Central areas of large cities offer in general many advantages to their inhabitants. Typically, a large number of products, services, and opportunities are available in those urban zones, thus increasing life quality. Unfortunately, these benefits are associated with increasing transportation activities that can cause serious problems, such as traffic congestion, excessive energy consumption, and pollution. This paper aims at presenting a new transport system that consists of transporting freight in long-haul passenger vehicles. Two mixed integer mathematical programming models are presented: one for total cost minimization and the other for the travel time minimization. The problem under study was considered as a multi-commodity network flow problem with time windows, multi transport-lines, and multiple vehicles. Three heuristics based on mixed integer programming (MIP) were designed to solve it: size reduction, LP-and-fix, and a combination of these two procedures. The proposed approaches were validated in a case study designed around the intercity passenger transport system, in Ceará, Northeast of Brazil. Several operational scenarios were evaluated, taking into account the available freight capacities. The developed MIP heuristics produced high-quality solutions, in reasonable computational times, with the LP-and-Fix algorithm outperforming the other approaches.