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This paper attempts to identify factors that may influence the gap acceptance behavior of drivers who turn left from the major road at unsignalized intersections. Drivers’ accepted and rejected gaps as well as their age and gender were collected at six unsignalized intersections with both two and four lanes on the major road, with and without the presence of a Left-Turn Lane (LTL), and with both high and low Speed Limits (SLs). Whether or not a driver accepts a given gap was considered as a binary decision and correlated logit models were used to estimate the probability of accepting a gap. Models with different factors were tested and the best model was selected by the quasi-likelihood information criterion. The gap duration, the number of rejected gaps, the mean and total time interval of the rejected gaps and the gender of the driver were all significant in explaining the variation of the gap acceptance probability, whereas the number of lanes of the major road, the presence of LTL, the SL and the driver’s age category were not. Gap acceptance probability functions were determined based on the best model, including both the factors of the number of rejected gaps and the mean time interval of the rejected gaps. As the values of these two factors increase, the probability of accepting a given gap rises up. The developed model can be further applied in practice to improve the analysis of traffic operations and capacity at unsignalized intersections. [ABSTRACT FROM PUBLISHER]

This article describes an investigation of possible differences in elderly drivers’ gap acceptance behavior from other drivers when making left turns across oncoming traffic at unsignalized intersections. Elderly and other drivers were observed turning left at two unsignalized intersections with different speed limits of major roads. Statistical analyses were used to identify whether older drivers choose different gaps for left turns. Results indicated that drivers older than age 70 were different from drivers younger than age 35 and drivers age 55 to 69 in gap selection and female drivers different from male drivers. Finally, traffic simulations were run in VISSIM to determine how age differences in gap acceptance impact traffic operations. Results showed significant differences in the delay time, the number of stops per vehicle, and the total delay time of the network for drivers older than age 70 and other drivers under the same traffic conditions. [ABSTRACT FROM AUTHOR]