This　paper　presents　the　optimal　dynamic　investment　allocation　on　intelligent　transportation　infrastructure　construction　and　road　maintenance　with　considering　environmental　costs.　We　propose　a　stochastic　optimal　control　problem　with　uncertain　traffic　volume,　aiming　to　minimize　the　expected　system　total　cost,　which　consists　of　the　fixed　travel　cost,　the　congestion　delay　cost,　the　congestion　environmental　cost　and　the　road　maintenance　environmental　cost.　By　adopting　Hamilton-Jacobi-Bellman　equation,　we　propose　the　optimal　dynamic　strategy　for　investment　allocation,　which　is　a　feedback　control　and　determined　by　two　observable　variables,　i.e.,　traffic　volume　and　road　network　capacity.　We　also　conduct　a　case　study　of　Beijing,　China,　for　the　proposed　dynamic　strategy.　The　numerical　results　demonstrate　that　our　strategy　can　lower　the　congestion　delay　and　related　environmental　cost　significantly,　which　is　enough　to　remedy　the　possible　increase　in　the　road　maintenance　environmental　cost.　Comparing　with　traditional　strategies,　the　new　dynamic　strategy　provides　closely　100%　of　the　benefit　cases.　©　2020　Elsevier　Ltd