Microscopic Road Traffic Simulation Research Articles

ENHANCE: Multilevel Heterogeneous Performance-Aware Re-Partitioning Algorithm For Microscopic Vehicle Traffic Simulation

Driven by our work on a large-scale distributed microscopic road traffic simulator, we present ENHANCE, a novel re-partitioning approach that allows incorporating fine-grained simulator-specific cost models into the partitioning process to account for the actual performance characteristics of the simulator. The use of explicit cost models enables partitioning for heterogeneous resources, which are a common occurrence in cloud deployments. Importantly, ENHANCE can be used in conjunction with other partitioning approaches by further enhancing partitions according to provided cost models. We demonstrate the benefits of our approach in an experimental evaluation showing performance improvements of up to 29% against METIS under heterogeneous conditions. Taking a different perspective, the partitioning produced by ENHANCE can provide similar performance as METIS, but using up to 20% fewer resources.

Real-Time Counting of Vehicles Stopped at a Traffic Light Using Vehicular Network Technology

Vehicular Adhoc NETworks (VANETs) is a new and emerging technology for wireless communications that has attracted considerable attention in the last years from the academic, scientific, industrial and governmental communities, due to the improvements and the new features that it brings to the Intelligent Transportation Systems (ITSs). In this paper, we present an algorithm that uses VANET technology to determine the total number of vehicles that are stopped at a traffic light at an intersection. To facilitate an efficient counting, we divide the road into fixed-size road regions and through a leader election mechanism, we designate one vehicle in each region as the “Region Leader” that is in charge of computing and propagating the total number of nodes in its region. Additionally, the region leader will act as a router to retransmit counting information from other region leaders that are further away, so it can eventually reach the central processing point where it is processed. We have carried out extensive experiments in various scenarios to validate and analyze the behavior and precision of our new proposed algorithm. Also, we compare our algorithm with another strategy proposed by a research team led by Alok Rajan. Our simulations were done using Veins (Vehicle in Network Simulation), an open-source simulation framework that ties together two simulators: OMNeT++ for the network simulation and SUMO for the microscopic road traffic simulation. Both simulators run in parallel and communicate with each other through a TCP connection using a protocol called TraCI (Traffic Control Interface). Our simulation results show that the algorithm performs an effective counting of vehicles, with a reduced response time, and a small total number of control messages sent by the vehicles to accomplish the counting task, under different conditions of vehicular traffic loads.

A Large-Scale SUMO-Based Emulation Platform

A hardware-in-the-loop simulation platform for emulating large-scale intelligent transportation systems is presented. The platform embeds a real vehicle into SUMO, a microscopic road traffic simulation package. Emulations, consisting of the real vehicle, and potentially thousands of simulated vehicles, are run in real time. The platform provides an opportunity for real drivers to gain a feel of being in a large-scale connected vehicle scenario. Various applications of the platform are presented.

Minimum Broadcasting Structure for Optimal Data Dissemination in Vehicular Networks

In this paper, we model a vehicular multihop network as an evolving graph and formulate the problem of optimal data dissemination over the network in terms of minimum number of transmissions. We show that the problem belongs to the NP complexity class and provide an easy to implement polynomial-time 2 τH(Δ)-approximation algorithm, where τ is the number of different subgraphs that comprise the evolving graph, and H(Δ) is the harmonic number of the degree of the evolving graph. By means of applying our heuristic over a vehicular scenario generated by a microscopic road-traffic simulator, we provide some insight into the data dissemination issue. In addition, the proposed algorithm is employed to benchmark a state-of-the-art communication protocol. We hope this paper will inspire more efficient heuristics and data dissemination solutions.

Development of Microscopic Road Traffic Simulation Model by using Fuzzy Neural Network

A microscopic road traffic simulation model is proposed in this study. The characteristic of the speed decision model is to be able to consider an individual drive characteristic by using the Car-Following model which uses fuzzy neural network. The route choice model is built by use of the logit model. The simulation model is checked at actual state. The TDM policy is examined for the Toyota city, and utility was shown. Moreover, the traffic capacity is analyzed the influence which the change in the driver's characteristic, and it showed that driver's influence was largely received.

PARAMICS?Parallel microscopic simulation of road traffic

This paper describes work done on the original PARAMICS project, which was developed for the Edinburgh Parallel Computing Centre to examine parallel microscopic road traffic simulation. The simulator, constructed originally for a Thinking Machines Connection Machine (CM-200), uses a data-parallel approach to simulate approximately 200,000 vehicles on 20,000 miles of roadway. More recent work has focused on the use of a message-passing paradigm, with a 256-node CRAY T3D as the target machine. The message-passing version of PARAMICS, PARAMICS-MP, is inherently scalable and can model many smaller networks on a broad range of platforms.