The space and time dynamics of moving vehicles regulated by traffic signals governs the node connectivity and communication capability of vehicular ad hoc networks (VANETs) in urban environments. However, none of the previous studies on node connectivity has considered such dynamics with the presence of traffic lights and vehicle interactions. In fact, most of them assume that vehicles are distributed homogeneously throughout the geographic area, which is unrealistic. We introduce in this paper a stochastic traffic model for VANETs in signalized urban road systems. The proposed model is a composite of the fluid model and stochastic model. The former characterizes the general flow and evolution of the traffic stream so that the average density of vehicles is readily computable, while the latter takes into account the random behavior of individual vehicles. As the key contribution of this paper, we attempt to approximate vehicle interactions and capture platoon formations and dissipations at traffic signals through a density-dependent velocity profile. The stochastic traffic model with approximation of vehicle interactions is evaluated with extensive simulations, and the distributional result of the model is validated against real-world empirical data in London. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the knowledge of the mean vehicular density dynamics and its probability distribution from the stochastic traffic model, we determine the degree of connectivity in the communication network and illustrate that system engineering and planning for optimizing both the transport (in terms of congestion) and communication networks (in terms of connectivity) can be carried out with the proposed model.

In the design and planning of vehicular ad-hoc networks, road-side infrastructure nodes are commonly used to improve the overall connectivity and communication capability of the networks, however, to determine the locations to install the infrastructure nodes for optimal performance based on the ever-changing density and connectivity dynamics of moving vehicles remains to be a challenging issue. In this paper, we introduce a stochastic traffic model to capture the space and time dynamics of vehicles in signalized urban road systems to identify poorly-connected regions for infrastructure node placements. To closely approximate the practical road conditions, we propose a density-dependent velocity profile to approximate vehicle interactions and capture platoons formation and dissipation at traffic signals. Numerical results are presented to evaluate the stochastic traffic model. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the understandings of the vehicular density dynamics from the proposed model, we illustrate that connectivity dynamics of vehicles can be determined and consequent system engineering and planning can be carried out.

In a Vehicular Ad-hoc Network (VANET), the amount of interference from neighboring nodes to a communication link is governed by the vehicle density dynamics in vicinity and transmission probability of terminals. It is obvious that vehicles are distributed non-homogeneously along a road segment due to traffic controls and speed limits at different portions of the road, the common assumption of homogeneous node distribution in the network in most of the previous work in mobile ad-hoc networks thus appears to be inappropriate in VANETs. To capture the density dynamics in generic urban routes, we utilize a fluid model to characterize the general vehicular traffic flow, and a stochastic model to capture the randomness of individual vehicles, from which we can acquire respectively the densities of the mean number of vehicles along the road and the probability distribution. With the knowledge of the vehicular density dynamics from the stochastic traffic model, we determine the throughput and progress performances of a routing strategy, and confirm the accuracy of the analytical results through simulations. The analytical model proposed in this paper serves as a fundamental building block for performance analysis of other transmission protocols and network configurations, we also demonstrate that the optimal transmission probability for optimized network performance can be found from our results, which provides insights into system engineering and protocol designs in VANETs.

This work presents an integrated mobile environmental sensing and analysis system developed to support the management of transport and urban air quality. A novel spectroscopic UV sensor is employed to provide second-by-second measurements of multiple pollutants at ppb levels. Sensor nodes are deployed on vehicles, infrastructure and people and feed data into a dynamically configurable e-science computing platform that scales to support both near real-time incident management and longer term strategic planning decisions. This paper describes the system architecture and sensor node design alongside results from system development testing. It goes on to highlight avenues for future development and the potential for further applications involving the wider sensors community.

Vehicular Ad hoc NETworks (VANETs) is a subclass of Mobile Ad hoc NETworks (MANETs). However, automotive ad hoc networks will behave in fundamentally different ways than the predominated models in MANET research. Driver behaviour, mobility constraints and high speeds create unique characteristics in the network. All of these constraints have implications on the VANET architecture at the physical, link, network, and application layers. To facilitate the cross-layer designs for VANETs, understanding of the relationship between mobility and network connectivity is of paramount importance. In this paper, we focus on studying transport systems with structured mobility (e.g., bus systems), which have unique characteristics on the road such as fixed routes that have never been explored in previous work. The main contributions of this paper are three-fold: 1) we provide an analytical framework including the design requirements of the mobility model for realistic vehicular network studies, and metrics for evaluating node connectivity in vehicular networks; 2) we demonstrate, through simulation, the impacts of marco- and micro-mobility models, and various transport elements on network connectivity; and 3) we show that multi-hop paths perform dramatically poorer than single-hop links in vehicular networks. Specifically, two- hop and three-hop (communication) paths can only respectively achieve less than 27% and 13% of the average duration of single-hop links. Such kind of knowledge of the performance of multi-hop transmission will be significant for the studies of routing algorithm and other networking functions in vehicular networks.