A digital twin is a virtual representation of a physical entity, serving as a pivotal convergence technology that facilitates the diagnosis, optimization, prediction, and problem-solving of the corresponding physical entity. It is widely applicable across diverse sectors, including automobiles, manufacturing, logistics, and smart cities. The automotive industry, in particular, is actively integrating digital twin throughout the entire product lifecycle from research and development, production, sales, and services to enhance the overall customer experience. This paper presents insights into software practices and experiences related to the implementation of smart mobility digital twin. Drawing from lessons learned in digital twin projects, we outline guidelines for effective application. It is expected to gradually improve transportation convenience and utility value for customers through a comprehensive analysis that integrates the digital twin of the vehicle with those of the surrounding environment, including traffic patterns and human behavior, in conjunction with spatio-temporal information.