Parallel Implementations of Cellular Automata for Traffic Models

The Biham-Middleton-Levine (BML) traffic model is a simple two-dimensional, discrete Cellular Automaton (CA) that has been used to study self-organization and phase transitions arising in traffic flows. From the computational point of view, the BML model exhibits the usual features of discrete CA, where the state of the automaton are updated according to simple rules that depend on the state of each cell and its neighbors. In this paper we study the impact of various optimizations for speeding up CA computations by using the BML model as a case study. In particular, we describe and analyze the impact of several parallel implementations that rely on CPU features, such as multiple cores or SIMD instructions, and on GPUs. Experimental evaluation provides quantitative measures of the payoff of each technique in terms of speedup with respect to a plain serial implementation. Our findings show that the performance gap between CPU and GPU implementations of the BML traffic model can be reduced by clever exploitation of all CPU features

Non-concave fundamental diagrams and phase transitions in a stochastic traffic cellular automaton

Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the discovery of the emergence of four distinct phases. Studying the transitions between these phases, allows us to establish a rigorous classification based on their tempo-spatial behavioral characteristics. As a result from the system's complex dynamics, its flow-density relation exhibits a non-concave region in which forward propagating density waves are encountered. All four phases furthermore share the common property that moving vehicles can never increase their speed once the system has settled into an equilibrium

ICT Infrastructure for Cooperative, Connected and Automated Transport in Transition Areas

One of the challenges of automated road transport is to manage the coexistence of conventional and highly automated vehicles, in order to ensure an uninterrupted level of safety and efficiency. Vehicles driving at a higher automation level may have to change to a lower level of automation in a certain area under certain circumstances and certain (e.g. road and weather) conditions. The paper targets the transition phases between different levels of automation. It will review related research, introduce a concept to investigate automation level changes, present some recent research results, i.e. assessing key performance indicators for both analysing driver behaviour and traffic management in light of autonomous vehicles, an initial simulation architecture, and address further research topics on investigation of the traffic management in such areas (called "Transition Areas") when the automation level changes, and development of traffic management procedures and protocols to enable smooth coexistence of automated, cooperative, connected vehicles and conventional vehicles, especially in an urban environment

Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model

In this paper a method is proposed for performance evaluation of road traffic control systems. The method is designed to be implemented in an on-line simulation environment, which enables optimisation of adaptive traffic control strategies. Performance measures are computed using a fuzzy cellular traffic model, formulated as a hybrid system combining cellular automata and fuzzy calculus. Experimental results show that the introduced method allows the performance to be evaluated using imprecise traffic measurements. Moreover, the fuzzy definitions of performance measures are convenient for uncertainty determination in traffic control decisions.Comment: The final publication is available at http://www.springerlink.co

Energy Dissipation Burst on the Traffic Congestion

We introduce an energy dissipation model for traffic flow based on the optimal velocity model (OV model). In this model, vehicles are defined as moving under the rule of the OV model, and energy dissipation rate is defined as the product of the velocity of a vehicle and resistant force which works to it.Comment: 15 pages, 19 Postscript figures. Reason for replacing: This is the submitted for

Modelling Future Mobility - Scenario Simulation at Macro Level

The aim of the report is to simulate policy scenarios for passenger transport using Europe-wide transport models, estimate their potential impacts and demonstrate how do they differ from each other and from the reference scenario for 2030. In more detail, the main objectives of the deliverable can be given as follows: - to model future multi-modal mobility scenarios for passengers formulated within the previous tasks of the project, - to simulate impacts of identified trends and selected strategies on demand, supply and technology at macro level, - to analyse impacts of selected policies and identified trends on mobility patterns such as in travel demand and modal split, - to estimate potential impacts of selected policy measures on environmental indicators via transport emissions and vehicle fleet sizes, - to compare impacts of different scenario options in quantitative terms and provide useful insights for exploring best policy scenarios and strategies for sustainable passenger transport. The research has been conducted under the OPTIMISM project which was received funding from the European Union's Seventh Framework Programme (FP7/2007-2013), grant agreement n° 284892. The report has been produced as the OPTIMISM project deliverable 3.4: Modelling Future Mobility - Scenario Simulation at Macro Level.JRC.J.1-Economics of Climate Change, Energy and Transpor

Spring-block model for a single-lane highway traffic

A simple one-dimensional spring-block chain with asymmetric interactions is considered to model an idealized single-lane highway traffic. The main elements of the system are blocks (modeling cars), springs with unidirectional interactions (modeling distance keeping interactions between neighbors), static and kinetic friction (modeling inertia of drivers and cars) and spatiotemporal disorder in the values of these friction forces (modeling differences in the driving attitudes). The traveling chain of cars correspond to the dragged spring-block system. Our statistical analysis for the spring-block chain predicts a non-trivial and rich complex behavior. As a function of the disorder level in the system a dynamic phase-transition is observed. For low disorder levels uncorrelated slidings of blocks are revealed while for high disorder levels correlated avalanches dominates.Comment: 6 pages, 7 figure