Introduction:　Urban　expressway　interchanges　have　become　accident-prone　sites　owing　to　the　accelerated　increase　in　motor-vehicle　ownership.　This　study　explored　the　impact　of　factors,　including　day　of　the　week,　time　of　day,　congestion　level,　traffic　control　devices,　and　road　conditions,　on　road　safety　risk　levels　in　the　interchange　area　of　an　urban　expressway　based　on　aggregate　driving　behavior　data.　Method:　A　large　amount　of　aggregate　driving　behavior　data　were　obtained　from　AutoNavi　navigation　software.　The　database　was　built　by　matching　various　types　of　data　and　observing　their　characteristics.　Day　of　the　week,　time　of　day,　congestion　level,　road　conditions　(number　of　lanes,　traffic　disturbance,　and　traffic　control　devices　[the　type　of　advance　guide　sign　system,　number　of　warning　signs,　and　the　complexity　of　the　diagrammatic　guide　sign])　were　identified　as　the　explanatory　variables.　The　traffic　order　index　(TOI),　based　on　driving　behavior　and　speed　variation,　was　used　to　evaluate　the　road　safety　risk　levels,　including　risky　roads,　general　roads,　and　safe　roads,　which　served　as　the　response　variables.　The　multinomial　logit　model　(MNL)　was　developed　to　explore　the　impact　of　various　factors,　including　traffic　control　devices　and　road　conditions,　on　road　safety　risk　levels.　Results:　The　results　showed　that　the　factors　that　significantly　influence　risky　roads　include　day　of　the　week,　number　of　lanes,　congestion　level　(slow　moving),　traffic　disturbance　(with　the　merge　or　diverge　within　500　m),　type　of　advance　guide　sign　system　(three-level　advance　guide　sign　system),　and　complexity　of　diagrammatic　guide　signs　(low　or　medium　complexity).　Practical　Applications:　This　study　could　offer　plausible　suggestions　for　traffic　management　departments　for　the　rehabilitation　of　road　conditions　and　traffic　control　devices　in　urban　expressway　interchange　areas.　(c)　2021　National　Safety　Council　and　Elsevier　Ltd.　All　rights　reserved.