Category: Papers

Comparison of traffic reliability index with real traffic data

Existing studies have developed different indices based on various approaches including network connectivity, delay time and flow capacity, estimating the traffic reliability states from different angles. However, these indices mainly estimate traffic reliability from single view and rarely consider the combined effect of city traffic dynamics and underlying network structure. Based on percolation theory, Li et al. has developed a traffic reliability index to address this issue (Proc. Natl. Acad. Sci. USA 112(3):669-672, 2015) [1]. Here we compare this percolation-based index with one of the well-known index – congestion delay index (CDI). Using real traffic data of Beijing and Shenzhen (two large cities in China), we compare the two indices in the macroscopic trends and microscopic extreme values. The two indices are found to indicate the state of real-time traffic reliability in different consideration. Our results can be used for better evaluation of traffic system reliability and mitigation measures of traffic jams.

 

Comparison of traffic reliability index with real traffic data
Limiao Zhang, Guanwen Zeng, Shengmin Guo, Daqing LiEmail author and Ziyou Gao
EPJ Data Science20176:19
https://doi.org/10.1140/epjds/s13688-017-0115-7 

Source: epjdatascience.springeropen.com

Effects of network modularity on the spread of perturbation impact in experimental metapopulations

The networks that form natural, social, and technological systems are vulnerable to the spreading impacts of perturbations. Theory predicts that networks with a clustered or modular structure—where nodes within a module interact more frequently than they do with nodes in other modules—might contain a perturbation, preventing it from spreading to the entire network. Gilarranz et al. conducted experiments with networked populations of springtail ( Folsomia candida ) microarthropods to show that modularity limits the impact of a local extinction on neighboring nodes (see the Perspective by Sales-Pardo). In networks with high modularity, the perturbation was contained within the targeted module, and its impact did not spread to nodes beyond it. However, simulations revealed that modularity is beneficial to the network only when perturbations are present; otherwise, it hinders population growth.

Science , this issue p. [199][1]; see also p. [128][2]

[1]: /lookup/doi/10.1126/science.aal4122
[2]: /lookup/doi/10.1126/science.aan8075

Source: science.sciencemag.org

Self-Organization in Traffic Lights: Evolution of Signal Control with Advances in Sensors and Communications

Traffic signals are ubiquitous devices that first appeared in 1868. Recent advances in information and communications technology (ICT) have led to unprecedented improvements in such areas as mobile handheld devices (i.e., smartphones), the electric power industry (i.e., smart grids), transportation infrastructure, and vehicle area networks. Given the trend towards interconnectivity, it is only a matter of time before vehicles communicate with one another and with infrastructure. In fact, several pilots of such vehicle-to-vehicle and vehicle-to-infrastructure (e.g. traffic lights and parking spaces) communication systems are already operational. This survey of autonomous and self-organized traffic signaling control has been undertaken with these potential developments in mind. Our research results indicate that, while many sophisticated techniques have attempted to improve the scheduling of traffic signal control, either real-time sensing of traffic patterns or a priori knowledge of traffic flow is required to optimize traffic. Once this is achieved, communication between traffic signals will serve to vastly improve overall traffic efficiency.

 

Self-Organization in Traffic Lights: Evolution of Signal Control with Advances in Sensors and Communications
Sanjay Goel, Stephen F. Bush, Carlos Gershenson

Source: arxiv.org