Can the Waymo Open Motion Dataset Support Realistic Behavioral Modeling? A Validation Study with Naturalistic Trajectories

Abstract

Traffic behavior around major freeway weaving sections exhibits complex dynamics associated with multi-directional maneuvers such as lane changes (LCs) accompanied by shockwave-generating braking. Data to study both microscopic and macroscopic properties of congested weaving sections have been generally lacking, leaving an important lacuna in the underlying traffic science. The Third Generation Simulation (TGSIM) trajectory data set collected on multiple freeway locations in the USA provides a rich opportunity to examine the phenomena associated with high-density weaving operations on freeways. The focus of this paper is to examine the spatial-temporal distribution of average speed, LCs, and heavy vehicles (HVs). In addition, we examine the time-shifted association of speed with LCs and HVs. Our analysis reveals considerable variation of speed across lanes and longitudinal locations. LCs are generally associated with higher speeds of the surrounding traffic and correlate with the speed changes on the original and target lanes differently. In addition, differences of speed change have been found for vehicles that execute mandatory LCs (MLCs) and discretionary LCs (DLCs). Finally, while a lower average speed is associated with the existence of HVs, it tends to recover gradually when the HVs move downstream.

Yanlin Zhang

Ph.D. Candidate

My research interests lies in the intersection of behavioral science and mixed autonomy traffic flow.