Simon-gutowitz Bidirectional Traffic Model Revisited

M ay 2 00 9 Simulation study of traffic accidents in bidirectional traffic models

Conditions for the occurrence of bidirectional collisions are developed based on the Simon-Gutowitz bidirectional traffic model. Three types of dangerous situations can occur in this model. We analyze those corresponding to head-on collision, rear-end collision and lane-changing collision. Using Monte Carlo simulations, we compute the probability of the occurrence of these collisions for differ...

Deeper Investigating Adequate

Cellular automata (CA) are particularly well suited for cryptographic application and there are several previous studies in this topic (Benkiniouar & Benmohamed, 2004; Gutowitz, 1995; Kari, 1992; Nandi et al., 1994; Oliveira et al., 2004; 2008; Seredynski et al., 2003; Tomassini & Perrenoud, 2000; Wuensche, 2008; Wolfram, 1986). Since CA rule is simple, local and discrete, it can be executed in...

Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the potential of deep learning methods in traffic forecasting has not yet fully been exploited in terms of the depth of the model architecture, the spatial scale of the prediction area, and the predictive power of spatial-...

College of Business Working Paper Series Exploration and Exploitation Revisited: Exploration and Exploitation Revisited: Extending March’s Model of Mutual Learning

Deep Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Short-term traffic forecasting based on deep learning methods, especially long-term short memory (LSTM) neural networks, received much attention in recent years. However, the potential of deep learning methods is far from being fully exploited in terms of the depth of the architecture, the spatial scale of the prediction area, and the prediction power of spatial-temporal data. In this paper, a ...