Urban freight distribution and innovative last-mile solutions from a traffic perspective

Urban population growth, the rise of e-commerce, and the increased need for economically and environmentally sustainable solutions represent urban freight distribution’s biggest challenges. Traffic and city logistics are often two sides of the same coin, as congestion affects city freight movements and vice versa. For this reason, it is important to develop comprehensive mobility and traffic management solutions that consider both systems. During the last decade, technology improvements in wireless communication, computational and sensing technologies, have paved the way to a series of mobility and transportation options (e.g., crowdshipping and driverless vehicles) that could transform the landscape of last-mile delivery. The main contribution of this dissertation consists of modeling urban freight impacts on traffic and investigating the potential implications of innovative last-mile solutions. The first part of this dissertation focuses on the feedback between freight movements and traffic, taking into consideration the impact of passenger vehicles on commercial vehicles, and vice versa. In order to achieve this goal, it is necessary to model trucks’ movements and loading/unloading operations with ad-hoc traffic simulations. Most of existing research has focused on analytical, static, or microscopic models, that either lack accuracy or scalability. Hence, this dissertation creates algorithms that couple existing macroscopic traffic flow models with the microscopic behavior of delivery vehicles. This issue is investigated both at single-link and network levels, by means of a suitable simulation framework. In both cases, applications of the modeling approach for freight traffic and freight demand management are shown. In the second part of this dissertation the potential impacts of last-mile delivery solutions are evaluated using the developed simulation framework. First, the impacts of alternative City Logistics solutions, such as off-peak deliveries and access restrictions are investigated. Then, the developed modeling framework is extended to investigate a crowdsourced service for parcel deliveries. The effects on traffic and emissions are investigated for the adoption of crowdshipping by carriers delivering parcels in the city center of Rome, Italy. The externalities associated with several strategic (chosen mode) and operational (detour length, parking behavior, and traffic conditions) aspects of this service are analyzed by means of simulation in realistic settings. Some results allow preliminary considerations about the effects of last-mile delivery solution that can been confirmed in other studies. Other findings, instead, are in line with studies from previous literature that adopted different approaches. The practice of off-peak deliveries, consisting in shifting part of the trips and operations to less congested hours of the day (typically evening and night) has proved to be an effective solution to freight-related congestion in urban settings. Restricting from deliveries specific links or sets of links, instead, could be beneficial only in some situations. Alternative crowdshipping implementation features, such as the transportation mode choice, but also operational aspects (such as availability of parking, optimization of existing trips, and implementation during off-peak hours) can also considerably influence the final traffic and emissions impacts of this service.Civil, Architectural, and Environmental Engineerin

Large-time behavior of some numerical schemes: application to the sonic-boom phenomenon

In this thesis we highlight the necessity of employing numerical schemes that preserve the large-time dynamical properties of the continuous system. We focus on Burgers- like equations, which are well known to develop N-waves as intermediate or asymptotic profiles. As we show, not only forward simulations can be distorted; the efficiency of solutions of optimization and inverse design problems might be affected too. In particular, we apply our results to the case of the prediction and control of the sonic- boom phenomenon, modeled by the augmented Burgers equation

Contribution à l'étude du trafic routier sur réseaux à l'aide des équations d'Hamilton-Jacobi

This work focuses on modeling and simulation of traffic flows on a network. Modeling road traffic on a homogeneous section takes its roots in the middle of XXth century and it has generated a substantial literature since then. However, taking into account discontinuities of the network such as junctions, has attracted the attention of the scientific circle more recently. However, these discontinuities are the major sources of traffic congestion, recurring or not, that basically degrades the level of service of road infrastructure. This work therefore aims to provide a unique perspective on this issue, while focusing on scale problems and more precisely on microscopic-macroscopic passage in existing models. The first part of this thesis is devoted to the relationship between microscopic car-following models and macroscopic continuous flow models. The asymptotic passage is based on a homogenization technique for Hamilton-Jacobi equations. In a second part, we focus on the modeling and simulation of vehicular traffic flow through a junction. The considered macroscopic model is built on Hamilton-Jacobi equations as well. Finally, the third part focuses on finding analytical or semi-analytical solutions, through representation formulas aiming to solve Hamilton-Jacobi equations under adequate assumptions. In this thesis, we are also interested in a generic class of second order macroscopic traffic flow models, the so-called GSOM modelsCe travail porte sur la modélisation et la simulation du trafic routier sur un réseau. Modéliser le trafic sur une section homogène (c'est-à-dire sans entrée, ni sortie) trouve ses racines au milieu du XXème siècle et a généré une importante littérature depuis. Cependant, la prise en compte des discontinuités des réseaux comme les jonctions, n'a attiré l'attention du cercle scientifique que bien plus récemment. Pourtant, ces discontinuités sont les sources majeures des congestions, récurrentes ou non, qui dégradent la qualité de service des infrastructures. Ce travail se propose donc d'apporter un éclairage particulier sur cette question, tout en s'intéressant aux problèmes d'échelle et plus particulièrement au passage microscopique-macroscopique dans les modèles existants. La première partie de cette thèse est consacrée au lien existant entre les modèles de poursuite microscopiques et les modèles d'écoulement macroscopiques. Le passage asymptotique est assuré par une technique d'homogénéisation pour les équations d'Hamilton-Jacobi. Dans une deuxième partie, nous nous intéressons à la modélisation et à la simulation des flux de véhicules au travers d'une jonction. Le modèle macroscopique considéré est bâti autour des équations d'Hamilton-Jacobi. La troisième partie enfin, se concentre sur la recherche de solutions analytiques ou semi-analytiques, grâce à l'utilisation de formules de représentation permettant de résoudre les équations d'Hamilton-Jacobi sous de bonnes hypothèses. Nous nous intéressons également dans cette thèse, à la classe générique des modèles macroscopiques de trafic de second ordre, dits modèles GSO

Snapshot-Based Methods and Algorithms

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science