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All too often, the performance of vehicular communications is benchmarked merely for a single link. A major challenge for benchmarking the performance of multiple interacting vehicles is the definition of repeatable vehicular scenarios. In this study, the authors propose and discuss an approach for performance analysis of the IEEE 802.11p standard in urban interference channels, by linking network simulations to a Software Defined Radio (SDR) setup. This approach provides communication performance measurements in the worst-case interference scenario caused by an urban traffic jam. They do this by starting out with vehicular traffic flow simulations and continue to model the medium access. They furthermore introduce an algorithm to reduce the complexity of the communication network while retaining its properties. Finally, they use a setup of SDR encompassing the communication nodes and channel emulators that emulate urban channels to measure the packet level performance as a function of signal-to-interference ratio and distance to a receiver under urban traffic conditions. [ABSTRACT FROM AUTHOR]

Traffic signal controls have become an integral part of urban traffic management and operations and play a crucial role in both mitigating congestion and reducing or eliminating conflicts at intersections. Starting with the installation of the first traffic signal in London in the nineteenth century, signal control technology has evolved steadily. Nowadays, traffic signal control is not only used to provide the right-of-way at intersections, but also to improve traffic efficiency by means of minimizing waiting times and optimizing traffic flow. In this paper we present recent efforts to introduce different types of both time-based and actuated traffic signal control strategies into the microscopic traffic simulator TraffSim. Furthermore, we demonstrate the applicability of selected control strategies by simulating both an isolated four-way intersection and a multi-intersection scenario under consideration of varying traffic densities. Moreover, we quantify the improvements in traffic efficiency imparted by these control strategies in terms of intersection throughput, waiting times, and network load. [ABSTRACT FROM AUTHOR]

Transport delays due to traffic jams are manifested in many urban areas worldwide. To make road traffic networks more efficient, intelligent transport services are currently being developed and deployed. In order to mitigate (or even avoid) congestion, vehicle-to-vehicle and vehicle-to-infrastructure communications provide a means for cooperation and intelligent route management in transport networks. This paper introduces the novel predictive congestion minimization in combination with an A*-based router (PCMA*) algorithm, which provides a comprehensive framework for detection, prediction, and avoidance of traffic congestion. It assumes utilization of vehicle-to-X communication for transmission of contemporary vehicle data such as route source and destination or current position, as well as for provision of the routing advice for vehicles. PCMA* further contains a component for intelligent selection of vehicles to be rerouted in case of a congestion, as well as an A*-based routing algorithm, taking into consideration the current road conditions and predicted future congestion. We prove the performance by dynamic microscopic traffic simulations in a real-world and an artificial road network scenario. Due to the well-performing prediction, the results reveal substantial advantages in terms of time and fuel consumption compared not only with situations with no active rerouting system but also with simple rerouting algorithms and more sophisticated approaches from literature. [ABSTRACT FROM PUBLISHER]

This paper introduces an LTE system level simulator and presents investigations of scenarios with differently balanced traffic emergence between uplink and downlink as well as inhomogeneous distribution of link direction asymmetry. In the TDD mode of LTE, duplexing is implemented via sharing the time domain between uplink and downlink users. This is done by different switching configurations, which offer varying capacity distributions between downlink and uplink, from a downlink-heavy configuration with 90 percent of the capacity in downlink direction to uplink heavy configurations with 60 percent uplink. We utilize the available capacity perfectly by adjusting the link configuration appropriately to traffic emergence. Performance gains when selecting a configuration appropriate to the arising traffic compared to usage of a static configuration with equally distributed capacity are investigated. In case of different configurations, additional interference can occur in neighbored cells due to distinct communication direction at the same time. We clarify the differences between these scenarios and quantify the gains and losses when the switching point between uplink and downlink is variable. [ABSTRACT FROM AUTHOR]

With our interest to reduce traffic congestion, simulations are necessary to investigate how to achieve this goal. Because of the difficulty of real-time experiments, traffic simulators are a good and widely used tool for analyzing specific situations of the traffic flow virtually. This paper introduces TraffSim, a new platform-independent framework, which is capable of simulating microscopic vehicular road traffic in a time-continuous manner. It is able to simulate scenarios close to reality by using OpenStreetMap but also artificial road networks. TraffSim is able to represent multilane motorways or dense city road networks including multiple types of intersections or one-way. Apart from comprehensive support for models for longitudinal movement, lane-changing and fuel-consumption, a supplementary component combines congestion detection, prediction and minimization of traffic jams through intelligent rerouting algorithms. We present the architectural and logical aspects of the simulator, as well as the user interface and statistical features. [ABSTRACT FROM AUTHOR]