Optimal transportation with traffic congestion and Wardrop equilibria

In the classical Monge-Kantorovich problem, the transportation cost only depends on the amount of mass sent from sources to destinations and not on the paths followed by this mass. Thus, it does not allow for congestion effects. Using the notion of traffic intensity, we propose a variant taking into account congestion. This leads to an optimization problem posed on a set of probability measures on a suitable paths space. We establish existence of minimizers and give a characterization. As an application, we obtain existence and variational characterization of equilibria of Wardrop type in a continuous space setting

Estimating daily nitrogen dioxide level: Exploring traffic effects

Data used to assess acute health effects from air pollution typically have good temporal but poor spatial resolution or the opposite. A modified longitudinal model was developed that sought to improve resolution in both domains by bringing together data from three sources to estimate daily levels of nitrogen dioxide ($\mathrm {NO}_2$) at a geographic location. Monthly $\mathrm {NO}_2$ measurements at 316 sites were made available by the Study of Traffic, Air quality and Respiratory health (STAR). Four US Environmental Protection Agency monitoring stations have hourly measurements of $\mathrm {NO}_2$. Finally, the Connecticut Department of Transportation provides data on traffic density on major roadways, a primary contributor to $\mathrm {NO}_2$ pollution. Inclusion of a traffic variable improved performance of the model, and it provides a method for estimating exposure at points that do not have direct measurements of the outcome. This approach can be used to estimate daily variation in levels of $\mathrm {NO}_2$ over a region.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS642 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Predicting Risk for Deer-Vehicle Collisions Using a Social Media Based Geographic Information System

As an experiment investigating social media as a data source for making management decisions, photo sharing websites were searched for data on deer sightings. Data about deer density and location are important factors in decisions related to herd management and transportation safety, but such data are often limited or not available. Results indicate that when combined with simple rules, data from photo sharing websites reliably predicted the location of road segments with high risk for deer-vehicle collisions as reported by volunteers to an internet site tracking roadkill. Use of Google Maps as the GIS platform was helpful in plotting and sharing data, measuring road segments and other distances, and overlaying geographical data. The ability to view satellite images and panoramic street views proved to be a particularly useful. As a general conclusion, the two independently collected sets of data from social media provided consistent information, suggesting investigative value to this data source. Overlaying two independently collected data sets can be a useful step in evaluating or mitigating reporting bias and human error in data taken from social media

Fine-Grained vs. Average Reliability for V2V Communications around Intersections

Intersections are critical areas of the transportation infrastructure associated with 47% of all road accidents. Vehicle-to-vehicle (V2V) communication has the potential of preventing up to 35% of such serious road collisions. In fact, under the 5G/LTE Rel.15+ standardization, V2V is a critical use-case not only for the purpose of enhancing road safety, but also for enabling traffic efficiency in modern smart cities. Under this anticipated 5G definition, high reliability of 0.99999 is expected for semi-autonomous vehicles (i.e., driver-in-the-loop). As a consequence, there is a need to assess the reliability, especially for accident-prone areas, such as intersections. We unpack traditional average V2V reliability in order to quantify its related fine-grained V2V reliability. Contrary to existing work on infinitely large roads, when we consider finite road segments of significance to practical real-world deployment, fine-grained reliability exhibits bimodal behavior. Performance for a certain vehicular traffic scenario is either very reliable or extremely unreliable, but nowhere in relative proximity to the average performance.Comment: 5 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1706.1001

Tweets on the road

The pervasiveness of mobile devices, which is increasing daily, is generating a vast amount of geo-located data allowing us to gain further insights into human behaviors. In particular, this new technology enables users to communicate through mobile social media applications, such as Twitter, anytime and anywhere. Thus, geo-located tweets offer the possibility to carry out in-depth studies on human mobility. In this paper, we study the use of Twitter in transportation by identifying tweets posted from roads and rails in Europe between September 2012 and November 2013. We compute the percentage of highway and railway segments covered by tweets in 39 countries. The coverages are very different from country to country and their variability can be partially explained by differences in Twitter penetration rates. Still, some of these differences might be related to cultural factors regarding mobility habits and interacting socially online. Analyzing particular road sectors, our results show a positive correlation between the number of tweets on the road and the Average Annual Daily Traffic on highways in France and in the UK. Transport modality can be studied with these data as well, for which we discover very heterogeneous usage patterns across the continent.Comment: 15 pages, 17 figure