Aspects of impact of intelligent transportation systems on modal split of surface freight carriers

Abstract

The objectives of the thesis are: (1) to demonstrate the possible capacity gains in terms of passenger cars when advanced vehicle control system is implemented and speculate its probable implications on freight transportation by trucks, (2) to develop mathematical freight demand models for the railway and trucking industry using the most recent data available, and (3) to propose a methodology to modify the demand models to capture the effects of Intelligent Transportation Systems (ITS) technologies on the modal s lit. Accordingly, probable automated highway scenarios are discussed and passenger car capacity gains are estimated for one of the automated highway scenario. The possible effects on freight movement due to this increased capacity is discussed. Statistical modal split models for three commodity groups are developed for the present highway infrastructure. The models developed incorporate the level of service (LOS) characteristics. A methodology is developed from the concepts of fuzzy logic, fuzzy expert systems, and approximate reasoning to capture expert opinions regarding changes in LOS characteristics in crisp terms and incorporate it in the model developed earlier. The methodology proposed may be utilized as a decision support system by the transportation planners, especially, when studying the market potential of new products.