1 The traffic flow heterogeneity caused by the different car-following dynamics among the different types 2 of vehicles has drawn increasing attention recently. This paper explores the characteristics of the four 3 types of car-truck car-following combinations, car-following-car (CC), car-following-truck (CT), truck4 following-car (TC) and truck-following-truck (TT), and their impacts on traffi...

This paper presents a method of learning reconfigurable hierarchical And-Or models to integrate context and occlusion for car detection. The And-Or model represents the regularities of car-to-car context and occlusion patterns at three levels: (i) layouts of spatially-coupled N cars, (ii) single cars with different viewpoint-occlusion configurations, and (iii) a small number of parts. The learn...

This research effort aims to compare car-following models when the models are calibrated to individual drivers with the naturalistic data. The models used are the GHR, Gipps, Intelligent Driver, Velocity Difference, Wiedemann, and the Fritzsche model. This research effort also analyzes the Wiedemann car-following model using car-following periods that occur at different speeds. The Wiedemann ca...

In this paper we consider a microscopic model of traffic flow called the adaptive time gap carfollowing model. This is a system of ODEs which describes the interactions between cars moving on a single line. The time gap is the time that a car needs to reach the position of the car in front of it (if the car in front of it would not move and if the moving car would not change its velocity). In t...

We develop a model to determine the optimal structure and size of a rail car fleet at a chemical company under uncertainty in demand and travel times as well as substitution between rail car types. First, we formulate an MILP model that accounts for the substitution relations between the types and minimizes the total direct rail car cost under given rail car availability constraints and a prede...

The car-following model is a basic model of microscopic traffic simulation. The complexity of car-following behavior is suggested by a large number of factors that influence car-following behavior. Moreover, as shown repeatedly in laboratory studies of human performance, humans are very adaptable and will develop new strategies for new situations. Meanwhile, human performance and the informatio...

Due to the increasing demand for traveling in public transportation systems and increasing traffic of vehicles, nowadays vehicles are getting to be intelligent to increase safety, reduce the probability of accident and also financial costs. Therefore, today, most vehicles are equipped with multiple safety control and vehicle navigation systems. In the process of developing such systems, simulat...