An earthquake often has impact on a traffic network from two aspects. The first one is a wide damage of theexisting transportation network which would decrease traffic capacity dramatically and cause frequent traffic congestions, and the second one is a soaring demand of transportation to deliver a great deal of injured people to other undamaged areas in a short time and to import many emergent resources to the damaged areas. Accumulation of above impact would worsen transportation reliability and reduce transportation capability of the traffic network. In order to avoid those adversities, based on recognizing traffic network properties under emergency conditions after an earthquake, a framework of emergency service resource supply and supply problems of emergency service resources after earthquakes are considered in this paper. An Emergent Transportation Collaboration Network (ETCN) is presented, which consists of a collection center of emergent service resources, a transit center of emergent service resources and distribution center of emergent service resources. All emergent activities in ETCN are classified into three working stages, and a Collaboration Supply Efficiency (CSE) coefficient to describe their relationships is introduced. Based on ECTN and CSE coefficients, an Emergent Supply Collaboration Model (ESCM) is developed, whose objectives are to maximize coverage area of emergent service resources and to minimize disaster loss. In order to ensure supplying emergent service resources and avoiding traffic congestions, a collaboration optimization model of emergent traffic network after earthquake is further developed from ESCM considering constraints of average transportation speed of emergency vehicles, road saturation, occupation ratio and queue length. Then, it is discussed that the changing principle of occupation ratio and queue length by variation of transportation speed of vehicles under emergencies. In the end, a case study is applied to testify a collaboration optimizationto ensure supplying emergent service resources. A numerical example demonstrates the proposed model is effective and the improved algorithmis efficient.This paper would be a theoretical base and potential practice solution for emergency traffic control and management.