Understanding individual travel behaviour is essential for the design of Advanced Traveller Information Systems (ATIS), which provide real-time travel information, like link travel times1,2. However, the response of road users to information is still an open question. It is not clear whether more information is beneficial. Drivers confronted with too much information may become oversaturated in the sense that information processing becomes to difficult and users develop simple heuristics to solve the situation7. Drivers may also overreact to information and thereby cause additional fluctuations. Thus, the behaviour of the drivers has to be incorporated in traffic forecasts. ATIS can reduce fluctuations only if behavioural effects are correctly taken into account. However, are there general patterns of decision behaviour with respect to information available?

Here we report on laboratory experiments of a day-to-day route choice game with two possible routes. `Drivers` had to choose between a main road and a side road. The capacity was greater for the main road. Two treatments were run in the experimental setup. Feedback in treatment I was given only about the own travel times whereas in treatment II in addition the travel times of the alternative route. The money payoffs increase with decreasing travel time. The results of the experiments are close to the Nash equilibrium. Fluctuations persisted until the end of the sessions in both treatments. Fluctuations are smaller under treatment II. Two distinct driver types could be identified. Simulations performed with an extension of a “payoff sum model” reflect the experimental data. The results help to better understand human behaviour and could optimize travel forecasts.