Modeling user adoption of advanced traveler information systems: dynamic evolution and stationary equilibrium

This paper models the growth rate and the saturation market penetration level for advanced traveler information system (ATIS) products/services with heterogeneous drivers. The price of using and the benefit gained from ATIS services are considered two key factors in explaining the growth of adoption of ATIS products. The information benefit is measured as the travel time saving between equipped and unequipped drivers and evaluated by a mixed stochastic and deterministic network equilibrium model. A modified logistic type growth model is adopted to describe the cumulative adoption of ATIS products over years. The final stationary equilibrium level of ATIS market penetration is so determined that the value of the information provided will decline to the point at which no new users will find it advantageous to purchase that service. The endogenous growth and stationary equilibrium model of market penetration of ATIS services is useful for forecasting the growth process and the impacts on the system performance of ATIS.     

Effectiveness of en route traffic information in developing countries using conventional discrete choice and neural‐network models

Providing commuters with traffic information or advising them of alternative routes during traffic incidents can alleviate congestion. For decades, advanced traveler information services (ATIS) have been devised and dedicated to this role. ATIS comprises a wide variety of technologies across the world, including radio traffic information (RTI) advisory service. RTI is common in both developed and developing countries. Although extensive literature and evaluation results of ATISs and RTI are available in developed countries, little attention has been devoted to that in developing countries. This work provides a modeling platform to study drivers' response to en route traffic information provided by Radio‐Payam broadcasting service in Tehran, the capital city of the developing country of Iran. The results are compared with counterpart cases in developed countries. Past studies and this study have employed conventional discrete models for drivers' response, such as ordered logit and ordered probit. This work evaluates the accuracy level of these conventional models in comparison with a developed neural‐network (NN) model, because it has been widely proven that NN models are highly precise. It has also been found that, apart from reliability, the conventional models are within an acceptable level of prediction accuracy compared with the NN models. The results show a high degree of similarities between the case of Tehran and its counterparts in the developing countries. The results also deliver some insights on how to improve or better implement the ATIS technologies. Copyright © 2012 John Wiley & Sons, Ltd.