Optimizing city transportation for smarter cities can have a major impact on the quality of life in urban areas in terms of economic merits and low environmental load. In many cities of the world, transport authorities are facing common challenges such as worsening congestion, insufficient transport infrastructure, increasing carbon emissions, and growing customer needs. To tackle these challenges, it is highly necessary to have fine-grained and large-scale agent simulation for designing smarter cities. In this paper we propose a large-scale traffic simulation platform built on top of X10, a new distributed and parallel programming language. Experimental results demonstrate linear scalable performance in simulating large-scale traffic flows of the national Japanese road network and a hundred of cities of the world using thousands of CPU cores. Copyright © 2012 ACM.