Titlebook: Stochastic Two-Dimensional Microscopic Traffic Model; Theory and Applicati HongSheng Qi Book 2024 The Editor(s) (if applicable) and The Aut

短程旅游

instill

Stochastic Lateral Wandering Patterns of Mixed Traffic Flow,e critical issue is the impact of autonomous vehicles’ lateral movement on the fatigue of pavements, as they tend to focus on the lane middle line. However, as the market penetration of autonomous vehicles gradually increases, the distribution of their lateral movement within the mixed flow of vehic

人工制品

Lateral Stochasticity in Lane Changing via Logistic Diffusion Process,vehicles. Accurately describing and predicting lane changing behavior is critical for the successful implementation of autonomous vehicles. Although various approaches have been employed to address this task, current models suffer from several drawbacks, such as a lack of consideration for stochasti

BULLY

Game Behavior Within the Intersection,cities of individual lanes at each approach. However, during peak hours or at complex intersections, vehicles often become trapped within the intersection, leading to competition and a subsequent decrease in capacity. Existing microscopic traffic models, such as the gap acceptance model, fail to cap

Certainty

Intersection Deadlock Probability: Stochastic Petri Net Approach,ity and duration, have not been established. In this chapter, we employ a Petri Net (PN)-based approach to investigate the probability and duration of deadlock formation. We formulate the key components of an intersection, including vehicle trajectory, traffic signal, vehicle arrivals, and conflict

苦笑

AGOG

Myelin

Introduction,t by the autonomous vehicles. After that, literature review is conducted for car following and lane changing behaviors, which are major two models of microscopic traffic flow models. The drawbacks of current models are presented, together with the structure of the book.

Adenocarcinoma

Parallel

Real World Observations, Maneuver Estimation and Behavioral Predictability,g and acceleration/deceleration, is proposed. Furthermore, given that the datasets are collected from diverse locations and countries, an analysis is conducted to explore the variability among the datasets using a predictability index. The results indicate significant behavioral differences among drivers from distinct countries.