Modelling, simulation, and forecasting offer a means of facilitating better planning and decision-making. These quantitative approaches can add value beyond traditional methods that do not rely on data and are particularly relevant for public transportation. Lagos is experiencing rapid urbanization and currently has a population of just under 15 million. Both long waiting times and uncertain travel times has driven many people to acquire their own vehicle or use alternative modes of transport. This has significantly increased the number of vehicles on the roads leading to even more traffic and greater traffic congestion. This paper investigates urban travel demand in Lagos and explores passenger dynamics in time and space. Using individual commuter trip data from tickets purchased from the Lagos State Bus Rapid Transit (BRT), the demand patterns through the hours of the day, days of the week and bus stations are analysed. This study aims to quantify demand from actual passenger trips and estimate the impact that dynamic scheduling could have on passenger waiting times. Station segmentation is provided to cluster stations by their demand characteristics in order to tailor specific bus schedules. Intra-day public transportation demand in Lagos BRT is analysed and predictions are compared. Simulations using fixed and dynamic bus scheduling demonstrate that the average waiting time could be reduced by as much as 80%. The load curves, insights and the approach developed will be useful for informing policymaking in Lagos and similar African cities facing the challenges of rapid urbanization.

翻译：模拟、模拟和预测提供了一种促进更好规划和决策的手段。这些定量方法除了传统方法之外,还可以增加价值,而传统方法并不依赖数据,而且与公共交通特别相关。拉各斯正在经历快速城市化,目前人口不到1 500万。漫长的等待时间和不确定的旅行时间促使许多人获得自己的车辆或使用其他运输方式。这大大增加了公路上车辆的数量,导致交通量增加和交通堵塞现象增多。本文调查了拉各斯的城市旅行需求,并探讨了乘客在时间和空间方面的动态动态。利用从拉各斯州快速交通车(BRT)购买的机票的个别通勤者出行数据,对每天、每周和公共汽车站的需求模式进行了分析。这项研究旨在量化实际客运的需求,并估计动态的日程安排可能对乘客候车时间产生的影响。根据需求特点向集群站提供站分路段,以调整具体的公共汽车时间表。对拉各斯边境站的日常公共交通需求进行了分析,并比较了乘客在时间和空间方面的动态交通动态动态动态。使用固定和动态的客运日程安排表明,平均等候时间在一天、星期和客车站站车站的时段将大大缩短,从而显示非洲在快速决策方面所面临的比率。