Conference Paper2017Cited by 14

Understanding Dhaka City Traffic Intensity and Traffic Expansion Using Gravity Model

Md Abu Sayed, Md Maksudur Rahman, Moinul Islam Zaber, Amin Ahsan Ali

20th International Conference On Computer and Information Technology (ICCIT 2017)

IEEE, pp. 1-6

  • Industry, Innovation and Infrastructure — Relevance: 64%
  • Sustainable Cities and Communities — Relevance: 92%
DOI: 10.1109/iccitechn.2017.8281770Open AccessURL

Abstract

Analysis of traffic pattern recognition and traffic congestion expansion in real time are one of the exciting and challenging tasks which help the government to build a robust and sustainable traffic management system specially in a densely populated city like Dhaka. In this paper, we analyze the traffic intensity for small areas which are also known as junction points or corridors. We describe Dhaka city traffic expansion from a congestion point by using gravity model. However, we process real-time traffic data of Dhaka city rather than depend on survey and interview. We exactly show that traffic expansion of Dhaka city exactly follows gravity model. Expansion of traffic from a congestion point spreads out rapidly to its neighbor and impact of congested point decreases as the distance increases from that congested point. This analysis will help the government making a planned urbanized Dhaka city in order to reduce traffic jam.

Keywords

  • gravity model
  • Traffic congestion
  • Traffic intensity
  • real-time traffic information
  • urban traffic management
  • Dhaka
  • transport corridors
  • traffic pattern recognition

CCDS Authors

Moinul I Zaber, PhD
Moinul I Zaber, PhD

Moinul I Zaber, PhD

  • Director, HCI Wing
  • Supervisor, DS Wing

Professor

+2 more affiliations

Department of Computer Science & Engineering

Dhaka University

Published at

ICPR, HCII, JMIR

Research Interests

Computational Social Science, Human-Computer Interaction, Telecommunication Policy

Amin Ahsan Ali, PhD
Amin Ahsan Ali, PhD

Amin Ahsan Ali, PhD

  • Director, AI/ML Wing

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Research Interests

Artificial Intelligence, Machine Learning

References

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Cited By

  1. 1.Shubing Shan, Buyang Cao, Zhiqiang Wu. (2019). Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model. IEEE Access, 7, 88093–88106[10.1109/access.2019.2925740]
  2. 2.Md Abu Sayed, Ahmed H. Anwar, Christopher Kiekintveld, Charles Kamhoua. (2023). Honeypot Allocation for Cyber Deception in Dynamic Tactical Networks: A Game Theoretic Approach. Lecture notes in computer science, 195–214[10.1007/978-3-031-50670-3_10]
  3. 3.Mohammed Ziaul Haider, Rabeya Sultana Papri. (2021). Cost of traffic congestion in Dhaka Metropolitan City. Public Transport, 13(2), 287–299[10.1007/s12469-021-00270-4]
  4. 4.Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji. (2022). Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder. 2022 IEEE International Conference on Big Data (Big Data), 2327–2332[10.1109/bigdata55660.2022.10021066]
  5. 5.Md Maksudur Rahman, S M Ariful Hoque, Moinul Islam Zaber. (2018). Understanding Real Time Traffic Characteristics of Urban Zones Using GPS Data: A Computational Study on Dhaka City. , 514–519[10.1109/iciev.2018.8640961]
  6. 6.Shahriar Iqbal Raj, A.S.M Julker Naem. (2022). Socioeconomic impact of the first Mass Rapid Transit (MRT) in Dhaka. [10.5821/siiu.11977]
  7. 7.Md Abu Sayed, Ahmed Hemida, Christopher Kiekintveld, Charles Kamhoua. (2024). Strategic Honeypot Allocation in Dynamic Networks: A Game-Theoretic Approach for Enhanced Cybersecurity. Research Square[10.21203/rs.3.rs-3960163/v1]
  8. 8.Moinul Zaber, Amin Ali, Md Abu Sayed, Farhad Bhuiyan, Samiul Islam, Nibras Rakib. (2018). Scrutiny of Electricity Billing and Supply Data as a Probable Proxy for Economic Activities: A Comprehensive Analysis of Power Consumption of Dhaka, Bangladesh. SSRN Electronic Journal[10.2139/ssrn.3142594]
  9. 9.Md. Mushfiqur Rahman, Nahian Muhtasim Zahin, Kazi Raiyan Mahmud, Md. Azmaeen Bin Ansar. (2020). Automated Intersection Management with MiniZinc. , 50, 1–6[10.1109/sti50764.2020.9350408]
  10. 10.Durhan Saliev, Georgi Mladenov, Plamen Petkov. (2025). Research and Analysis of Traffic Intensity on a Street with High Traffic Load: Case Study of the City of Sofia. , 37[10.3390/engproc2025100037]
  11. 11.Naoto Minakawa, Kiyoshi Izumi, Yuri Murayama, Hiroki Sakaji. (2024). Firm Default Prediction by GNN with Gravity-Model Informed Neighbor Node Sampling. The Review of Socionetwork Strategies, 18(2), 303–328[10.1007/s12626-024-00170-6]
  12. 12.Nahida Shaulin, Azmaine Faeique. (2023). Role of Traffic Police in Managing Traffic in Dhaka City: Challenges and The Ways Forward. Indonesian Journal of Social Research (IJSR), 5(2), 132–141[10.30997/ijsr.v5i2.322]
  13. 13.Shubing Shan, Buyang Cao, Zhiqiang Wu. (2019). The Predictor for Urban Buildings’ Hourly Electricity Consumption. IOP Conference Series Earth and Environmental Science, 322(1), 012007[10.1088/1755-1315/322/1/012007]
  14. 14.Sourav Saha, Abu Bakar Mohammad Abdullah, Monosij Kanti Sarker, Sabrina Islam, Mohammad Rejwan Uddin, Mahady Hasan. (2025). IoT-based Smart Traffic Management System Using Tripwire Laser. , 1–6[10.1109/sti69347.2025.11367570]
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