Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

SMADS - An ITS in a Wide-Area Public Transportation Network


Affiliations
1 Department of Computer Electronics and Graphics Technology, Central Connecticut State University, New Britain, United States
2 Department of Management and Education, University of Pittsburgh, Bradford, PA,, United States
     

   Subscribe/Renew Journal


In this paper, we propose an untraditional Intelligent Transportation System (ITS) that deploys in a wide-area public transportation network. Based on emerging digitalized supply chain service (including logistics), peer-to-peer/ad-hoc network, blockchain and Internet of Things (IoT) technologies, our proposed SMADS system has these new features and advantages compared to traditional transportation systems: self-organizing, multi-relayed, across-strangers, decentralized, and sharing-economy-based. We identify two essential requirements for this network system — availability and reliability. To meet these requirements, we compare this network system with existing similar ones and pinpoint two major technical challenges — connectivity/routing maintenance and trust management. We apply latest development in technologies in above-mentioned areas to design solutions to address these challenges. The resulted system can operate on top of existing multiple separate segments of transportation links to form a wide-area transportation network, which enlarges services with low cost. Additionally, the notion has potential application in a wide range of various services. We hope to bring this to readers’ attention for further discussion and improvement.

Keywords

Blockchain, Connectivity, ITS, Network, Routing.
Subscription Login to verify subscription
User
Notifications
Font Size


  • “New Application for Ride Sharing”. Accessed Jan. 2021. [Online]. Available: http://lazooz.org/
  • “Arcade City: The Future of Ridesharing is Decentralized”. Accessed: Jan. 2021. [Online]. Available: https://fee.org/articles/arcade-city-the-fu ture-of-ridesha ring-is-decentralized/
  • T. C. Hu, “The maximum capacity route problem,” Operations Research, vol. 9, no. 6, pp. 898-900, 1961.
  • F. Chin, and D. Houck, “Algorithms for updating minimal spanning trees,” Journal of Computer and System Sciences, vol. 16, no. 3, pp. 333-344, 1978.
  • S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system,” 2008. [Online]. Available: https://bitcoin.org/ bitcoin.pdf
  • Z. Ji, H. Pi, W. Wei, B. Xiong, M. Woźniak, and R. Damasevicius, “Recommendation based on review texts and social communities: A hybrid model,” IEEE Access, vol. 7, pp. 40416-40427, 2019.
  • R. K. Behera, S. K. Rath, S. Misra, R. Damasevicius, and R. Maskeliunas, “Large scale community detection using a small world model,” Applied Sciences, vol. 7, no. 11, pp. 1-18, 2017, Art. no. 1173.
  • R. Colomo-Palacios, F. J. García-Peñalvo, V. Stantchev, and S. Misrad, “Towards a social and context-aware mobile recommendation system for tourism,” Pervasive and Mobile Computing, vol. 38, part. 2, pp. 505-515, 2017.
  • Rabbani, and Aslam, “Internet service selection using service association factor (SAF),” Information Technology and Control, vol. 48, no. 1, pp. 104-114, 2019.
  • T. G. Crainica, M. Gendreaub, and J.-Y. Potvin, “Intelligent freight-transportation systems: Assess-ment and the contribution of operations research,” Transportation Research Part C: Emerging Technol-ogies, vol. 17, no. 6, pp. 541-557, 2009.
  • M. Rahimi, A. Baboli, and Y. Rekik, “Sustainable inventory routing problem for perishable products by considering reverse logistic,” International Federation of Automatic Control, vol. 49, no. 12, pp. 949-954, 2016.
  • C. Cheng, P. Yang, M. Qi, and L.-M. Rousseau, “Modeling a green inventory routing problem with a heterogeneous fleet,” Transportation Research Part E: Logistics and Transportation Review, vol. 97, pp. 97-112, Jan. 2017.
  • Y. Li, F. Chu, C. Feng, C. Chu, and M. Zhou, “Integrated production inventory routing planning for intelligent food logistics systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 3, pp. 867-878, 2019.
  • H. Anisi, and H. Abdullah, “Efficient data reporting in intelligent transportation systems,” Networks and Spatial Economics, vol. 16, no. 2, pp. 623-642, 2015.
  • B. Y. Chen, X.-W. Chen, H.-P. Chen, and W. H. K. Lam, “Efficient algorithm for finding k shortest paths based on re-optimization technique,” Transportation Research Part E Logistics and Transportation Review, vol. 133, pp. 1-13, 2020.
  • E. Q. V. Martins, and M. M. B. Pascoal, “A new implementation of Yen’s ranking loopless paths algorithm,” 4OR, vol. 1, no. 2, pp. 121-133, 2003.
  • L. Yang, and X. Zhou, “Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks: Linear mixed integer programming reformulations,” Transportation Research Part B: Methodological, vol. 96, pp. 68-91, 2017.
  • H. Yu, Z. Fang, F. Alan, T. Murray, H. Peng, and J. Chen, “Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes,” Applied Energy, vol. 237, pp. 390-403, 2019.
  • Y.-S. Myung, and Y.-M. Yu, “Freight transportation network model with bundling option,” Transportation Research Part E: Logistics and Transportation Review, vol. 133, pp. 1-11, 2020, Art. no. 101827.
  • Z. Kuang, Z. Lian, J. W. Lien, and J. Zheng, “Serial and parallel duopoly competition in multi-segment transportation routes,” Transportation Research Part E: Logistics and Transportation Review, vol. 133, pp. 1-23, 2020, Art. no. 101821.
  • L. Wei, J. Zhang, R. Dai, and G. Zhu, “Green flexible vs. inflexible capacity strategies for duopoly,” Transportation Research Part E: Logistics and Transportation Review, vol. 122, pp. 247-267, Feb. 2019.
  • M. De, and B. C. Giri, “Modelling a closed-loop supply chain with a heterogeneous fleet under carbon emission reduction policy,” Transportation Research Part E Logistics and Transportation Review, vol. 133, pp. 1-24, 2020, Art. no. 101813.
  • S. Zhao, and K. Wang, “A framework for a decentralized and self-organized mail service network,” Proceedings of the 14th International Conference on Future Networks and Communications (FNC), 2019, pp. 327-334.

Abstract Views: 153

PDF Views: 0




  • SMADS - An ITS in a Wide-Area Public Transportation Network

Abstract Views: 153  |  PDF Views: 0

Authors

Shushan Zhao
Department of Computer Electronics and Graphics Technology, Central Connecticut State University, New Britain, United States
Wes C. Chiang
Department of Management and Education, University of Pittsburgh, Bradford, PA,, United States

Abstract


In this paper, we propose an untraditional Intelligent Transportation System (ITS) that deploys in a wide-area public transportation network. Based on emerging digitalized supply chain service (including logistics), peer-to-peer/ad-hoc network, blockchain and Internet of Things (IoT) technologies, our proposed SMADS system has these new features and advantages compared to traditional transportation systems: self-organizing, multi-relayed, across-strangers, decentralized, and sharing-economy-based. We identify two essential requirements for this network system — availability and reliability. To meet these requirements, we compare this network system with existing similar ones and pinpoint two major technical challenges — connectivity/routing maintenance and trust management. We apply latest development in technologies in above-mentioned areas to design solutions to address these challenges. The resulted system can operate on top of existing multiple separate segments of transportation links to form a wide-area transportation network, which enlarges services with low cost. Additionally, the notion has potential application in a wide range of various services. We hope to bring this to readers’ attention for further discussion and improvement.

Keywords


Blockchain, Connectivity, ITS, Network, Routing.

References