Peer, Stefanie Knockaert, Jasper Koster, Paul Tseng, Yin-Yen Verhoef, Erik
Year of Publication:
Tinbergen Institute Discussion Paper 11-180/3
A common way to determine values of travel time and schedule delay is by estimating departure time choice models using revealed preference (RP) data. The estimation of such models requires that (expected) travel times are known for both chosen as well as unchosen departure time alternatives. As the availability of such data is limited, most departure time choice studies only take into account travel times on trip segments rather than door-to-doortravel times, or use very rough measures of door-to-door travel times. We show that ignoring the temporal and spatial variation of travel times, and in particular, the correlation of travel times across links may lead to biased estimates of the value of time. To approximate door-to-door travel times for which no complete measurement is possible, we develop a model that relates travel times on links with continuous speed measurements to travel times on links where relatively sparse GPS-based speed measurements are available. We use geographically weighted regression to estimate the location-specific relation between the speeds on these two types of links, which is then used for travel time prediction at different locations, days, and times of the day. This method is not only useful for the calculation of door-to-door travel times in departure time choice models but is generally relevant for predicting travel times in situations where continuous speed measurementsshould be enriched with GPS data.
Scheduling model revealed preference data door-to-door travel times geographically weighted regression GPS