Esmaeil Balal

TL;DR: A Fuzzy Inference System (FIS) which models a driver’s binary decision to or not to execute a discretionary lane changing move on freeways and has a potential to be implemented in lane change advisory systems, in autonomous vehicles, as well as microscopic traffic simulation tools.

TL;DR: In this paper, the statistical properties of 10 lane changing parameters were studied, including the gaps, times to collision between vehicles and the subject vehicle's speed, and the results suggest that using one or few selected parameters may be sufficient to quantify the risk of a lane changing event.

TL;DR: Comparative analyses on drivers’ behavior during mandatory and discretionary lane changes by examining the statistical properties of four lane changing decision variables that describe the gaps between the subject vehicle and the surrounding vehicles show that, for the three decision variables associated with gaps in the target lane, the means and distributions are not significantly different.

TL;DR: The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening, however, additional screening at the destinations and connecting airports contributed marginal benefits.

TL;DR: Five candidate measures of urban highway network resilience that are consistent with the concept of resilience triangle are proposed, derived from queue length, link speed, link travel time, frontage road delay and detour route delay, respectively.