Recently,　an　open-source　light-weight　dynamic　traffic　assignment　(DTA)　package,　namely　DTALite,　has　been　developed　to　allow　a　rapid　utilization　of　advanced　dynamic　traffic　analysis　capabilities.　Aiming　to　bridge　the　modeling　gaps　between　multi-agent　simulation　and　optimization　in　a　multimodal　environment,　we　further　design　and　develop　DTALite-S　to　simplify　the　traffic　flow　dynamic　representation　details　in　DTALite　for　future　extensions.　We　hope　to　offer　a　unified　modeling　framework　with　inherently　consistent　space–time　network　representations　for　both　optimization　formulation　and　simulation　process.　This　paper　includes　three　major　modeling　components:　(1)　mathematic　formulations　to　describe　traffic　and　public　transportation　simulation　problem　on　a　space–time　network;　(2)　transportation　transition　dynamics　involving　multiple　agents　in　the　optimization　process;　(3)　an　alternating　direction　method　of　multipliers (ADMM)-based　modeling　structure　to　link　different　features　between　multi-agent　simulation　and　optimization　used　in　transportation.　This　unified　framework　can　be　embedded　in　a　Lagrangian　relaxation　method　and　a　time-oriented　sequential　simulation　procedure　to　handle　many　general　applications. We　carried　out　a　case　study　by　using　this　unified　framework　to　simulate　the　passenger　traveling　process　in Beijing　subway　network　which　contains　18　urban　rail　transit　lines,　343　stations,　and　52　transfer　stations. Via　the ADMM-based　solution　approach,　queue　lengths　at　platforms,　in-vehicle　congestion　levels　and　absolute　deviation　of　travel　times　are　obtained　within　1560　seconds.The　case　study indicate　that　the　open-source　DTALite-S　integrates　simulation　and　optimization　procedure　for　complex　dynamic　transportation　systems　and　can　efficiently　generate　comprehensive　space-time　traveling　status.　©　2019,　The　Author(s).