonomi Flavio, Milito Rodolfo, Zhu Jiang, and Addepalli Sateesh. 2012. Fog computing and its role in the internet of things. In Proceedings of the 1st MCC Workshop on Mobile Cloud Computing. 13–16.
21. [21] Boukhater C. M., Dakroub O., Lahoud F., Awad M., and Artail H.. 2014. An intelligent and fair GA carpooling scheduler as a social solution for greener transportation. In Proceedings of the17th IEEE Mediterranean Electrotechnical Conference (MELECON’14). 182–186.
22. [22] Boysen Nils, Briskorn Dirk, Schwerdfeger Stefan, and Stephan Konrad. 2021. Optimizing carpool formation along high-occupancy vehicle lanes. Eur. J. Operat. Res. 293, 3 (2021), 1097–1112.
23. [23] Bresciani C., Colorni A., Costa F., Luè A., and Studer L.. 2018. Carpooling: Facts and new trends. In Proceedings of the International Conference of Electrical and Electronic Technologies for Automotive. 1–4.
24. [24] Caballero-Gil Cándido, Caballero-Gil Pino, Molina-Gil Jezabel, Martín-Fernández Francisco, and Loia Vincenzo. 2017. Trust-based cooperative social system applied to a carpooling platform for smartphones. Sensors 17, 2 (2017), 245.
25. [25] Calvert S. C., Schakel W. J., and Lint C. J. W. van. 2017. Will automated vehicles negatively impact traffic flow?J. Adv. Transport. (2017), 1–17.
26. [26] Calvo Roberto Wolfler, Luigi Fabio de, Haastrup Palle, and Maniezzo Vittorio. 2004. A distributed geographic information system for the daily car pooling problem. Comput. Operat. Res. 31, 13 (2004), 2263–2278.
27. [27] Chan Nelson D. and Shaheen Susan A.. 2012. Ridesharing in North America: Past, present, and future. Transp. Rev. 32, 1 (2012), 93–112.
28. [28] Cheikh Sondes Ben and Hammadi Slim. 2014. The alliance between optimization and multi-agent system for the management of the dynamic carpooling. In Agent and Multi-Agent Systems: Technologies and Applications. Springer, 193–202.
29. [29] Cheikh-Graiet Sondes Ben, Dotoli Mariagrazia, and Hammadi Slim. 2020. A Tabu Search based metaheuristic for dynamic carpooling optimization. Comput. Industr. Eng. 140 (2020), 106217.
30. [30] Chen Lu, Zhong Qilu, Xiao Xiaokui, Gao Yunjun, Jin Pengfei, and Jensen Christian S.. 2018. Price-and-time-aware dynamic ridesharing. In Proceedings of the IEEE 34th International Conference on Data Engineering (ICDE’18). IEEE, 1061–1072.
31. [31] Chen Rui, Fung Benjamin C. M., Mohammed Noman, Desai Bipin C., and Wang Ke. 2013. Privacy-preserving trajectory data publishing by local suppression. Inf. Sci. 231 (2013), 83–97.
32. [32] Chen Tong Donna et al. 2015. Management of a Shared, Autonomous, Electric Vehicle Fleet: Vehicle Choice, Charging Infrastructure & Pricing Strategies. Ph.D. Dissertation. The University of Virginia.
33. [33] Chen T. Donna and Kockelman Kara M.. 2016. Management of a shared autonomous electric vehicle fleet: Implications of pricing schemes. Transport. Res. Rec. 2572, 1 (2016), 37–46.
34. [34] Chen T. Donna, Kockelman Kara M., and Hanna Josiah P.. 2016. Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions. Transport. Res. A: Policy Pract. 94 (2016), 243–254.
35. [35] Chiang Mung, Ha Sangtae, Chih-Lin I., Risso Fulvio, and Zhang Tao. 2017. Clarifying fog computing and networking: 10 questions and answers. IEEE Commun. Mag. 55, 4 (2017), 18–20.
36. [36] Lin Chih-Hsiang, Jiau Ming-Kai, and Huang Shih-Chia. 2012. A cloud computing framework for real-time carpooling services. In Proceedings of the 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM’12). 266–271.
37. [37] Chou S., Jiau M., and Huang S.. 2016. Stochastic set-based particle swarm optimization based on local exploration for solving the carpool service problem. IEEE Trans. Cybernet. 46, 8 (2016), 1771–1783.
38. [38] Ciari Francesco, Balac Milos, and Balmer Michael. 2015. Modelling the effect of different pricing schemes on free-floating carsharing travel demand: A test case for Zurich, Switzerland. Transportation 42, 3 (2015), 413–433.
39. [39] Clements Lewis M. and Kockelman Kara M.. 2017. Economic effects of automated vehicles. J. Transport. Res. Board2606 (2017), 106–114.
40. [40] Coindreau Marc-Antoine, Gallay Olivier, and Zufferey Nicolas. 2018. Synchronizing heterogeneous vehicles in a routing and scheduling context. In Proceedings of the 16th International Conference on Project Management and Scheduling. 79.
41. [41] Collotta M., Pau G., Salerno V. M., and Scatà G.. 2012. A novel trust based algorithm for carpooling transportation systems. In Proceedings of the IEEE International Energy Conference and Exhibition (ENERGYCON’12). 1077–1082.
42. [42] Cruz M. O., Macedo H., and Guimarães A.. 2015. Grouping similar trajectories for carpooling purposes. In Proceedings of the Brazilian Conference on Intelligent Systems (BRACIS’15). 234–239.
43. [43] Créno Lisa and Cahour Beatrice. 2015. Perceived risks and trust experience in a service of Carpooling. In Proceedings of the 22nd ITS World Congress.
44. [44] Dawy Zaher, Husseini Ahmad, Yaacoub Elias, and Al-Kanj Lina. 2010. A wireless communications laboratory on cellular network planning. IEEE Trans. Educ. 53, 4 (2010), 653–661.
45. [45] Delhomme Patricia and Gheorghiu Alexandra. 2016. Comparing French carpoolers and non-carpoolers: Which factors contribute the most to carpooling?Transport. Res. D: Transport Environ. 42 (2016), 1–15.
46. [46] Di Xuan and Ban Xuegang Jeff. 2019. A unified equilibrium framework of new shared mobility systems. Transport. Res. B: Methodol. 129 (2019), 50–78.
47. [47] Diana Marco. 2006. The importance of information flows temporal attributes for the efficient scheduling of dynamic demand responsive transport services. J. Adv. Transport. 40, 1 (2006), 23–46.
48. [48] Dimitrijević Dejan, Dimitrieski Vladimir, and Nedić Nemanja. 2014. Prototype implementation of a scalable real-time dynamic carpooling and ride-sharing application. Informatica 38, 3 (2014).
49. [49] Dimitrijević D., Nedić N., and Dimitrieski V.. 2013. Real-time carpooling and ride-sharing: Position paper on design concepts, distribution and cloud computing strategies. In Proceedings of the Federated Conference on Computer Science and Information Systems. 781–786.
50. [50] Duan Y., Mosharraf T., Wu J., and Zheng H.. 2018. Optimizing carpool scheduling algorithm through partition merging. In Proceedings of the IEEE International Conference on Communications (ICC’18). 1–6.
51. [51] Elbery A., ElNainay M., and Rakha H.. 2016. Proactive and reactive carpooling recommendation system based on spatiotemporal and geosocial data. In Proceedings of the IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob’16). 1–8.
52. [52] Enzi Miriam, Parragh Sophie N., Pisinger David, and Prandtstetter Matthias. 2020. Modeling and solving the multimodal car-and ride-sharing problem. arXiv:2001.05490. Retrieved from https://arxiv.org/abs/2001.05490.
53. [53] Feng H., Sengbin Y., Ruichun H., and Xiaoyao W.. 2015. Research on optimization model of taxi-carpooling expenses based on the passengers’ personalized demand. In Proceedings of the International Conference on Transportation Information and Safety (ICTIS’15). 246–249.
54. [54] Ferguson Erik. 1997. The rise and fall of the American carpool: 1970–1990. Transportation 24, 4 (1997), 349–376.
55. [55] Ferrari Emilio, Manzini Riccardo, Pareschi Arrigo, Persona Alessandro, and Regattieri Alberto. 2003. The car pooling problem: Heuristic algorithms based on savings functions. J. Adv. Transport. 37, 3 (2003), 243–272.
56. [56] Fougères A., Canalda P., Ecarot T., Samaali A., and Guglielmetti L.. 2012. A push service for carpooling. In Proceedings of the IEEE International Conference on Green Computing and Communications. 685–691.
57. [57] Friginal Jesús, Gambs Sébastien, Guiochet Jérémie, and Killijian Marc-Olivier. 2014. Towards privacy-driven design of a dynamic carpooling system. Perv. Mobile Comput. 14 (2014), 71–82.
58. [58] Furuhata Masabumi, Dessouky Maged, Ordóñez Fernando, Brunet Marc-Etienne, Wang Xiaoqing, and Koenig Sven. November 2013. Ridesharing: The state-of-the-art and future directions. Transport. Res. B: Methodol. 57 (November 2013), 28–46.
59. [59] Gadsby E., Jaimes S., Najarian L., Sanchez M., Sujlana R., Donohue G. L., and Coyne M.. 2003. George Mason University (GMU) Fairfax campus transportation system. In Proceedings of the IEEE Systems and Information Engineering Design Symposium. 77–82.
60. [60] Garrison William L., Wellar Barry, MacKinnon Ross, Black William R., and Getis Arthur. 2011. Research Commentary: Increasing the Flexibility of Legacy Systems. Int. J. Appl. Geospat. Res. 2, 2 (2011), 39–55.
61. [61] Goel Preeti, Kulik Lars, and Ramamohanarao Kotagiri. 2016. Optimal pick up point selection for effective ride sharing. IEEE Trans. Big Data 3, 2 (2016), 154–168.
62. [62] Goel Preeti, Kulik Lars, and Ramamohanarao Kotagiri. 2016. Privacy-aware dynamic ride sharing. ACM Trans. Spatial Algor. Syst. 2, 1 (2016), 1–41.
63. [63] Graziotin Daniel. 2013. An Analysis of issues against the adoption of Dynamic Carpooling. arxiv:1306.0361. Retrieved from http://arxiv.org/abs/1306.0361.
64. [64] Guidotti Riccardo, Nanni Mirco, Rinzivillo Salvatore, Pedreschi Dino, and Giannotti Fosca. 2017. Never drive alone: Boosting carpooling with network analysis. Inf. Syst. 64 (2017), 237–257.
65. [65] Hallgren Per, Orlandi Claudio, and Sabelfeld Andrei. 2017. PrivatePool: Privacy-preserving ridesharing. In Proceedings of the IEEE 30th Computer Security Foundations Symposium (CSF’17). IEEE, 276–291.
66. [66] Hariz M. B., Said D., and Mouftah H. T.. 2019. Mobility traffic model based on combination of multiple transportation forms in the smart city. In Proceedings of the 15th International Wireless Communications Mobile Computing Conference (IWCMC’19). 14–19.
67. [67] Hartman Irith Ben-Arroyo, Keren Daniel, Dbai Abed Abu, Cohen Elad, Knapen Luk, Janssens Davy, et al. 2014. Theory and practice in large carpooling problems. Proc. Comput. Sci. 32 (2014), 339–347.
68. [68] Hasan Raza, Bhatti Abdul Hadi, Hayat Mohammad Sohail, Gebreyohannes Haftamu Menker, Ali Syed Imran, and Syed Abeer Javed. 2016. Smart peer car pooling system. In Proceedings of the 3rd MEC International Conference on Big Data and Smart City (ICBDSC’16). IEEE, 1–6.
69. [69] Hassine M., Canalda P., and Hassine I.. 2017. Dynamic intra-modal carpooling with transhipment: Formalization and first combinatorial exact solution. In Proceedings of the IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computed, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI’17). 1–8.
70. [70] He W., Hwang K., and Li D.. 2014. Intelligent carpool routing for urban ridesharing by mining gps trajectories. IEEE Trans. Intell. Transport. Syst. 15, 5 (2014), 2286–2296.
71. [71] He Y., Ni J., Wang X., Niu B., Li F., and Shen X.. 2018. Privacy-Preserving partner selection for ride-sharing services. IEEE Trans. Vehic. Technol. 67, 7 (2018), 5994–6005.
72. [72] Herbawi Wesam and Weber Michael. 2012. The ridematching problem with time windows in dynamic ridesharing: A model and a genetic algorithm. In Proceedings of the IEEE Congress on Evolutionary Computation. IEEE, 1–8.
73. [73] Hong Zihan, Chen Ying, Mahmassani Hani S., and Xu Shuang. 2017. Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology, application and impact evaluation. Transport. Res. C: Emerg. Technol. 85 (2017), 573–590.
74. [74] Huang J., Wu J., and Chen L.. 2018. Coalitional game based carpooling algorithms for quality of experience. In Proceedings of the IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS’18). 1–5.
75. [75] Huang J., Wu J., Chen L., and Yan J.. 2019. Utility-Aware batch-processing algorithms for dynamic carpooling based on double auction. In Proceedings of the IEEE International Conference on Parallel Distributed Processing with Applications, Big Data Cloud Computing, Sustainable Computing Communications, Social Computing Networking (ISPA/BDCloud/SocialCom/SustainCom’19). 1059–1063.
76. [76] Huang S., Jiau M., and Chong K.. 2018. A heuristic multi-objective optimization algorithm for solving the carpool services problem featuring high-occupancy-vehicle itineraries. IEEE Trans. Intell. Transport. Syst. 19, 8 (2018), 2663–2674.
77. [77] Huang S., Jiau M., and Lin C.. 2015. A genetic-algorithm-based approach to solve carpool service problems in cloud computing. IEEE Trans. Intell. Transport. Syst. 16, 1 (2015), 352–364.
78. [78] Huang S., Jiau M., and Liu Y.. 2019. An ant path-oriented carpooling allocation approach to optimize the carpool service problem with time windows. IEEE Syst. J. 13, 1 (2019), 994–1005.
79. [79] Huang Shih-Chia, Jiau Ming-Kai, and Lin Chih-Hsiang. 2014. Optimization of the carpool service problem via a fuzzy-controlled genetic algorithm. IEEE Trans. Fuzzy Syst. 23, 5 (2014), 1698–1712.
80. [80] Huang Yan, Jin Ruoming, Bastani Favyen, and Wang Xiaoyang Sean. 2013. Large scale real-time ridesharing with service guarantee on road networks. arXiv:1302.6666. Retrieved from https://arxiv.org/abs/1302.6666.
81. [81] Hussain R., Abbas F., Son J., Eun H., and Oh H.. 2013. Privacy-aware route tracing and revocation games in VANET-based clouds. In Proceedings of the IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob’13). 730–735.
82. [82] Hussain Rasheed, Hussain Fatima, and Zeadally Sherali. 2019. Integration of VANET and 5G Security: A review of design and implementation issues. Fut. Gener. Comput. Syst. 101 (2019), 843–864.
83. [83] Hussain R., Lee J., and Zeadally S.. 2018. Autonomous cars: Social and economic implications. IT Profess. 20, 6 (November 2018), 70–77.
84. [84] Jadhao R. B. and Patil J. M.. 2017. Recommendation system for carpooling and regular taxicab services. In Proceedings of the International Conference on Inventive Systems and Control (ICISC’17). 1–8.
85. [85] M. N. Jean. 2014. France falls out of love with the car. The Guardian. Retrieved from https://www.theguardian.com/world/2014/nov/09/france-car-ownership-sales-downturn.
86. [86] Jeribi Karama, Mejri Hinda, Zgaya Hayfa, and Hammadi Slim. 2011. Vehicle sharing services optimization based on multi-agent approach. IFAC Proc. Vol. 44, 1 (2011), 13040–13045.
87. [87] Jiau M. and Huang S.. 2015. Services-Oriented computing using the compact genetic algorithm for solving the carpool services problem. IEEE Trans. Intell. Transport. Syst. 16, 5 (2015), 2711–2722.
88. [88] Jiau M. and Huang S.. 2019. Self-Organizing neuroevolution for solving carpool service problem with dynamic capacity to alternate matches. IEEE Trans. Neural Netw. Learn. Syst. 30, 4 (2019), 1048–1060.
89. [89] Jiau M., Huang S., and Lin C.. 2013. Optimizing the carpool service problem with genetic algorithm in service-based computing. In Proceedings of the IEEE International Conference on Services Computing. 478–485.
90. [90] Jin Fanglei, Yao Enjian, and An Kun. 2020. Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution. J. Transport Geogr. 82 (2020), 102630.
91. [91] Kesting Arne, Treiber Martin, Schönhof Martin, Kranke Florian, and Helbing Dirk. 2007. Jam-avoiding adaptive cruise control (ACC) and its impact on traffic dynamics. In Traffic and Granular Flow’05. Springer, 633–643.
92. [92] Khattak Hasan Ali, Shah Munam Ali, Khan Sangeen, Ali Ihsan, and Imran Muhammad. 2019. Perception layer security in Internet of Things. Fut. Gener. Comput. Syst. 100 (2019), 144–164.
93. [93] Lafrance Adrienne. 2016. Your Grandmother’s Driverless Car. Retrieved from https://www.theatlantic.com/technology/archive/2016/06/beep-beep/489029/.
94. [94] Li Desheng, He Qian, Liu Chunli, and Yu Hongjie. 2017. Real-Time carpooling system on android terminal using session initiation protocol and location based service. J. Comput. Theoret. Nanosci. 14, 4 (2017), 2069–2076.
95. [95] Li J., Huang T., Chen S., and Yang Y.. 2018. Optimization based on taxi carpooling preferences and pricing. In Proceedings of the 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD’18). 108–112.
96. [96] Li M., Zhu L., and Lin X.. 2019. Efficient and privacy-preserving carpooling using blockchain-assisted vehicular fog computing. IEEE IoT J. 6, 3 (2019), 4573–4584.
97. [97] Li Meng, Zhu Liehuang, Zhang Zijian, and Xu Rixin. 2017. Achieving differential privacy of trajectory data publishing in participatory sensing. Inf. Sci. 400 (2017), 1–13.
98. [98] Li Qing, Liao Feixiong, Timmermans Harry J. P., Huang Haijun, and Zhou Jing. 2018. Incorporating free-floating car-sharing into an activity-based dynamic user equilibrium model: A demand-side model. Transport. Res. B: Methodol. 107 (2018), 102–123.
99. [99] Li Ruimin, Liu Zhiyong, and Zhang Ruibo. 2018. Studying the benefits of carpooling in an urban area using automatic vehicle identification data. Transport. Res. C: Emerg. Technol. 93 (2018), 367–380.
100. [100] Li S., Fei F., Ruihan D., Yu S., and Dou W.. 2016. A dynamic pricing method for carpooling service based on coalitional game analysis. In Proceedings of the IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS’16). 78–85.
101. [101] Li Shuai, Zhu Haojin, Gao Zhaoyu, Guan Xinping, Xing Kai, and Shen Xuemin. 2012. Location privacy preservation in collaborative spectrum sensing. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’12). IEEE, 729–737.
102. [102] Lin J., Huang S., and Jiau M.. 2019. An evolutionary multiobjective carpool algorithm using set-based operator based on simulated binary crossover. IEEE Trans. Cybernet. 49, 9 (2019), 3432–3442.
103. [103] Liu Nianbo, Liu Ming, Cao Jiannong, Chen Guihai, and Lou Wei. 2010. When transportation meets communication: V2P over VANETs. In Proceedings of the IEEE 30th International Conference on Distributed Computing Systems. IEEE, 567–576.
104. [104] Liu Zhidan, Gong Zengyang, Li Jiangzhou, and Wu Kaishun. 2020. Mobility-Aware dynamic taxi ridesharing. In Proceedings of the IEEE 36th International Conference on Data Engineering (ICDE’20). IEEE, 961–972.
105. [105] Lloret-Batlle Roger, Masoud Neda, and Nam Daisik. 2017. Peer-to-Peer ridesharing with ride-back on high-occupancy-vehicle lanes: Toward a practical alternative mode for daily commuting. Transport. Res. Rec. 2668, 1 (2017), 21–28.
106. [106] Lou Yingyan, Yin Yafeng, and Laval Jorge A.. 2011. Optimal dynamic pricing strategies for high-occupancy/toll lanes. Transport. Res. C: Emerg. Technol. 19, 1 (2011), 64–74.
107. [107] Luo Y., Jia X., Fu S., and Xu M.. 2019. pRide: Privacy-Preserving Ride Matching Over Road Networks for Online Ride-Hailing Service. IEEE Trans. Inf. Forens. Secur. 14, 7 (2019), 1791–1802.
108. [108] Ma Changxi, He Ruichun, and Zhang Wei. 2018. Path optimization of taxi carpooling. PLoS One 13, 8 (2018).
109. [109] Ma Jiaqi, Li Xiaopeng, Zhou Fang, and Hao Wei. 2017. Designing optimal autonomous vehicle sharing and reservation systems: A linear programming approach. Transport. Res. C: Emerg. Technol. 84 (2017), 124–141.
110. [110] Ma Rui and Zhang H. M.. 2017. The morning commute problem with ridesharing and dynamic parking charges. Transport. Res. B: Methodol. 106 (2017), 345–374.
111. [111] Ma Shuo, Zheng Yu, and Wolfson Ouri. 2013. T-share: A large-scale dynamic taxi ridesharing service. In Proceedings of the IEEE 29th International Conference on Data Engineering (ICDE’13). IEEE, 410–421.
112. [112] Ma Shuo, Zheng Yu, and Wolfson Ouri. 2014. Real-time city-scale taxi ridesharing. IEEE Trans. Knowl. Data Eng. 27, 7 (2014), 1782–1795.
113. [113] Malik Sayyam, Khattak Hasan Ali, Ameer Zoobia, Shoaib Umar, Rauf Hafiz Tayyab, and Song Houbing. 2021. Proactive scheduling and resource management for connected autonomous vehicles: A data science perspective. IEEE Sens. J. 21, 22 (2021), 25151–25160.
114. [114] Mallus Matteo, Colistra Giuseppe, Atzori Luigi, Murroni Maurizio, and Pilloni Virginia. 2017. Dynamic carpooling in urban areas: Design and experimentation with a multi-objective route matching algorith. Sustainability 9, 2 (2017), 254.
115. [115] Mao Lina, Li Wenquan, Hu Pengsen, Zhou Guiliang, Zhang Huiting, and Zhou Xuanyu. 2019. Urban arterial road optimization and design combined with hov carpooling under connected vehicle environment. J. Adv. Transport. 2019 (2019).
116. [116] Marco-Gisbert Hector and Ripoll Ismael. 2013. Preventing brute force attacks against stack canary protection on networking servers. In Proceedings of the IEEE 12th International Symposium on Network Computing and Applications. IEEE, 243–250.
117. [117] Martín-Fernández Francisco, Caballero-Gil Cándido, and Caballero-Gil Pino. 2015. A trustworthy distributed social carpool method. In European Conference on Parallel Processing. Springer, 324–335.
118. [118] Masoud Neda and Jayakrishnan R.. 2017. A decomposition algorithm to solve the multi-hop peer-to-peer ride-matching problem. Transportation Research Part B: Methodological 99 (2017), 1–29.
119. [119] Masoud Neda and Jayakrishnan R.. 2017. A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system. Transport. Res. B: Methodol. 106 (2017), 218–236.
120. [120] Masoud Neda, Lloret-Batlle Roger, and Jayakrishnan R.. 2017. Using bilateral trading to increase ridership and user permanence in ridesharing systems. Transport. Res. E: Logist. Transport. Rev. 102 (2017), 60–77.
121. [121] Masoud Neda, Nam Daisik, Yu Jiangbo, and Jayakrishnan R.. 2017. Promoting peer-to-peer ridesharing services as transit system feeders. Transport. Res. Rec. 2650, 1 (2017), 74–83.
122. [122] Massaro Dominic W., Chaney Benjamin, Bigler Stephanie, Lancaster Jessica, Iyer Suresh, Gawade Mrunal, Eccleston Michael, Gurrola Edith, and Lopez Angelica. 2009. Just-in-Time carpooling without elaborate preplanning. In Proceedings of the 5th International Conference on Web Information Systems and Technologies (Webist’09). 219–224.
123. [123] Megalingam R. K., Nair R. N., and Radhakrishnan V.. 2011. Automated wireless carpooling system for an eco-friendly travel. In Proceedings of the 3rd International Conference on Electronics Computer Technology, Vol. 4. 325–329.
124. [124] Meng Hui, Ran Lun, Chen Jing, and Jiao Zihao. 2017. Goal-Driven approach to optimize matching mechanism in electric vehicles ride-sharing system. Energy Proc. 105 (2017), 2273–2280.
125. [125] Mo Daniel Y., Wang Yue, Lee Y. C. E., and Tseng Mitchell M.. 2018. Mass customizing paratransit services with a ridesharing option. IEEE Trans. Eng. Manage. (2018).
126. [126] Montes Rosana, Sanchez Ana M., Villar Pedro, and Herrera Francisco. 2018. Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust. Appl. Soft Comput. 67 (2018), 941–952.
127. [127] Moradi Behzad. 2019. The new optimization algorithm for the vehicle routing problem with time windows using multi-objective discrete learnable evolution model. Soft Comput. (2019), 1–29.
128. [128] Mourad Abood, Puchinger Jakob, and Chu Chengbin. 2019. A survey of models and algorithms for optimizing shared mobility. Transport. Res. B: Methodol. 123 (2019), 323–346.
129. [129] Nagare Deepak B., More Kishor L., Tanwar Nitin S., Kulkarni S. S., and Gunda Kalyan C.. 2013. Dynamic carpooling application development on Android platform. Int. J. Innovat. Technol. Explor. Eng. 2, 3 (2013), 136–139.
130. [130] Ni Jianbing, Zhang Kuan, Lin Xiaodong, and Shen Xuemin Sherman. 2017. Securing fog computing for internet of things applications: Challenges and solutions. IEEE Commun. Surv. Tutor. 20, 1 (2017), 601–628.
131. [131] Ni Jianbing, Zhang Kuan, Lin Xiaodong, Yang Haomiao, and Shen Xuemin Sherman. 2016. AMA: Anonymous mutual authentication with traceability in carpooling systems. In Proceedings of the IEEE Int. Conf. Commun. (ICC’16). IEEE, 1–6.
132. [132] Pamula Rajendra and Chakraborty Rini. 2017. Taxi recommender system using ridesharing service. In Proceedings of the 4th International Conference on Advanced Computing and Communication Systems (ICACCS’17). IEEE, 1–6.
133. [133] Paul Sunil, Khanna Jahan, Wong Robert, and Moran Robert. 2016. Systems and methods for providing transportation discounts in shared rides. US Patent App. 14/794,425.
134. [134] Pearson Siani and Balacheff Boris. 2003. Trusted Computing Platforms: TCPA Technology in Context. Prentice Hall Professional.
135. [135] Pelzer Dominik, Xiao Jiajian, Zehe Daniel, Lees Michael H., Knoll Alois C., and Aydt Heiko. 2015. A partition-based match making algorithm for dynamic ridesharing. IEEE Trans. Intell. Transport. Syst. 16, 5 (2015), 2587–2598.
136. [136] Gong Pengfei and Li Wenquan. 2011. Urban traffic demand control based on carpooling: A case of Nanjing. In Proceedings of the International Conference on Remote Sensing, Environment and Transportation Engineering. 1863–1866.
137. [137] Perboli Guido, Ferrero Francesco, Musso Stefano, and Vesco Andrea. 2018. Business models and tariff simulation in car-sharing services. Transport. Res. A: Policy Pract. 115 (2018), 32–48.
138. [138] Pham Anh, Dacosta Italo, Endignoux Guillaume, Pastoriza Juan Ramon Troncoso, Huguenin Kévin, and Hubaux Jean-Pierre. 2017. Oride: A privacy-preserving yet accountable ride-hailing service. In Proceedings of the 26th USENIX Security Symposium (USENIX Security’17). 1235–1252.
139. [139] Pham Anh, Dacosta Italo, Jacot-Guillarmod Bastien, Huguenin Kévin, Hajar Taha, Tramèr Florian, Gligor Virgil, and Hubaux Jean-Pierre. 2017. Privateride: A privacy-enhanced ride-hailing service. Proc. Priv. Enhanc. Technol. 2017, 2 (2017), 38–56.
140. [140] Qadir H., Khalid O., Khan M. U. S., Khan A. U. R., and Nawaz R.. 2018. An optimal ride sharing recommendation framework for carpooling services. IEEE Access 6 (2018), 62296–62313.
141. [141] Qi X., Wang L., and Wang X.. 2016. Optimization of carpooling based on complete subgraphs. In Proceedings of the 35th Chinese Control Conference (CCC’16). 9294–9299.
142. [142] Qu Fengzhong, Wu Zhihui, Wang Fei-Yue, and Cho Woong. 2015. A security and privacy review of VANETs. IEEE Trans. Intell. Transport. Syst. 16, 6 (2015), 2985–2996.
143. [143] Rayle Lisa, Dai Danielle, Chan Nelson, Cervero Robert, and Shaheen Susan. 2016. Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco. Transport Pol. 45 (2016), 168–178.
144. [144] Rios-Torres Jackeline and Malikopoulos Andreas A.. 2016. A survey on the coordination of connected and automated vehicles at intersections and merging at highway on-ramps. IEEE Trans. Intell. Transport. Syst. 18, 5 (2016), 1066–1077.
145. [145] Hahn Robert Metcalfe and Robert. 2017. The Ridesharing Revolution: Economic Survey and Synthesis, Vol. IV. Oxford University Press.
146. [146] Salamanis Athanasios, Kehagias Dionysios D., Tsoukalas Dimitrios, and Tzovaras Dimitrios. 2019. Reputation assessment mechanism for carpooling applications based on clustering user travel preferences. Int. J. Transport. Sci. Technol. 8, 1 (2019), 68–81.
147. [147] Sánchez David, Martínez Sergio, and Domingo-Ferrer Josep. 2016. Co-utile P2P ridesharing via decentralization and reputation management. Transport. Res. C: Emerg. Technol. 73 (2016), 147–166.
148. [148] Sayarshad Hamid R. and Gao H. Oliver. 2018. A scalable non-myopic dynamic dial-a-ride and pricing problem for competitive on-demand mobility systems. Transport. Res. C: Emerg. Technol. 91 (2018), 192–208.
149. [149] Sghaier Manel, Zgaya Hayfa, Hammadi Slim, and Tahon Christian. 2010. A distributed dijkstra’s algorithm for the implementation of a Real Time Carpooling Service with an optimized aspect on siblings. In Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems. IEEE, 795–800.
150. [150] Sghaier Manel, Zgaya Hayfa, Hammadi Slim, and Tahon Christian. 2010. Ortic: A novel approach towards optimized real time carpooling with an advanced network representation model on siblings. IFAC Proc. Vol. 43, 8 (2010), 367–375.
151. [151] Sghaier Manel, Zgaya Hayfa, Hammadi Slim, and Tahon Christian. 2011. A distributed optimized approach based on the multi agent concept for the implementation of a real time carpooling service with an optimization aspect on siblings. Int. J. Eng. 5, 2 (2011), 217.
152. [152] Sghaier M., Zgaya H., Hammadi S., and Tahon C.. 2011. A novel approach based on a distributed dynamic graph modeling set up over a subdivision process to deal with distributed optimized real time carpooling requests. In Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems (ITSC’11). 1311–1316.
153. [153] Shaheen Susan A. and Lipman Timothy E.. 2007. Reducing greenhouse emissions and fuel consumption: Sustainable approaches for surface transportation. IATSS Res. 31, 1 (2007), 6–20.
154. [154] Shaheen Susan, Cohen Adam, and Bayen Alexandre. 2018. The Benefits of Carpooling. Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7jx6z631. Institute of Transportation Studies, UC Berkeley.
155. [155] Shao Z. Z., Wang H. G., Liu H., Song C., Meng C., and Yu H.. 2013. Heuristic optimization algorithms of multi-carpooling problem based on two-stage clustering. J. Comput. Res. Dev. (2013).
156. [156] Sharma Surbhi and Kaushik Baijnath. 2019. A survey on internet of vehicles: Applications, security issues & solutions. Vehic. Commun. 20 (2019), 100182.
157. [157] Miller Brent R. Heard and Shelie A.. 2016. The environmental impact of autonomous vehicles depends on adoption patterns. Environ. Sci. Technol. 50, 12 (2016), 6119–6121.
158. [158] Shen Zukang, Papasakellariou Aris, Montojo Juan, Gerstenberger Dirk, and Xu Fangli. 2012. Overview of 3GPP LTE-advanced carrier aggregation for 4G wireless communications. IEEE Commun. Mag. 50, 2 (2012), 122–130.
159. [159] Sherif A. B. T., Rabieh K., Mahmoud M. M. E. A., and Liang X.. 2017. Privacy-Preserving ride sharing scheme for autonomous vehicles in big data era. IEEE IoT J. 4, 2 (2017), 611–618.
160. [160] Shi Q. and Chen X.. 2020. Carpool for big data: Enabling efficient crowd cooperation in data market for pervasive AI. IEEE Trans. Vehic. Technol. (2020), 1–1.
161. [161] Shladover Steven E.. 2009. Cooperative (rather than autonomous) vehicle-highway automation systems. IEEE Intell. Transport. Syst. Ma. 1, 1 (2009), 10–19.
162. [162] Shladover Steven E., Su Dongyan, and Lu Xiao-Yun. 2012. Impacts of cooperative adaptive cruise control on freeway traffic flow. Transport. Res. Rec. 2324, 1 (2012), 63–70.
163. [163] Silwal Shrawani, Gani Md Osman, and Raychoudhury Vaskar. 2019. A survey of taxi ride sharing system architectures. In Proceedings of the IEEE International Conference on Smart Computing (SMARTCOMP’19). IEEE, 144–149.
164. [164] Song Fei, Li Rong, and Zhou Huachun. 2015. Feasibility and issues for establishing network-based carpooling scheme. Perv. Mobile Comput. 24 (2015), 4–15.
165. [165] Standing Craig, Standing Susan, and Biermann Sharon. 2019. The implications of the sharing economy for transport. Transport Rev. 39, 2 (2019), 226–242.
166. [166] Stiglic Mitja, Agatz Niels, Savelsbergh Martin, and Gradisar Mirko. 2015. The benefits of meeting points in ride-sharing systems. Transport. Res. B: Methodol. 82 (2015), 36–53.
167. [167] Stiglic Mitja, Agatz Niels, Savelsbergh Martin, and Gradisar Mirko. 2016. Making dynamic ride-sharing work: The impact of driver and rider flexibility. Transport. Res. E: Logist. Transport. Rev. 91 (2016), 190–207.
168. [168] Storck C. R. and Duarte-Figueiredo F.. 2020. A survey of 5G technology evolution, standards, and infrastructure associated with vehicle-to-everything communications by internet of vehicles. IEEE Access 8 (2020), 117593–117614.
169. [169] Tahmasseby Shahram, Kattan Lina, and Barbour Brian. 2016. Propensity to participate in a peer-to-peer social-network-based carpooling system. J. Adv. Transport. 50, 2 (2016), 240–254.
170. [170] Tahon Christian, Hammadi Slim, et al. 2016. An evolutionary approach to solve the dynamic multi-hop ridematching problem. SIMULATION (2016).
171. [171] Tang F., Kawamoto Y., Kato N., and Liu J.. 2020. Future intelligent and secure vehicular network toward 6G: Machine-Learning approaches. Proc. IEEE 108, 2 (2020), 292–307.
172. [172] Tong Wei, Hua Jingyu, and Zhong Sheng. 2017. A jointly differentially private scheduling protocol for ridesharing services. IEEE Trans. Inf. Forens. Secur. 12, 10 (2017), 2444–2456.
173. [173] Tyagi Amit Kumar and Niladhuri Sreenath. 2016. Ensuring trust and privacy in large carpooling problems. In Proceeding of the International Conference on Computational Intelligence and Communication (CIC’16), Vol. 14. 1–11.
174. [174] Tyagi Amit Kumar and Sreenath N.. 2016. Providing together security, location privacy and trust for moving objects. Int. J. Hybrid Inf. Technol. 9, 3 (2016), 221–240.
175. [175] Tyagi Amit Kumar and Sreenath N.. 2016. Vehicular Ad Hoc Networks: New challenges in carpooling and parking services. In Proceeding of International Conference on Computational Intelligence and Communication (CIC’16), Vol. 14.
176. [176] Wang Fengwei, Zhu Hui, Liu Ximeng, Lu Rongxing, Li Fenghua, Li Hui, and Zhang Songnian. 2018. Efficient and privacy-preserving dynamic spatial query scheme for ride-hailing services. IEEE Trans. Vehic. Technol. 67, 11 (2018), 11084–11097.
177. [177] Wang W., Chen Y., Zhang Q., Wu K., and Zhang J.. 2016. Less transmissions, more throughput: Bringing carpool to public WLANs. IEEE Trans. Mobile Comput. 15, 5 (2016), 1168–1181.
178. [178] Wang Xing, Agatz Niels, and Erera Alan. 2018. Stable matching for dynamic ride-sharing systems. Transport. Sci. 52, 4 (2018), 850–867.
179. [179] Wang Xiaolei, He Fang, Yang Hai, and Gao H. Oliver. 2016. Pricing strategies for a taxi-hailing platform. Transport. Res. E: Logist. Transport. Rev. 93 (2016), 212–231.
180. [180] Wright Steve, Nelson John D., and Cottrill Caitlin D.. 2020. MaaS for the suburban market: Incorporating carpooling in the mix. Transport. Res. A: Policy Pract. 131 (2020), 206–218.
181. [181] Wu Yongzhong, Chen Xiangying, and Ma Jingwen. 2018. Modeling passengers’ choice in ride-hailing service with dedicated-ride option and ride-sharing option. In Proceedings of the 4th International Conference on Industrial and Business Engineering. 94–98.
182. [182] Xi Yong, Schwiebert Loren, and Shi Weisong. 2014. Privacy preserving shortest path routing with an application to navigation. Perv. Mobile Comput. 13 (2014), 142–149.
183. [183] Xia Jizhe, Curtin Kevin M., Huang Jiajun, Wu Di, Xiu Wenqun, and Huang Zhengdong. 2019. A carpool matching model with both social and route networks. Comput. Environ. Urban Syst. 75 (2019), 90–102.
184. [184] Xiao Qiang, He Ruichun, Ma Changxi, and Zhang Wei. 2019. Evaluation of urban taxi-carpooling matching schemes based on entropy weight fuzzy matter-element. Appl. Soft Comput. 81 (2019), 105493.
185. [185] Xiao Qiang, He RuiChun, Zhang Wei, and Ma C. X.. 2014. Algorithm research of taxi carpooling based on fuzzy clustering and fuzzy recognition. J. Transport. Syst. Eng. Inf. Technol. 14, 5 (2014), 119–125.
186. [186] Xiao Qiang and He R.-C.. 2017. Carpooling scheme selection for taxi carpooling passengers: A multi-objective model and optimisation algorithm. Arch. Transport 42 (2017).
187. [187] Xiong Zehui, Feng Shaohan, Wang Wenbo, Niyato Dusit, Wang Ping, and Han Zhu. 2018. Cloud/fog computing resource management and pricing for blockchain networks. IEEE IoT J. 6, 3 (2018), 4585–4600.
188. [188] Yan S., Chen C., and Chang S.. 2014. A car pooling model and solution method with stochastic vehicle travel times. IEEE Trans. Intell. Transport. Syst. 15, 1 (2014), 47–61.
189. [189] Yan Wangcheng, Zhou Wenjun, Tan Chang, and Fan Lei. 2019. Employee ridesharing: Reinforcement learning and choice modeling. In Proceedings of the 25th Americas Conference on Information Systems (AMCIS’19).
190. [190] Yang Hai and Huang Hai-Jun. 1999. Carpooling and congestion pricing in a multilane highway with high-occupancy-vehicle lanes. Transport. Res. A: Policy Pract. 33, 2 (1999), 139–155.
191. [191] Yeung S., Aziz H. M. A., and Madria S.. 2019. Activity-Based shared mobility model for smart transportation. In Proceedings of the 20th IEEE International Conference on Mobile Data Management (MDM’19). 599–604.
192. [192] Yu H., Jia X., Zhang H., Yu X., and Shu J.. 2019. PSRide: Privacy-Preserving shared ride matching for online ride hailing systems. IEEE Trans. Depend. Secure Comput. (2019), 1–1.
193. [193] Yu H., Shu J., Jia X., Zhang H., and Yu X.. 2019. lpRide: Lightweight and privacy-preserving ride matching over road networks in online ride hailing systems. IEEE Trans. Vehic. Technol. 68, 11 (2019), 10418–10428.
194. [194] Yu Xiaojuan, Berg Vincent A. C. van den, and Verhoef Erik T.. 2019. Carpooling with heterogeneous users in the bottleneck model. Transport. Res. B: Methodol. 127 (2019), 178–200.
195. [195] Hou Yunfei, Li X., and Qiao C.. 2012. TicTac: From transfer-incapable carpooling to transfer-allowed carpooling. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’12). 268–273.
196. [196] Zeng Cheng and Oren Nir. 2014. Dynamic taxi pricing. Front. Artif. Intell. Appl. (2014).
197. [197] Zha Liteng, Yin Yafeng, and Du Yuchuan. 2017. Surge pricing and labor supply in the ride-sourcing market. Transport. Res. Proc. 23, 2–21 (2017), 5–2.
198. [198] Zhang Chaoli, Xie Jiapeng, Wu Fan, Gao Xiaofeng, and Chen Guihai. 2020. Pricing and allocation algorithm designs in dynamic ridesharing system. Theor. Comput. Sci. 803 (2020), 94–104.
199. [199] Zhang D., He T., Liu Y., Lin S., and Stankovic J. A.. 2014. A carpooling recommendation system for taxicab services. IEEE Trans. Emerg. Top. Comput. 2, 3 (2014), 254–266.
200. [200] Zhang Desheng, He Tian, Liu Yunhuai, and Stankovic John A.. 2013. CallCab: A unified recommendation system for carpooling and regular taxicab services. In Proceedings of the IEEE International Conference on Big Data. IEEE, 439–447.
201. [201] Zhang Desheng, He Tian, Zhang Fan, Lu Mingming, Liu Yunhuai, Lee Haengju, and Son Sang H.. 2016. Carpooling service for large-scale taxicab networks. ACM Trans. Sens. Netw. 12, 3 (2016), 1–35.
202. [202] Zhang F., Yang Z. J., Wang Y., and Kuang F.. 2016. An augmented estimation of distribution algorithm for multi-carpooling problem with time window. In Proceedings of the IEEE 83rd Vehicular Technology Conference (VTC Spring). 1–5.
203. [203] Zhang J. T.. 2016. A research the dynamic pricing strategy of taxi software. J. Tangsh. Univ. 29, 6 (2016), 78–84.
204. [204] Zhang Wei, He Ruichun, Chen Yong, Gao Mingxia, and Ma Changxi. 2019. Research on taxi pricing model and optimization for carpooling detour problem. J. Adv. Transport. (2019).
205. [205] Zhang Wei, He Ruichun, Ma Changxi, and Gao Mingxia. 2018. Research on taxi driver strategy game evolution with carpooling detour. J. Adv. Transport. (2018).
206. [206] Zhang Wei, He Ruichun, Xiao Qiang, and Ma Changxi. 2017. Taxi carpooling model and carpooling effects simulation. Int. J. Simul. Process Model. 12, 3–4 (2017), 338–346.
207. [207] Zhang Z., Wang G., Cao B., and Han Y.. 2015. Data services for carpooling based on large-scale traffic data analysis. In Proceedings of the IEEE International Conference on Services Computing. 672–679.
208. [208] Zhao Tianlu, Yang Yongjian, and Wang En. 2020. Minimizing the average arriving distance in carpooling. Int. J. Distrib. Sens. Netw. 16, 1 (2020), 1550147719899369.
209. [209] Zhou Guiliang, Lv Mengru, Bao Tianwen, Mao Lina, and Huang Kai. 2019. Design of intelligent carpooling program based on big data analysis and multi-information perception. Clust. Comput. 22, 1 (2019), 521–532.
210. [210] Zhou Zhuping, Zhang Kai, Zhu Wenbo, and Wang Yinhai. 2019. Modeling lane-choice behavior to optimize pricing strategy for HOT lanes: A support vector regression approach. J. Transport. Eng. A: Syst. 145, 4 (2019), 04019004.
211. [211] Zhu Liehuang, Li Meng, Zhang Zijian, and Qin Zhan. 2018. ASAP: An anonymous smart-parking and payment scheme in vehicular networks. IEEE Trans. Depend. Secure Comput. (2018).

Index Terms

• Computer systems organization

  • Dependable and fault-tolerant systems and networks

    • Redundancy

  • Embedded and cyber-physical systems

    • Embedded systems

    • Robotics

• Networks

  • Network properties

    • Network reliability