Charles R.S. Hatfield , Anna Kustar , Marcel Reinmuth , Constant Cap , Agraw Ali Beshir , Jacqueline M. Klopp , Alexander Zipf , James Rising , Thet Hein Tun
{"title":"Lessons in traffic: Nairobi's school term congestion and equity challenges","authors":"Charles R.S. Hatfield , Anna Kustar , Marcel Reinmuth , Constant Cap , Agraw Ali Beshir , Jacqueline M. Klopp , Alexander Zipf , James Rising , Thet Hein Tun","doi":"10.1016/j.aftran.2025.100044","DOIUrl":null,"url":null,"abstract":"<div><div>The specific needs of children – and the impacts of road design, traffic, and congestion on them – tend to be poorly addressed in transport planning, including in cities like Nairobi. While a growing body of research on the geography of education in African cities has delved into aspects of school travel, equity, and their effects on learning, the influence of school sessions, which induces unique trip dynamics, remains largely unexplored. This paper aims to address this gap through a data-driven analysis of traffic effects when schools are in session, compared to holidays in Nairobi. We leverage real-time road speed information from the publicly available Uber Movement data for 2019 to model congestion spatially and temporally. We achieve this by modeling travel times to the central business district (CBD) from across the city for both school term and holiday periods, as well as by measuring changes in mean daily and hourly road speeds across different road types between the two periods. Through this analysis, we found that mean road speeds across the city were statistically significantly lower during the school term than during the holiday period with secondary roads overrepresented among the most congested roads in the city. There was also high positive spatial autocorrelation for changes in travel times to the CBD across the city with some clusters experiencing significant increases in travel times while others experienced significant decreases. The high degree of clustering, decreased road speeds, and overburdening of specific road types suggests potential equity and economic impacts of congestion, which may be closely connected to inadequate land use and planning regarding children's education and school travel. Overall, this suggests that better planning for schools could help reduce congestion, while improving child health and well-being.</div></div>","PeriodicalId":100058,"journal":{"name":"African Transport Studies","volume":"3 ","pages":"Article 100044"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"African Transport Studies","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950196225000225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The specific needs of children – and the impacts of road design, traffic, and congestion on them – tend to be poorly addressed in transport planning, including in cities like Nairobi. While a growing body of research on the geography of education in African cities has delved into aspects of school travel, equity, and their effects on learning, the influence of school sessions, which induces unique trip dynamics, remains largely unexplored. This paper aims to address this gap through a data-driven analysis of traffic effects when schools are in session, compared to holidays in Nairobi. We leverage real-time road speed information from the publicly available Uber Movement data for 2019 to model congestion spatially and temporally. We achieve this by modeling travel times to the central business district (CBD) from across the city for both school term and holiday periods, as well as by measuring changes in mean daily and hourly road speeds across different road types between the two periods. Through this analysis, we found that mean road speeds across the city were statistically significantly lower during the school term than during the holiday period with secondary roads overrepresented among the most congested roads in the city. There was also high positive spatial autocorrelation for changes in travel times to the CBD across the city with some clusters experiencing significant increases in travel times while others experienced significant decreases. The high degree of clustering, decreased road speeds, and overburdening of specific road types suggests potential equity and economic impacts of congestion, which may be closely connected to inadequate land use and planning regarding children's education and school travel. Overall, this suggests that better planning for schools could help reduce congestion, while improving child health and well-being.