Komba, Julius JMataka, MMalisa, JTWalubita, LFMaina, JW2018-10-012018-10-012018-07Komba, J.J. et al. 2018. Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania. Proceedings of the 5th GeoChina International Conference 2018: Civil Infrastructures Confronting Severe Weathers and Climate Changes: From Failure to Sustainability, 23-25 July 2018, HangZhou, China, pp. 39-51978-3-319-95645-9978-3-319-95644-2https://link.springer.com/chapter/10.1007/978-3-319-95645-9_5https://doi.org/10.1007/978-3-319-95645-9_5http://hdl.handle.net/10204/10424Copyright: 2018 Springer. Due to copyright restrictions, the attached PDF file contains the accepted version of the published paper. For access to the published item, please consult the publisher's website.Traffic loading is one of the key inputs for the structural design of pavements. For pavement design purposes, heavy vehicles are mostly used for the estimation of the traffic load spectra, as they cause the most structural damage to pavements. As part of the pavement design process, heavy vehicle volume and axle load surveys are typically carried out to assist with the accurate estimation of the cumulative traffic loading over a pavement design period. However, traffic volumes, axle loads and, ultimately, the cumulative traffic loading are often not uniform due to factors, such as varying motorist population and economic activities along the length of road. In this paper, a comparative assessment of traffic loading estimated during the rehabilitation design in 2005 and the actual measured site-specific traffic loading in 2015, as well as the projected future traffic loading were conducted for the Korogwe-Mombo road section along the T2 trunk road that connects Tanzania’s business hub of Dar es Salaam with the northern regional cities. The T2 trunk road is also used by heavy vehicles travelling to and from the neighbouring countries of Kenya and Uganda. This study found inter alia that the cumulative traffic loading based on the 2015 measured site-specific traffic data is approximately 2.8 times higher than the design traffic loading based on the 2005 traffic data, which illustrates the importance of using the latest, most accurate and reliable traffic data during rehabilitation design. To improve the accurate determination of traffic loading, traffic studies should ideally be conducted over a long period (typically over one year), but this is not practical and cost effective when traditional manual methods are used. Hence, road agencies should consider installing portable or permanent automated traffic and Weigh-In-Motion (WIM) monitoring systems.enPavementTrafficWeightAxleWeigh-In-MotionWIMTraffic loadingKorogwe-Mombo roadTanzaniaRoad rehabilitationTraffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in TanzaniaConference PresentationKomba, J. J., Mataka, M., Malisa, J., Walubita, L., & Maina, J. (2018). Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania. Springer. http://hdl.handle.net/10204/10424Komba, Julius J, M Mataka, JT Malisa, LF Walubita, and JW Maina. "Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania." (2018): http://hdl.handle.net/10204/10424Komba JJ, Mataka M, Malisa J, Walubita L, Maina J, Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania; Springer; 2018. http://hdl.handle.net/10204/10424 .TY - Conference Presentation AU - Komba, Julius J AU - Mataka, M AU - Malisa, JT AU - Walubita, LF AU - Maina, JW AB - Traffic loading is one of the key inputs for the structural design of pavements. For pavement design purposes, heavy vehicles are mostly used for the estimation of the traffic load spectra, as they cause the most structural damage to pavements. As part of the pavement design process, heavy vehicle volume and axle load surveys are typically carried out to assist with the accurate estimation of the cumulative traffic loading over a pavement design period. However, traffic volumes, axle loads and, ultimately, the cumulative traffic loading are often not uniform due to factors, such as varying motorist population and economic activities along the length of road. In this paper, a comparative assessment of traffic loading estimated during the rehabilitation design in 2005 and the actual measured site-specific traffic loading in 2015, as well as the projected future traffic loading were conducted for the Korogwe-Mombo road section along the T2 trunk road that connects Tanzania’s business hub of Dar es Salaam with the northern regional cities. The T2 trunk road is also used by heavy vehicles travelling to and from the neighbouring countries of Kenya and Uganda. This study found inter alia that the cumulative traffic loading based on the 2015 measured site-specific traffic data is approximately 2.8 times higher than the design traffic loading based on the 2005 traffic data, which illustrates the importance of using the latest, most accurate and reliable traffic data during rehabilitation design. To improve the accurate determination of traffic loading, traffic studies should ideally be conducted over a long period (typically over one year), but this is not practical and cost effective when traditional manual methods are used. Hence, road agencies should consider installing portable or permanent automated traffic and Weigh-In-Motion (WIM) monitoring systems. DA - 2018-07 DB - ResearchSpace DP - CSIR KW - Pavement KW - Traffic KW - Weight KW - Axle KW - Weigh-In-Motion KW - WIM KW - Traffic loading KW - Korogwe-Mombo road KW - Tanzania KW - Road rehabilitation LK - https://researchspace.csir.co.za PY - 2018 SM - 978-3-319-95645-9 SM - 978-3-319-95644-2 T1 - Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania TI - Traffic data characterization for road rehabilitation: A case study of the Korogwe-Mombo road section in Tanzania UR - http://hdl.handle.net/10204/10424 ER -