Penetration effect of connected and automated vehicles on cooperative on‐ramp merging

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166263/1/itr2bf00795.pd

Traffic Optimization at Junctions to Improve Vehicular Flows

The aim of this work is to improve urban traffic viability through an appropriate choice of yielding and stop signs or red and green phases for traffic lights in junctions with two entering and one exiting roads (junctions of 2×1 type). We consider a macroscopic fluid-dynamic model able to capture the traffic evolution. We analyze different functionals measuring networks performance in terms of average velocity, average traveling time, total flux, density, stop and go waves, average traveling time, weighted with the number of cars moving on roads, and kinetic energy. Right of way parameters which optimize the latter two functionals are obtained. Simulations of simple junctions of 2×1type have been used to test the correctness of the analytical results. Then, global performance of optimization procedures has been investigated on Re di Roma Square, in Italy. In particular, we discuss cases in which the functionals are optimized locally at each junction for different values of right of way parameters. We show that for the chosen initial data the only algorithm for the maximization of velocity assures globally the best performance for the network, also in terms of average traveling times and kinetic energy

Forecast based traffic signal coordination using congestion modelling and real-time data

This dissertation focusses on the implementation of a Real-Time Simulation-Based Signal Coordination module for arterial traffic, as proof of concept for the potential of integrating a new generation of advanced heuristic optimisation tools into Real-Time Traffic Management Systems. The endeavour represents an attempt to address a number of shortcomings observed in most currently marketed on-line signal setting solutions and provide better adaptive signal timings. It is unprecedented in its use of a Genetic Algorithm coupled with Continuous Dynamic Traffic Assignment as solution evaluation method, only made possible by the recently presented parallelisation strategies for the underlying algorithms. Within a fully functional traffic modelling and management framework, the optimiser is developed independently, leaving ample space for future adaptations and extensions, while relying on the best available technology to provide it fast and realistic solution evaluation based on reliable real-time supply and demand data. The optimiser can in fact operate on high quality network models that are well calibrated and always up-to-date with real-world road conditions; rely on robust, multi-source network wide traffic data, rather than being attached to single detectors; manage area coordination using an external simulation engine, rather than a na¨ıve flow propagation model that overlooks crucial traffic dynamics; and even incorporate real-time traffic forecast to account for transient phenomena in the near future to act as a feedback controller. Results clearly confirm the efficacy of the proposed method, by which it is possible to obtain relevant and consistent corridor performance improvements with respect to widely known arterial bandwidth maximisation techniques under a range of different traffic conditions. The computational efforts involved are already manageable for realistic real-world applications, and future extensions of the presented approach to more complex problems seem within reach thanks to the load distribution strategies already envisioned and prepared for in the context of this work

Mathematical Model and Cloud Computing of Road Network Operations under Non-Recurrent Events

Optimal traffic control under incident-driven congestion is crucial for road safety and maintaining network performance. Over the last decade, prediction and simulation of road traffic play important roles in network operation. This dissertation focuses on development of a machine learning-based prediction model, a stochastic cell transmission model (CTM), and an optimisation model. Numerical studies were performed to evaluate the proposed models. The results indicate that proposed models are helpful for road management during road incidents

Multiscale control of generic second order traffic models by driver-assist vehicles

We study the derivation of generic high order macroscopic traffic models from a follow-the-leader particle description via a kinetic approach. First, we recover a third order traffic model as the hydrodynamic limit of an Enskog-type kinetic equation. Next, we introduce in the vehicle interactions a binary control modelling the automatic feedback provided by driver-assist vehicles and we upscale such a new particle description by means of another Enskog-based hydrodynamic limit. The resulting macroscopic model is now a Generic Second Order Model (GSOM), which contains in turn a control term inherited from the microscopic interactions. We show that such a control may be chosen so as to optimise global traffic trends, such as the vehicle flux or the road congestion, constrained by the GSOM dynamics. By means of numerical simulations, we investigate the effect of this control hierarchy in some specific case studies, which exemplify the multiscale path from the vehicle-wise implementation of a driver-assist control to its optimal hydrodynamic design.Comment: 22 pages, 3 figure

Distributed, decentralised and compensational mechanisms for platoon formation

Verkehrsprobleme nehmen mit der weltweiten Urbanisierung und der Zunahme der Anzahl der Fahrzeuge pro Kopf zu. Platoons, eine Formation von eng hintereinander fahrenden Fahrzeugen, stellen sich als mögliche Lösung dar, da bestehende Forschungen darauf hinweisen, dass sie zu einer besseren Straßenauslastung beitragen, den Kraftstoffverbrauch und die Emissionen reduzieren und Engpässe schneller entlasten können. Rund um das Thema Platooning gibt es viele Aspekte zu erforschen: Sicherheit, Stabilität, Kommunikation, Steuerung und Betrieb, die allesamt notwendig sind, um den Einsatz von Platooning im Alltagsverkehr näher zu bringen. Während in allen genannten Bereichen bereits umfangreiche Forschungen durchgeführt wurden, gibt es bisher nur wenige Arbeiten, die sich mit der logischen Gruppierung von Fahrzeugen in Platoons beschäftigen. Daher befasst sich diese Arbeit mit dem noch wenig erforschten Problem der Platoonbildung, wobei sich die vorhandenen Beispiele mit auf Autobahnen fahrenden Lastkraftwagen beschäftigen. Diese Fälle befinden sich auf der strategischen und taktischen Ebene der Planung, da sie von einem großen Zeithorizont profitieren und die Gruppierung entsprechend optimiert werden kann. Die hier vorgestellten Ansätze befinden sich hingegen auf der operativen Ebene, indem Fahrzeuge aufgrund der verteilten und dezentralen Natur dieser Ansätze spontan und organisch gruppiert und gesteuert werden. Dadurch entstehen sogenannte opportunistische Platoons, die aufgrund ihrer Flexibilität eine vielversprechende Voraussetzung für alle Netzwerkarte bieten könnten. Insofern werden in dieser Arbeit zwei neuartige Algorithmen zur Bildung von Platoons vorgestellt: ein verteilter Ansatz, der von klassischen Routing-Problemen abgeleitet wurde, und ein ergänzender dezentraler kompensatorischer Ansatz. Letzteres nutzt automatisierte Verhandlungen, um es den Fahrzeugen zu erleichtern, sich auf der Basis eines monetären Austausches in einem Platoon zu organisieren. In Anbetracht der Tatsache, dass alle Verkehrsteilnehmer über eine Reihe von Präferenzen, Einschränkungen und Zielen verfügen, muss das vorgeschlagene System sicherstellen, dass jede angebotene Lösung für die einzelnen Fahrzeuge akzeptabel und vorteilhaft ist und den möglichen Aufwand, die Kosten und die Opfer überwiegt. Dies wird erreicht, indem den Platooning-Fahrzeugen eine Form von Anreiz geboten wird, im Sinne von entweder Kostensenkung oder Ampelpriorisierung. Um die vorgeschlagenen Algorithmen zu testen, wurde eine Verkehrssimulation unter Verwendung realer Netzwerke mit realistischer Verkehrsnachfrage entwickelt. Die Verkehrsteilnehmer wurden in Agenten umgewandelt und mit der notwendigen Funktionalität ausgestattet, um Platoons zu bilden und innerhalb dieser zu operieren. Die Anwendbarkeit und Eignung beider Ansätze wurde zusammen mit verschiedenen anderen Aspekten untersucht, die den Betrieb von Platoons betreffen, wie Größe, Verkehrszustand, Netzwerkpositionierung und Anreizmethoden. Die Ergebnisse zeigen, dass die vorgeschlagenen Mechanismen die Bildung von spontanen Platoons ermöglichen. Darüber hinaus profitierten die teilnehmenden Fahrzeuge mit dem auf verteilter Optimierung basierenden Ansatz und unter Verwendung kostensenkender Anreize unabhängig von der Platoon-Größe, dem Verkehrszustand und der Positionierung, mit Nutzenverbesserungen von 20% bis über 50% im Vergleich zur untersuchten Baseline. Bei zeitbasierten Anreizen waren die Ergebnisse uneinheitlich, wobei sich der Nutzen einiger Fahrzeuge verbesserte, bei einigen keine Veränderung eintrat und bei anderen eine Verschlechterung zu verzeichnen war. Daher wird die Verwendung solcher Anreize aufgrund ihrer mangelnden Pareto-Effizienz nicht empfohlen. Der kompensatorische und vollständig dezentralisierte Ansatz weißt einige Vorteile auf, aber die daraus resultierende Verbesserung war insgesamt vernachlässigbar. Die vorgestellten Mechanismen stellen einen neuartigen Ansatz zur Bildung von Platoons dar und geben einen aussagekräftigen Einblick in die Mechanik und Anwendbarkeit von Platoons. Dies schafft die Voraussetzungen für zukünftige Erweiterungen in der Planung, Konzeption und Implementierung effektiverer Infrastrukturen und Verkehrssysteme.Traffic problems have been on the rise corresponding with the increase in worldwide urbanisation and the number of vehicles per capita. Platoons, which are a formation of vehicles travelling close together, present themselves as a possible solution, as existing research indicates that they can contribute to better road usage, reduce fuel consumption and emissions and decongest bottlenecks faster. There are many aspects to be explored pertaining to the topic of platooning: safety, stability, communication, controllers and operations, all of which are necessary to bring platoons closer to use in everyday traffic. While extensive research has already made substantial strides in all the aforementioned fields, there is so far little work on the logical grouping of vehicles in platoons. Therefore, this work addresses the platoon formation problem, which has not been heavily researched, with existing examples being focused on large, freight vehicles travelling on highways. These cases find themselves on the strategic and tactical level of planning since they benefit from a large time horizon and the grouping can be optimised accordingly. The approaches presented here, however, are on the operational level, grouping and routing vehicles spontaneously and organically thanks to their distributed and decentralised nature. This creates so-called opportunistic platoons which could provide a promising premise for all networks given their flexibility. To this extent, this thesis presents two novel platoon forming algorithms: a distributed approach derived from classical routing problems, and a supplementary decentralised compensational approach. The latter uses automated negotiation to facilitate vehicles organising themselves in a platoon based on monetary exchanges. Considering that all traffic participants have a set of preferences, limitations and goals, the proposed system must ensure that any solution provided is acceptable and beneficial for the individual vehicles, outweighing any potential effort, cost and sacrifices. This is achieved by offering platooning vehicles some form of incentivisation, either cost reductions or traffic light prioritisation. To test the proposed algorithms, a traffic simulation was developed using real networks with realistic traffic demand. The traffic participants were transformed into agents and given the necessary functionality to build platoons and operate within them. The applicability and suitability of both approaches were investigated along with several other aspects pertaining to platoon operations such as size, traffic state, network positioning and incentivisation methods. The results indicate that the mechanisms proposed allow for spontaneous platoons to be created. Moreover, with the distributed optimisation-based approach and using cost-reducing incentives, participating vehicles benefited regardless of the platoon size, traffic state and positioning, with utility improvements ranging from 20% to over 50% compared to the studied baseline. For time-based incentives the results were mixed, with the utility of some vehicles improving, some seeing no change and for others, deteriorating. Therefore, the usage of such incentives would not be recommended due to their lack of Pareto-efficiency. The compensational and completely decentralised approach shows some benefits, but the resulting improvement was overall negligible. The presented mechanisms are a novel approach to platoon formation and provide meaningful insight into the mechanics and applicability of platoons. This sets the stage for future expansions into planning, designing and implementing more effective infrastructures and traffic systems

Evacuation planning under selfish evacuation routing

In case of an evacuation a large number of evacuees must be routed through a street network to let them leave the endangered area and reach safe places. In such a situation a lot of evacuees use the street network in a short time span and so the network capacity will be insufficient. With an evacuation plan the traffic could be guided through the network for a better use of network capacity. But to implement the solution planned by a central decision maker, optimal routes must be communicated to all network users, which lead to a high communication effort. Furthermore, it must be ensured that the evacuees take the given routes. But a lot of people do not follow the instructions from authorities in a panic situation. They do what they assume is best for themselves. Such selfish behaviour leads to a suboptimal distribution of traffic and results in congestion. In this thesis we present a concept to guide the evacuees through the network without determining optimal routes for all network users. With the blockage of street sections we force the evacuees to use other routes than the preferred ones but give them the possibility to choose their routes on their own. The thesis presents different mathematical model formulations and heuristic for the described problem. In a comprehensive computational study, with real world examples, the functionality of the presented concept and methods are tested

Analysis of right-turn lane length in left-hand traffic countries at signalised intersections of urban roads

Analysis of the right turn lane length of urban roads in left-hand traffic countries, such as Australia, UK and India (left-turn lane length in right-hand traffic countries such as USA), at signalised intersections encounters two main geometric features namely, deceleration length and storage length. The literature shows that in routine practice, the deceleration length is generally estimated by using constant deceleration rate. Many researchers consider this assumption for all design speeds unrealistic as it does not reflect the influence of the pavement condition. Hence, it may be desirable to consider the pavement’s condition in terms of its longitudinal coefficient of friction in the design analysis. In regard to the storage length, a large number of the current guidelines and models estimate the storage length of right-turn lane at signalised intersections under split phase. Hence, there is a need to examine other phase types and timings and integrate the signal timing as a part of the geometric design In this thesis, two analytical expressions have been analysed for the design of deceleration length. The first expression assumes a constant deceleration rate, and the second expression employs the concept of forces on a rotating wheel in which the coefficient of longitudinal friction between a vehicle’s tyres and the road surface is considered. The calculated deceleration lengths by these two expressions were compared with the recommended values in American and Australian standards as well as with the deceleration lengths that were obtained by a recent simulation study presented in the literature. It has been found that applying a constant deceleration rate of 2.74 m/s2 in the first expression provides the values of deceleration length comparable to most guidelines and studies. The second expression highlights the importance of using the pavement design in terms of the coefficient of friction to reduce the deceleration length in the case of limited space. A MATLAB based simulation programme has been developed to provide an estimate of the right-turn lane storage length for different traffic volumes in order to avoid the problems associated with blocking and overflow of right turn vehicles in 95% of cycles. In established intersections that cannot be modified due to physical constraints, the model is flexible enough to examine different signal phase types and timings and provides other solutions to reduce overflow and/or blockage situations. The simulation model also takes into consideration the leftover queue. The model results have been compared against an available analytical method in which similar signal phases and timings were investigated. The outcomes are similar to those of the analytical model in most of the signal phase types. The simulation model provides the flexibility to estimate the right-turn lane length for different combinations of through lane and right-turn lane traffic volumes. The developed simulation model has also been validated against the field data using three parameters, namely 95th percentile of maximum queue, overflow cycle percentage, and blockage cycle percentage. Comparing with the field observations yields a level of accuracy in the range of 78%-85%. Finally this simulation model has been used to optimise the green time in the case of split phase that demonstrates a large difference in traffic volumes of two opposite approaches; this could reduce the mean wait time by up to 28%