TRESIS (Transport and Environmental Strategy Impact Simulator): Application to a Case Study in NE Sydney

This paper presents an integrated microsimulation urban passenger transport model system (TRESIS) for evaluating the impact of a large number of interrelated policy instruments on urban travel behavior and the environment. The model system has four integrated modules defining household location and automobile choices, commuter workplace and commuting travel choices, non-commuting travel activity, and worker distributed work practices. The demand model system, estimated as a set of discrete and continuous choice models, is combined with a set of equilibrating criteria in each of the location, automobile and commuting markets to predict overall demand for passenger travel in various socio-economic segments, automobile classes and geographic locations. The current version has been developed to operate at a high level of aggregation for the Sydney region, comprising a 14-zone system, with a spider-web network, and is designed to explore the impacts of broad strategic directions. The model system is embedded within a decision support system to make it an attractive suite of tools for practitioners. We illustrate the usefulness of TRESIS to a major investment option in Northeast Sydney, to replace a bottleneck opening bridge with either bridge improvements together with improvements to a number of intersections on the roads serving the region, or several possible tunnel options, including different levels of tolls for the tunnels. The application of TRESIS to this case was considered a success, with the model providing useful outputs on the revenue implications of various alternative tolls, the impacts of the proposals on regional travel, and the likely effects on public transport ridership

SERVICE QUALITY--DEVELOPING A SERVICE QUALITY INDEX IN THE PROVISION OF COMMERCIAL BUS CONTRACTS

This paper investigates ways of quantifying service quality and comparing the levels within and between bus operators. An earlier pilot program showed the value of a service quality index as a way to capture customer perceptions of service quality. This paper presents the findings of the second phase of this study. Two key features were identified that needed more attention: selection of service segments within an operator\u27s domain, and a carefully structured sampling plan. One major public operator and one major private operator were invited to propose service segments. A total of nine service segments were surveyed in this round, sufficient to establish a benchmarking capability for ongoing monitoring for each segment, and through aggregation, for each operator. In order to benchmark meaningfully, this study identifies the important weights to attach to each attribute that recognizes the differences in scale between the utility expressions associated with each segment. Having a seat all the way and bus frequency were ranked as the strongest positive contributors, while travel time and bus fare were the two largest negative contributors

Service quality--developing a service quality index in the provision of commercial bus contracts

The measurement of service quality continues to be a challenging research theme and one of great practical importance to service providers and regulatory agencies. The key challenges begin with the identification of the set of potentially important dimensions of service quality perceived by passengers, current and potential. We then have to establish a way of measuring each attribute and identifying their relative importance in the overall calculation of satisfaction associated with existing service levels. Once a set of relevant attributes has been identified, this information can be integrated into programs such as monitoring and benchmarking, and even in contract specification. This paper, building on earlier research by the authors, investigates ways of quantifying service quality and comparing the levels within and between bus operators. The importance of establishing suitable market segments and the need to scale the service quality index for each operator to make meaningful comparisons is highlighted.