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Demand-Responsive Mobility for Rural Areas: A Review

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Highlights in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection (PAAMS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1678))

Abstract

Demand-responsive mobility is currently considered an environmentally conscious transportation option that can improve user experience and cut operating costs. Many works propose and analyse demand-responsive transportation systems for urban areas with a high displacement demand. However, the number of works that propose these systems for rural settlements, where scattered populations and low demand are present, is reduced. This work discusses the challenges and open issues found in rural demand-responsive transportation extracted from the review of various recent publications. The commented solutions are approached through artificial intelligence and computer science techniques. Finally, conclusions on the topic are presented, including recommendations for better quality future research.

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References

  1. Anburuvel, A., Perera, W., Randeniya, R.: A demand responsive public transport for a spatially scattered population in a developing country. Case Stud. Transp. Policy 10(1), 187–197 (2022)

    Article  Google Scholar 

  2. Balmer, M., Rieser, M., Meister, K., Charypar, D., Lefebvre, N., Nagel, K.: MATSim-T: architecture and simulation times. In: Multi-agent Systems for Traffic and Transportation Engineering, pp. 57–78. IGI Global (2009)

    Google Scholar 

  3. Bertelle, C., Nabaa, M., Olivier, D., Tranouez, P.: A decentralised approach for the transportation on demand problem. In: Aziz-Alaoui, M.A., Bertelle, C. (eds.) From System Complexity to Emergent Properties, pp. 281–289. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02199-2_13

    Chapter  Google Scholar 

  4. Billhardt, H., Fernández, A., Ossowski, S., Palanca, J., Bajo, J.: Taxi dispatching strategies with compensations. Expert Syst. Appl. 122, 173–182 (2019)

    Article  Google Scholar 

  5. Bischoff, J., Maciejewski, M.: Proactive empty vehicle rebalancing for demand responsive transport services. Procedia Comput. Sci. 170, 739–744 (2020)

    Article  Google Scholar 

  6. Calabrò, G., Le Pira, M., Giuffrida, N., Inturri, G., Ignaccolo, M., Correia, G.: Fixed-route vs demand-responsive transport feeder services: an exploratory study using an agent-based model. J. Adv. Transp. 2022 (2022)

    Google Scholar 

  7. Coutinho, F.M., van Oort, N., Christoforou, Z., Alonso-González, M.J., Cats, O., Hoogendoorn, S.: Impacts of replacing a fixed public transport line by a demand responsive transport system: case study of a rural area in Amsterdam. Res. Transp. Econ. 83, 100910 (2020)

    Google Scholar 

  8. Currie, G., Fournier, N.: Why most DRT/micro-transits fail-what the survivors tell us about progress. Res. Transp. Econ. 83, 100895 (2020)

    Google Scholar 

  9. Dytckov, S., Persson, J.A., Lorig, F., Davidsson, P.: Potential benefits of demand responsive transport in rural areas: a simulation study in Lolland, Denmark. Sustainability 14(6) (2022)

    Google Scholar 

  10. Enoch, M., Potter, S., Parkhurst, G., Smith, M.: Why do demand responsive transport systems fail? In: Transportation Research Board 85th Annual Meeting, Washington DC, USA (2006)

    Google Scholar 

  11. Ho, S.C., Szeto, W., Kuo, Y.H., Leung, J.M., Petering, M., Tou, T.W.: A survey of dial-a-ride problems: literature review and recent developments. Transp. Res. Part B: Methodol. 111, 395–421 (2018)

    Article  Google Scholar 

  12. Hunter, A., Chalaguine, L., Czernuszenko, T., Hadoux, E., Polberg, S.: Towards computational persuasion via natural language argumentation dialogues. In: Benzmüller, C., Stuckenschmidt, H. (eds.) KI 2019. LNCS (LNAI), vol. 11793, pp. 18–33. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30179-8_2

    Chapter  Google Scholar 

  13. Hyland, M., Mahmassani, H.S.: Operational benefits and challenges of shared-ride automated mobility-on-demand services. Transp. Res. Part A: Policy Pract. 134, 251–270 (2020)

    Google Scholar 

  14. Inturri, G., Giuffrida, N., Ignaccolo, M., Le Pira, M., Pluchino, A., Rapisarda, A.: Testing demand responsive shared transport services via agent-based simulations. In: Daniele, P., Scrimali, L. (eds.) New Trends in Emerging Complex Real Life Problems. ASS, vol. 1, pp. 313–320. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00473-6_34

    Chapter  Google Scholar 

  15. Jordan, J., Palanca, J., Marti, P., Julian, V.: Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation. Expert Syst. Appl. 197, 116739 (2022)

    Google Scholar 

  16. Lakatos, A., Tóth, J., Mándoki, P.: Demand responsive transport service of ‘dead-end villages’ in interurban traffic. Sustainability 12(9) (2020)

    Google Scholar 

  17. Liu, J., Zhu, B.: An intelligent personal assistant robot: BoBi secretary. In: 2nd International Conference on Advanced Robotics and Mechatronics (ICARM), pp. 402–407 (2017)

    Google Scholar 

  18. Liyanage, S., Dia, H.: An agent-based simulation approach for evaluating the performance of on-demand bus services. Sustainability 12(10) (2020)

    Google Scholar 

  19. Marković, N., Kim, M.E., Kim, E., Milinković, S.: A threshold policy for dispatching vehicles in demand-responsive transit systems. Promet - Traffic & Transp. 31(4), 387–395 (2019)

    Google Scholar 

  20. Martí, P., Jordán, J., De la Prieta, F., Billhardt, H., Julian, V.: Demand-responsive shared transportation: a self-interested proposal. Electronics 11(1) (2022)

    Google Scholar 

  21. Mo, B., Kong, H., Wang, H., Wang, X.C., Li, R.: Impact of pricing policy change on on-street parking demand and user satisfaction: a case study in Nanning, China. Transp. Res. Part A: Policy Pract. 148, 445–469 (2021)

    Google Scholar 

  22. Palanca, J., Terrasa, A., Carrascosa, C., Julián, V.: SimFleet: a new transport fleet simulator based on MAS. In: De La Prieta, F., et al. (eds.) PAAMS 2019. CCIS, vol. 1047, pp. 257–264. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24299-2_22

    Chapter  Google Scholar 

  23. Ryley, T.J., Stanley, P.A., Enoch, M.P., Zanni, A.M., Quddus, M.A.: Investigating the contribution of demand responsive transport to a sustainable local public transport system. Res. Transp. Econ. 48, 364–372 (2014)

    Article  Google Scholar 

  24. Schade, J., Schlag, B.: Acceptability of urban transport pricing strategies. Transport. Res. F: Traffic Psychol. Behav. 6(1), 45–61 (2003)

    Article  Google Scholar 

  25. Schlüter, J., Bossert, A., Rössy, P., Kersting, M.: Impact assessment of autonomous demand responsive transport as a link between urban and rural areas. Res. Transp. Bus. Manag. 39, 100613 (2021)

    Google Scholar 

  26. Tisue, S., Wilensky, U.: NetLogo: a simple environment for modeling complexity. In: International Conference on Complex Systems, Boston, MA, vol. 21, pp. 16–21 (2004)

    Google Scholar 

  27. Vallée, S., Oulamara, A., Cherif-Khettaf, W.R.: Maximizing the number of served requests in an online shared transport system by solving a dynamic DARP. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds.) ICCL 2017. LNCS, vol. 10572, pp. 64–78. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68496-3_5

    Chapter  Google Scholar 

  28. van Engelen, M., Cats, O., Post, H., Aardal, K.: Enhancing flexible transport services with demand-anticipatory insertion heuristics. Transp. Res. Part E: Logist. Transp. Rev. 110, 110–121 (2018)

    Article  Google Scholar 

  29. Vansteenwegen, P., Melis, L., Aktaş, D., Montenegro, B.D.G., Vieira, F.S., Sörensen, K.: A survey on demand-responsive public bus systems. Transp. Res. Part C: Emerg. Technol. 137, 103573 (2022)

    Google Scholar 

  30. Viergutz, K., Schmidt, C.: Demand responsive - vs. conventional public transportation: a MATSim study about the rural town of Colditz, Germany. Procedia Comput. Sci. 151, 69–76 (2019)

    Article  Google Scholar 

  31. Ye, B., Ge, F., Rong, X., Li, L.: The influence of nonlinear pricing policy on residential electricity demand—a case study of Anhui residents. Energ. Strat. Rev. 13, 115–124 (2016)

    Article  Google Scholar 

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Acknowledgements

This work is partially supported by grant RTI2018-095390-B-C31 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe. Pasqual Martí is supported by grant ACIF/2021/259 funded by the “Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana”. Jaume Jordán is supported by grant IJC2020-045683-I funded by MCIN/AEI/ 10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”.

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Authors and Affiliations

  1. Valencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politécnica de Valéncia, Camino de Vera s/n, 46022, Valencia, Spain

    Pasqual Martí, Jaume Jordán & Vicente Julian

Authors
  1. Pasqual Martí
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  2. Jaume Jordán
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  3. Vicente Julian
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Corresponding author

Correspondence to Pasqual Martí .

Editor information

Editors and Affiliations

  1. University of Salamanca, Salamanca, Spain

    Alfonso González-Briones

  2. Institute of Engineering - Polytechnic of Porto, Porto, Portugal

    Ana Almeida

  3. Universidad Rey Juan Carlos, Madrid, Spain

    Alberto Fernandez

  4. German International University, Cairo, Egypt

    Alia El Bolock

  5. University of Minho, Braga, Portugal

    Dalila Durães

  6. Universitat Politècnica de València, Valencia, Spain

    Jaume Jordán

  7. National Laboratory of Energy and Geology, Amadora, Portugal

    Fernando Lopes

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Martí, P., Jordán, J., Julian, V. (2022). Demand-Responsive Mobility for Rural Areas: A Review. In: González-Briones, A., et al. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection. PAAMS 2022. Communications in Computer and Information Science, vol 1678. Springer, Cham. https://doi.org/10.1007/978-3-031-18697-4_11

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  • DOI: https://doi.org/10.1007/978-3-031-18697-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18696-7

  • Online ISBN: 978-3-031-18697-4

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