Abstract: Objective Controlling the biased wear of running tires is a critical technical challenge for SMT（straddle-type monorail transit） vehicles. It is necessary to study the control of biased tire wear when a SMT vehicle passes through curved segments of the running surface. Method Taking the arc height of the track beam running surface as the optimization variable, and using the total friction work of the running tires and the deviation of the friction work as dual optimization objectives, an optimization model for the running surface of SMT vehicles is established. Based on the dynamics model of SMT vehicles, a functional relationship is developed between the running surface optimization variables and the boundary parameters of the running tire operating conditions. A multidisciplinary co-simulation optimization approach using the particle swarm optimization algorithm is employed to obtain the Pareto optimal solutions for the arc height of the track beam running surface. Result ＆ Conclusion When the optimal arc height of the concave inner running surface is 23.50 mm, the total friction work of the running tires decreases by 5.09%. When the optimal arc height of the convex outer running surface is 12.21 mm, the total friction work of running tires decreases by 4.85%, and the friction work deviation value decreases by 26.74%, and the overall friction work deviation value decreases by 10.69%. By optimizing the running surface arc height of the rail beam and reasonably designing the running surface profile, the biased wear of running tires can be mitigated to some extent, thereby achieving the goal of reducing running tire wear.