Bus routing is one of the most important elements of public transit system planning. The bus route is optimized by minimizing the total system cost, including operator and user costs, while considering diagonal links in the study network.

Commuter bus routes are generally located on main thoroughfares of urban areas. However, considering realistic distributions of passenger travel demand over space and time, many route locations may not be cost-effective from either the operator or user standpoint. Therefore, relocating bus routes and redesigning headways may reduce operating costs as well as improve passenger accessibility. Both transit operators and passengers prefer short and fast routes to reduce the operating cost and travel time, respectively. However, passengers also prefer bus routes that can be easily accessed from their origins and destinations. To reduce access impedance, tortuous routes are often constructed. This, in turn, is likely to increase both the in-vehicle portion of user travel time as well as the bus operating cost. Transit operators are well aware of this trade-off when planning a new bus route or extending an existing service


In the past 30 years, many researchers have analyzed the problems of optimal transit service design with many-to-one travel patterns by using analytical methods (Byrne and Vuchic 1971; Chang and Schonfeld 1991; Hurdle 1973; Spasovic and Schonfeld 1993; Spasovic et al.1994; Wirasinghe et al. 1977). They dealt with selecting zones, route/line spacings, headways, and route lengths designed to carry people between distributed origins and a single destination (e.g., central business district [CBD], transfer station, etc.). By assuming demand homogeneity of the service area, the researchers optimized the characteristics of bus systems consisting of a set of parallel routes feeding a major transfer station of a trunk line or a single terminal point, such as the CBD ( Source:

A recent method for analyzing fixed-route bus systems is the out-of-direction (OOD) technique (Welch et al. 1991). This method improves the accessibility of a bus system by improving passenger accessibility along certain route segments. Chien and Schonfeld (1997) optimize a grid transit system in an urban area without oversimplifying the spatial and demand characteristics. They extended the model to jointly optimize the characteristics of a rail transit route and the associated feeder bus routes in an urban corridor (Chien and Schonfeld 1998)

The impact of the change in headway on user, operator, and total costs is also analyzed (Figure 2). Short headway resulting in high operator costs (due to large fleet size required) reduces user costs because of less waiting time. The optimal headway is reached in point B (14.2-minute headway), at which the minimum total cost is achieved, while the operator and user costs are $159/hour and $327/hour, respectively

Figure 2



Figure 3 shows the relationship between demand and optimal headway. For various bus sizes, the optimal headway decreases as the demand increases. Analysis results show that regardless of the variation in demand or in the value of passenger time, the 35-passenger-per-bus vehicle size is the most preferable as it yields the minimum total cost. Figure 4 shows that even change of headway does not change the optimality of using smaller buses to serve the analyzed region. In addition, Figure 8 shows that the increase in value of passenger time results in an increase in user cost. Thus, the optimal headway decreases.

Figure 3
Figure 4

The model can be easily modified to account for changes of spatial (e.g., one-way street, roadway/lane closure, reversible lane) and temporal (e.g., incidents, special events) conditions. All these features enhance transit planners’ capability to redesign bus routes in areas that may experience significant shifts in residential density, as well as geographic or physical changes of the street network.