To reduce traffic along a heavily congested Texas toll road, researchers are using stated preference surveys and discrete choice models to understand how motorists will respond to alternative time-of-day pricing policies.
Transport and Travel Demand Modelling
RAND Europe has contributed to the development and testing of new approaches in transport studies for over 25 years. The application of discrete choice models using observations of individual travel behaviour has allowed significant improvements in the quality and range of applicability of urban, regional and national (multi-modal) travel demand forecasting techniques.
RAND Europe’s transport models contain substantial detail about travellers, including detailed segmentation of traveller behaviour by person and household types. Many of these characteristics have a significant influence on travel behaviour and we therefore believe that it is essential that such influences are considered when forecasting future travel demand. Our models also contain multiple modes and purposes, and a wide range of possible behavioural responses, including explicit representation of such responses as:
- choice of mode
- choice of access mode, e.g. park-and-ride, and at which station
- choice of route
- choice of travel destination
- choice of departure time
- car ownership and licence holding
- trip frequency
- residential location
- employer location
Considerable attention is given to the implications of excess demand in the form of congestion, and the resulting feedback to other stages in the demand formation process, e.g. time-of-day of travel, and ultimately the mode, destination and frequency of the trip.
Our model parameters are evidence-based, usually derived from local surveys. We frequently combine a range of different types of data, and are adept at developing procedures to overcome data bias during analysis.
We have extensive experience in developing demand forecasting systems from the estimated models, including development of population forecasting methods to produce the detailed population inputs required for future forecasts, methods for implementing forecast changes (referred to as pivoting), and outputting information required for appraisal using the Department for Transport's Economic Efficiency of the Transport System (TEE) or other approaches.