On the relationship between travel time and travel distance of commuters

Abstract

Abstract. This paper gives a detailed empirical analysis of the relationships between di¨erent indicators of costs of commuting trips by car: di¨erence as the crow¯ies, shortest travel time according to route planner, corresponding travel distance, and reported travel time. Reported travel times are usually rounded in multiples of ®ve minutes. This calls for special statistical techniques. Ignoring the phenomenon of rounding leads to biased estimation results for shorter distances. Rather surprisingly, the distance as the crow¯ies and the network distance appear to be slightly better proxies of the reported travel time compared with the shortest network travel time as indicated by the route planner. We conclude that where actual driving times are missing in commuting research the other three indicators mentioned may be used as proxies, but that the following problems may emerge: actual travel times may be considerably higher than network times generated by route planners, and the average speed of trips increases considerably with distance, implying an overestimate of travel time for long distance commuters. The only personal feature that contributes signi®cantly to variations in reported travel times is gender: women appear to drive at lower average speeds according to our data. As indicated in the paper this may be explained by the di¨erences in the car types of male and female drivers (females drive older and smaller cars) as well as higher numbers of stops/trip chaining among women. A concise analysis is carried out for carpoolers. Car-pooling leads to an increase in travel time of some 17% compared with solo drivers covering the same distance. In the case of car poolers, the above mentioned measures appear to be very poor proxies for the actual commuting times.

Adverse Weather and Commuting Speed

“…Some other results are that older people drive slower, that trips made during weekends are faster than trips made on working days, and that male commuters drive slightly faster than female commuters. The latter is consistent with the literature (see, e.g., Rietveld et al 1999;Van Ommeren and Dargay 2006).…”

“…We select the trips longer than 10 km to increase the probability that a trip takes place partly on highways. In order to control for carpooling effects, we control for the number of people in the vehicle (Rietveld et al 1999). Seasonal effects are captured by seasonal dummy variables.…”

Over-reporting vs. overreacting: Commuters’ perceptions of travel times

“…Most of them found that individuals substantially overstate travel times (e.g. O'Farrell and Markham, 1974;Burnett, 1978;Henley et al, 1981;MVA Consultancy, 1987;Rietveld et al, 1999;Van Exel and Rietveld, 2009). Based on this evidence, they usually conclude that travel times are perceived as longer than they actually are.…”

“…Van Exel and Rietveld, 2009) or the possibility that actual travel times might have been measured wrongly (e.g. Rietveld et al, 1999) as plausible explanations for the overstated travel times. Consistent with the results obtained in these earlier studies, also we find that travel times are strongly overreported, by a factor of 1.5 on average.…”

Welfare Effects of Adverse Weather through Speed Changes in Car Commuting Trips

“…14 Furthermore, we interact the congestion variable with rush hour as well as with a rain dummy, as one may expect that rain may have stronger negative effects during rush hours on congested roads. In order to control for carpooling effects, we control for the number of people in the vehicle (Rietveld et al, 1999). Seasonal effects are captured by seasonal dummy variables.…”