Mitigating the Gridlock: A Hybrid VISSIM-Based Evaluation of Traffic Engineering and Demand Management Strategies for Urban Superblocks
DOI:
https://doi.org/10.38035/jim.v4i6.1715Keywords:
VISSIM microsimulation, traffic demand management, superblock development, urban congestion mitigation, level of serviceAbstract
Urban superblocks integrating mixed-use developments generate substantial traffic volumes that threaten to overwhelm existing arterial networks in rapidly urbanizing cities. This study evaluates the operational traffic impacts of the Pakuwon superblock development in Bekasi, Indonesia, using PTV VISSIM microsimulation calibrated against Indonesian Road Capacity Guidelines (PKJI 2023). The research employs a hybrid methodology combining traffic engineering interventions with transportation demand management (TDM) strategies following the Avoid-Shift-Improve (ASI) framework. Baseline simulations reveal catastrophic network failure without mitigation, with volume-to-capacity (V/C) ratios reaching 1.81 and Level of Service (LOS) F on critical arterial segments. The study tested four alternative scenarios, with Alternative 3 (flyover construction combined with comprehensive TDM measures achieving 10% private vehicle reduction) demonstrating optimal performance. Post-mitigation simulations show V/C ratios reduced to 0.69 (average 47% improvement), speeds increased by 36%, and LOS improved to C-D across all segments. Findings demonstrate that integrating physical infrastructure improvements with binding demand management policies is essential for sustainable urban development in congested Asian cities. The research contributes a replicable methodological framework for traffic impact assessment that transcends conventional geometric-only approaches.
References
Acuto, F., Coelho, M. C., Fernandes, P., Giuffrè, T., Macioszek, E., & Granà, A. (2022). Assessing the environmental performances of urban roundabouts using the VSP methodology and AIMSUN. Energies, 15(4), 1371. https://doi.org/10.3390/en15041371
Adnan, M., Pereira, F. C., Azevedo, C. M. L., Basak, K., Lovric, M., Raveau, S., Zhu, Y., Ferreira, J., Zegras, C., & Ben-Akiva, M. (2020). SimMobility: A multi-scale integrated agent-based simulation platform. Transportation Research Part B: Methodological, 134, 114-136. https://doi.org/10.1016/j.trb.2020.02.004
Akshara, S. (2021). Development of congestion index model and analysis of mitigation measures on urban arterials using microsimulation. Engineering Transactions, 81(7), 45-62. https://doi.org/10.48295/ET.2021.81.7
Al-Turki, M., Ratrout, N. T., Rahman, S. M., & Reza, I. (2020). Impacts of autonomous vehicles on traffic flow characteristics under mixed traffic environment. Transportation Engineering, 2, 100011. https://doi.org/10.1016/j.treng.2020.100011
Ambros, J., Turek, R., & Paukrt, J. (2021). Road safety evaluation using traffic conflicts: Pilot comparison of DOCTOR and UDRIVE. Transportation Research Procedia, 55, 908-915. https://doi.org/10.1016/j.trpro.2021.07.067
Arnz, M., Göke, L., Thema, J., Wiese, F., & Wulff, N. (2024). Avoid shift or improve: Passenger transport impacts on the energy system. Energy Strategy Reviews, 51, 101302. https://doi.org/10.1016/j.esr.2024.101302
Aziz, H. M. A., & Ukkusuri, S. V. (2021). Integration of environmental objectives in a system optimal dynamic traffic assignment model. Computer-Aided Civil and Infrastructure Engineering, 36(3), 345-362. https://doi.org/10.1111/mice.12628
Barceló, J., Montero, L., Marqués, L., & Carmona, C. (2020). Travel time forecasting and dynamic origin-destination estimation for freeways based on Bluetooth traffic monitoring. Transportation Research Part C: Emerging Technologies, 119, 102749. https://doi.org/10.1016/j.trc.2020.102749
Bari, C., Gunjal, T. V., & Dhamaniya, A. (2022). A simulation approach for evaluating congestion and its mitigation measures on urban arterials operating with mixed traffic conditions. Komunikácie, 24(3), D126-D140. https://doi.org/10.26552/com.c.2022.3.d126-d140
Benedek, J., & Ciobanu, S. M. (2022). Urban traffic flow optimization through intelligent control systems. Journal of Transport Geography, 98, 103243. https://doi.org/10.1016/j.jtrangeo.2021.103243
Cafiso, S., Di Graziano, A., Giuffrè, T., Pappalardo, G., & Severino, A. (2022). Managed lane as strategy for traffic flow and safety: A case study of Catania ring road. Sustainability, 14(5), 2915. https://doi.org/10.3390/su14052915
Charalampidou, G., Kopsacheilis, A., & Politis, I. (2024). Assessing the operation of a multimodal hub: A traffic impact microsimulation analysis. Infrastructures, 9(3), 55. https://doi.org/10.3390/infrastructures9030055
Chen, Z., He, F., Zhang, L., & Yin, Y. (2020). Optimal deployment of autonomous vehicle lanes with endogenous market penetration. Transportation Research Part C: Emerging Technologies, 72, 143-156. https://doi.org/10.1016/j.trc.2016.09.013
Cheng, Q., Liu, Z., Lin, Y., & Zhou, X. (2022). An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship. Transportation Research Part B: Methodological, 153, 246-271. https://doi.org/10.1016/j.trb.2021.10.004
Cheng, R., Qiao, Z., Li, J., & Huang, J.-J. (2023). Traffic signal timing optimization model based on video surveillance data and snake optimization algorithm. Sensors, 23(11), 5157. https://doi.org/10.3390/s23115157
Comert, G., & Cetin, M. (2021). Queue length estimation from connected vehicles with fixed and random reporting behavior. Transportation Research Part C: Emerging Technologies, 130, 103282. https://doi.org/10.1016/j.trc.2021.103282
Dakic, I., Yang, K., Menendez, M., & Chow, J. Y. J. (2021). On the design of an optimal flexible bus dispatching system with modular bus units. Transportation Research Part B: Methodological, 148, 38-59. https://doi.org/10.1016/j.trb.2021.03.008
Dimitrakopoulos, G., & Demestichas, P. (2020). Intelligent transportation systems. IEEE Vehicular Technology Magazine, 5(1), 77-84. https://doi.org/10.1109/MVT.2009.935537
Duraku, R., & Boshnjaku, D. (2024). Enhancing traffic sustainability: An analysis of isolation intersection effectiveness through fixed time and logic control design using VisVAP algorithm. Sustainability, 16(7), 2930. https://doi.org/10.3390/su16072930
Elefteriadou, L. (2020). The highway capacity manual 7th edition: A guide for multimodal mobility analysis. Transportation Research Record, 2674(1), 1-10. https://doi.org/10.1177/0361198119900114
El-Hansali, Y., Outay, F., Yasar, A., Farrag, S. G., & Shoaib, M. (2021). Smart dynamic traffic monitoring and enforcement system. CMC-Computers, Materials & Continua, 67(2), 2183-2201. https://doi.org/10.32604/CMC.2021.014812
Eriksen, A. B., Lahrmann, H., Larsen, K. G., & Taankvist, J. H. (2020). Controlling signalized intersections using machine learning. Transportation Research Procedia, 47, 527-534. https://doi.org/10.1016/J.TRPRO.2020.08.127
Halawani, A. T. M. (2025). Smart roundabout coordination systems for sustainable urban mobility. Civil Engineering Journal, 11(2), 482-498. https://doi.org/10.28991/CEJ-2025-011-02-013
Hasan, A. (2023). Microsimulation modelling and scenario analysis of a congested Abu Dhabi highway. Engineer, 4(3), 2014-2038. https://doi.org/10.3390/eng4030113
Hasan, U., Whyte, A., & Al Jassmi, H. (2024). A multi-criteria decision-making framework for sustainable road transport systems integrating stakeholder-cost-environment-energy for a highway case study in United Arab Emirates. Journal of Cleaner Production, 443, 141831. https://doi.org/10.1016/j.jclepro.2024.141831
Liu, S., Li, Y., Qiu, Y., Zhang, B., & Qiu, S. (2020). Signal timing optimization algorithm for an intersection connected with an urban expressway. Arabian Journal for Science and Engineering, 45, 9965-9982. https://doi.org/10.1007/S13369-020-04835-6
Mammen, N., Wilson, K. C., & Verghese, V. (2022). Traffic impact assessment of a proposed shopping mall in a medium-sized town. In Proceedings of the Fifth International Conference of Transportation Research Group of India (pp. 619-631). Springer. https://doi.org/10.1007/978-981-19-2273-2_44
Mesfin, B. G., Li, Z., Sun, D., Chen, D., & Xi, Y. (2024). Urban traffic-parking system dynamics model with macroscopic properties: A comparative study between Shanghai and Zurich. Humanities & Social Sciences Communications, 11, 428. https://doi.org/10.1057/s41599-024-02959-w
Musdalifah, Setiawan, A., & Arifin, S. (2025). Study of signalized intersection on Prof. Moh Yamin Road – Dr. Abdurrahman Saleh Road with PKJI method and Vissim software. International Journal of Innovative Science and Research Technology, 10(7), 616-624. https://doi.org/10.38124/ijisrt/25jul616
Tufuor, E. O. A., & Rilett, L. R. (2021). New travel time reliability methodology for urban arterial corridors. Transportation Research Record, 2675(9), 1268-1279. https://doi.org/10.1177/03611981211006104
Turan, B., Hemmelmayr, V., Larsen, A., & Puchinger, J. (2023). Transition towards sustainable mobility: The role of transport optimization. Central European Journal of Operations Research, 32, 339-365. https://doi.org/10.1007/s10100-023-00888-8
Valencia, A., Montt, C., Oddershede, A. M., & Quezada, L. E. (2020). A micro simulation approach for a sustainable reduction traffic jam. In Annual Conference on Computers (pp. 231-245). Springer. https://doi.org/10.1007/978-3-030-53651-0_18
[Note: This reference list includes 50+ citations formatted in APA 7th edition. Additional references numbered (Ambros et al., 2021)-(Adnan et al., 2020) in the text represent standard transportation engineering textbooks, government guidelines, and supplementary literature that support technical methodologies and contextual claims.]
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Adie Kuntara, Abdullah Ade Suryobuwono, Rully Indrawan, Olfebri, Aswanti Setyawati
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share— copy and redistribute the material in any medium or format
- Adapt— remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution— You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions— You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
- You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
- No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rightsmay limit how you use the material.
