Simulation Outputs UC Madrid

The dataset includes traffic simulation outputs that compare baseline scenarios with those incorporating traffic management interventions under varying penetration rates of connected vehicles (CVs). Specifically, two scenarios are analyzed: one involving planned roadworks in Madrid, and another addressing unplanned incidents. For each scenario, traffic-related Key Performance Indicators (KPIs) are reported across both the baseline and intervention experiments, with CV penetration rates varied. For each experiment five resplications were simulated using different random seeds to ensure robustness and account for stochastic variability. The simulations are based on a calibrated transport model for the city of Madrid, developed using traffic data from 2019. Due to data-sharing restrictions, the transport model itself cannot be made publicly available.本数据集涵盖交通仿真输出结果，用于对比基线场景与不同联网车辆（connected vehicles, CVs）渗透率下引入交通管理干预措施的各类场景。具体而言，本次分析包含两类场景：其一为马德里市的计划性道路施工场景，其二为突发性事故处置场景。针对每一类场景，均报告了基线实验与干预实验中与交通相关的关键绩效指标（Key Performance Indicators, KPIs），且联网车辆渗透率设置存在差异。针对每一项实验，均采用不同随机种子开展五次重复仿真，以保障结果的稳健性并覆盖随机波动性带来的影响。本次仿真基于经过校准的马德里市交通模型，该模型依托2019年的交通数据构建而成。受数据共享限制，该交通模型本身无法对外公开。