Development of a methodology for modeling ramp driver behavior during freeway merge maneuvers

Freeway entrance ramp accelerations and merging processes are complex and have significant impacts upon freeway traffic operations and ramp junction geometric designs. The complexity is a result of the fact that driver psychological components have multiple dimensions affecting freeway merge decisions.; The major objective of this dissertation is to develop empirical methodologies for modeling ramp driver acceleration-deceleration and gap acceptance behavior during freeway merge maneuvers. A large quantity of freeway merge data were collected from several entrance ramps including both parallel and taper type acceleration lanes capturing a wide traffic flow range to suit different analysis purposes. Comprehensive freeway merge traffic analyses were conducted using the collected data. Both graphical presentations and independence tests in contingency tables indicated that ramp vehicle merge behavior is insignificantly related to any single traffic parameter, such as ramp vehicle approach speeds, freeway flow levels, and speed differentials as well as time or distance gaps between ramp vehicles and surrounding freeway and ramp vehicles. Combination forms of these traffic parameters were found to be better indicators for modeling freeway merge driver behavior.; Initially, ramp vehicle acceleration-deceleration behavior models were conceptually formulated as extended forms of conventional nonlinear car-following models incorporating joint freeway and ramp vehicle effects. These sophisticated nonlinear specifications, although theoretically attractive, have been proven to be infeasible to predict dynamic ramp vehicle acceleration-deceleration rates. A bi-level calibration framework, however, successfully provided good calibration results. A multinomial probit model, using speed differentials, distance separations of ramp vehicles to corresponding freeway and ramp vehicles, distance to the acceleration lane terminus, and Markov indexes as attributes, predicted ramp driver acceleration, deceleration, or constant speed choice behavior. The resulting acceleration or deceleration rate magnitudes were predicted by a family of exponential curves using ramp vehicle speed as an explanatory variable. Calibration results of a binary logit gap acceptance function indicated that perceived ramp driver angular velocity to a corresponding freeway lag vehicle and remaining distance to the acceleration lane end are the best gap acceptance decision criteria.