The location and number of bus stops are key to the operational efficiency of the services that use them; these criteria affect commercial speed, reliability, and passenger access times. In the defining of the number of stops, a trade-off arises between reduced access time, which widens a route's coverage area, and both the operational speed of the route and the users’ in-vehicle travel time. In this study, a model for optimally locating stops was developed, and the model was applied to the Grecia Avenue public transport corridor in the city of Santiago, Chile. The proposed model uses a continuous and multiperiod approximation of corridor demand; this approximation allows for the determination of the density of stops, which minimizes the sum of operator costs and total costs to passengers. The model simultaneously solves for the optimal stop density and the headway between successive buses. The actual stop locations of the Grecia Avenue corridor were compared with the optimal locations suggested by the model, and many similarities were found.

This paper presents the optimization problem of three different on-demand transit systems operated by vehicles of different sizes. This problem is aimed at minimizing the total cost of the system, which consists of the temporal cost experienced by users and the operating cost incurred by transit agencies. A compact set of estimations of the user performance and operating cost is provided, based on geometric probability. The optimization procedure allows the cost comparison of different semi-flexible services. Transit systems operated by cars (shared taxicabs) with flexible layouts are preferable for low demand densities (less than 92 pax/km²-h). For very high demand (higher than 200 pax/km²-h), bus systems with fixed layout and variable stop locations present the lowest total cost per passenger. In an intermediate domain, taxi and semi-flexible services compete among each other. The estimation of unit operating costs allows decision-makers to calculate the subsidies needed to make the system profitable.

Autonomous vehicles promise to revolutionize the automobile market, although their implementation could take several decades in which both types of cars will coexist on the streets. We formulate a model for a circular city based on continuous approximations, considering demand surfaces over the city. Numerical results from our model predict direct and indirect effects of connected and autonomous vehicles. Direct effects will be positive for our cities: (a) less street supply is needed to accommodate the traffic; (b) congestion levels decrease: travel costs may decrease by 30%. Some indirect effects will counterbalance these positive effects: (c) a decrease of 20% in the value of travel time can reduce the total cost by a third; (d) induced demand could be as high as 50%, bringing equivalent total costs in the future scenario; (e) the vehicle-kilometers traveled could also affect the future scenario; and (f) increases in city size and urban sprawl. As a conclusion, the implementation of autonomous vehicles could be neutral for the cities regarding travel time costs. City planning agencies still have to promote complementary modes such as active mobility (walking and bicycle), transit (public transportation), and shared mobility (shared autonomous vehicles and mobility as a service).