Risk aversion and route choice decisions.

Engineers often focus on standard drivers conditions, which are representative of one (or a collection) of average days. The choice models used are often probabilistic (random utility or discrete choice models). In the conventional approach, the probability is just the expression of the analyst's imperfect knowledge. Here, a second reason, fundamentally different which justifies a probabilistic approach, is considered. Most of the time, when routes are congested, the actual travel time is not equal to the average travel time. It is shown that the drivers' utility functions are non-linear in travel time, so that the average travel time does not provide a good enough statistic. As a consequence, the value of time, which measures the individual cost associated with the travel time incurred, does not convey enough information to represent users' preferences. The preferences for the route with the shortest average travel time but with the highest variability varies across individuals: some individuals prefer the shortest expected travel time, while others prefer to use routes with longest expected travel time, but better travel time reliability. Preference for avoiding travel time variability depends, a priori, on the individual socio-economic characteristics, attitudinal factors, and the purpose of the trip. To estimate the main parameter of the model, the degree of risk aversion, telephone interviews were used to collect information for about 4000 individuals. They were asked to choose between risk-free (constant travel time) alternatives and risky (random travel time) alternatives. Finally, two implications of the estimation of drivers' risk aversion were explored. The certain equivalent which is the value of the expected travel time that gives the same utility level as in the case of a random travel time (with a smaller expected travel time if drivers are risk averse) was calculated. Second, using the estimates of the value of time and based on the compensating variation approach, it was possible to calculate the cost associated with stochastic travel time. This computation is especially important for the design of automatic traveller information systems, since it enables the allocation of a monetary value to the provision of information. For the covering abstract see ITRD E126595.