<p>This study investigated the problem of joint optimization of roadside unit (RSU) deployment and connected vehicle routing for emergency information propagation. The problem is formulated as a mixed-integer nonlinear programming model. The aim of the model is to minimize the multi-hop emergency information propagation time. The multi-hop emergency information propagation time on each road segment is formulated as a function of the RSU deployment scheme and connected vehicle routing scheme. The connected vehicle routing is constrained by the capacity of the road segments. A piecewise linearization algorithm is proposed to convert the proposed model into a mixed-integer linear programming. In order to improve the solution efficiency, a method that combines Lagrangian relaxation algorithm and branch-and-bound algorithm is proposed to solve the linearized model. A numerical example shows that, compared with the method implementing only the piecewise linearization algorithm, the method combining the piecewise linearization algorithm, the Lagrangian relaxation algorithm, and the branch-and-bound algorithm improves the model solution efficiency by at least 15.7%. Compared with models that optimizing only the RSU deployment, the proposed model reduces multi-hop emergency information propagation time by at least 10.2%.</p>