Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City

Hewan Nigussie Melissie

doi:doi:10.11648/j.ijtet.20261204.11

Case Report |

| Peer-Reviewed

Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City

Hewan Nigussie Melissie^*

Published in International Journal of Transportation Engineering and Technology (Volume 12, Issue 4)

Received: 24 July 2026 Accepted: 6 August 2026 Published: 28 October 2026

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.

Published in	International Journal of Transportation Engineering and Technology (Volume 12, Issue 4)
DOI	10.11648/j.ijtet.20261204.11
Page(s)	125-132
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Household Travel Survey, Home-based Trip Generation, Multiple Linear Regression, Multiple Classification Analysis, Travel Demand Forecasting, Transportation Planning

References

[1]	Gupta, B. D., Rana, M. S., & Ferdousi, J. A. Development of urban trip generation model based on residential area: A case study of Ward No. 09 under Khulna City Corporation, Bangladesh. International Journal of Development Research. 2017, 7(7), 13526-13530.
[2]	Panjaitan, A., Matondang, A. R., Sihombing, M., & Purwoko, A. Home based trip generation model's analysis in Medan, Binjai, Deli Serdang and Karo (Mebidangro) urban area, Indonesia. Journal of World Conference 2020, 2(1), 139-143. https://doi.org/10.33306/mjsc20/02
[3]	Gebre, G., & Quezon, E. T. Modeling public transport users’ trip production in Hawassa city, Ethiopia. Journal of Civil Engineering, Science and Technology. 2021, 12(2), 75-90. https://doi.org/10.33736/jcest.3972.2021
[4]	Nega, H. Developing trip generation model for suburb area of a city: Case of Kolfe Keranio Sub City, Addis Ababa [Master’s thesis, Addis Ababa University]. AAU Institutional Repository. 2021, https://etd.aau.edu.et/items/3829f360-65bb-4484-9864-0c3005b80c36
[5]	Solanke, M. O., & Raji, B. A. Intra-urban trip generation factors in developing world: A study of Ogun State, Nigeria. Transport and Communications. 2021, 9(1), 25-35. https://doi.org/10.26552/tac.C.2021.1.4
[6]	Masoumi, H. E. Household trip generation modeling in MENA megacities: A comparative study of Cairo, Istanbul, and Tehran. Journal of Urban Planning and Development. 2022, 148(3), 04022025. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000845
[7]	Lafta, S. A., Raheem, H. M., Hassooni, A. N., & Ali, Y. A. Development of trip production models using household surveys for urban travel demand forecasting. Engineering, Technology & Applied Science Research. 2025, 15(5), 26952-26958. https://doi.org/10.48084/etasr.11671
[8]	Mohammed, M., Boghandora, S., & Belkhair, A. Developing a trip generation model for South Tripoli using linear regression. Comprehensive Journal of Science. 2025, 10(38), 2275-2289. https://doi.org/10.65405/qwjk3151
[9]	Qawasmeh, B. Household travel demand forecasting using count regression models: Evidence from Michigan NHTS data. Transportation Letters: The International Journal of Transportation Research. 2025, 17(2), 145-158. https://doi.org/10.1080/19427867.2025.2301102
[10]	Srinarawat, M., Ito, Y., Fukuda, A., & Arimura, M. Estimation of trip generation from residential area in Bangkok. In Proceedings of the 3^rdATRANS Symposium Student Chapter Session. Asian Transportation Research Society.2010, (pp. 101-105).
[11]	Naseralavi, S., Mazaheri, M., & Hainen, A. Analyzing household trip generation across the United States: Spatial heterogeneity and predictive modeling using NHTS data. Transportation Research Record: Journal of the Transportation Research Board. 2025, https://doi.org/10.1177/03611981251280012
[12]	Stopher, P. R., & McDonald, M. Trip generation by cross-classification: An alternative methodology. Transportation Research Record. 1983, 944, 84-91.
[13]	McDonald, M., & Stopher, P. R. Some contrary indications for the use of household structure in trip-generation analysis. Transportation Research Record. 1983, 944, 92-100.
[14]	Gadepalli, R., Jahed, M., Ramachandra Rao, K., & Tiwari, G. Multiple classification analysis for trip production models using household data: Case study of Patna, India. Journal of Urban Planning and Development. 2014, 140(1), 05013001. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000168
[15]	Irshaid, M., & Abu-Eisheh, S. Application of Adaptive Neuro-Fuzzy Inference System in modeling home-based trip generation. Ain Shams Engineering Journal. 2023, 14(11), 102220. https://doi.org/10.1016/j.asej.2023.102220

Cite This Article

Plain Text BibTeX RIS

APA Style

Melissie, H. N. (2026). Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. International Journal of Transportation Engineering and Technology, 12(4), 125-132. https://doi.org/10.11648/j.ijtet.20261204.11

Copy | Download

ACS Style

Melissie, H. N. Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. Int. J. Transp. Eng. Technol. 2026, 12(4), 125-132. doi: 10.11648/j.ijtet.20261204.11

Copy | Download

AMA Style

Melissie HN. Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. Int J Transp Eng Technol. 2026;12(4):125-132. doi: 10.11648/j.ijtet.20261204.11

Copy | Download

@article{10.11648/j.ijtet.20261204.11,
  author = {Hewan Nigussie Melissie},
  title = {Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City},
  journal = {International Journal of Transportation Engineering and Technology},
  volume = {12},
  number = {4},
  pages = {125-132},
  doi = {10.11648/j.ijtet.20261204.11},
  url = {https://doi.org/10.11648/j.ijtet.20261204.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtet.20261204.11},
  abstract = {Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City
AU  - Hewan Nigussie Melissie
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ijtet.20261204.11
DO  - 10.11648/j.ijtet.20261204.11
T2  - International Journal of Transportation Engineering and Technology
JF  - International Journal of Transportation Engineering and Technology
JO  - International Journal of Transportation Engineering and Technology
SP  - 125
EP  - 132
PB  - Science Publishing Group
SN  - 2575-1751
UR  - https://doi.org/10.11648/j.ijtet.20261204.11
AB  - Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.
VL  - 12
IS  - 4
ER  -

Copy | Download

Author Information

Hewan Nigussie Melissie

Department of Civil Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia

Contact Email

http://orcid.org/0009-0006-3848-1948

Download PDF

Submit an Article

Sections

Plain Text BibTeX RIS

APA Style

Melissie, H. N. (2026). Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. International Journal of Transportation Engineering and Technology, 12(4), 125-132. https://doi.org/10.11648/j.ijtet.20261204.11

Copy | Download

ACS Style

Melissie, H. N. Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. Int. J. Transp. Eng. Technol. 2026, 12(4), 125-132. doi: 10.11648/j.ijtet.20261204.11

Copy | Download

AMA Style

Melissie HN. Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City. Int J Transp Eng Technol. 2026;12(4):125-132. doi: 10.11648/j.ijtet.20261204.11

Copy | Download

@article{10.11648/j.ijtet.20261204.11,
  author = {Hewan Nigussie Melissie},
  title = {Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City},
  journal = {International Journal of Transportation Engineering and Technology},
  volume = {12},
  number = {4},
  pages = {125-132},
  doi = {10.11648/j.ijtet.20261204.11},
  url = {https://doi.org/10.11648/j.ijtet.20261204.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtet.20261204.11},
  abstract = {Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City
AU  - Hewan Nigussie Melissie
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ijtet.20261204.11
DO  - 10.11648/j.ijtet.20261204.11
T2  - International Journal of Transportation Engineering and Technology
JF  - International Journal of Transportation Engineering and Technology
JO  - International Journal of Transportation Engineering and Technology
SP  - 125
EP  - 132
PB  - Science Publishing Group
SN  - 2575-1751
UR  - https://doi.org/10.11648/j.ijtet.20261204.11
AB  - Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.
VL  - 12
IS  - 4
ER  -

Copy | Download