Browse ORBi

- What it is and what it isn't
- Green Road / Gold Road?
- Ready to Publish. Now What?
- How can I support the OA movement?
- Where can I learn more?

ORBi

On characterizing the relationship between route choice behaviuor and optimal traffic control solution space Rinaldi, Marco ; ; Viti, Francesco in Transportation Research. Part B : Methodological (2017) Explicitly including the dynamics of users' route choice behaviour in optimal traffic control applications has been of interest for researchers in the last five decades. This has been recognized as a very ... [more ▼] Explicitly including the dynamics of users' route choice behaviour in optimal traffic control applications has been of interest for researchers in the last five decades. This has been recognized as a very challenging problem, due to the added layer of complexity and the considerable non-convexity of the resulting problem, even when dealing with simple static assignment and analytical link cost functions. In this work we establish a direct behavioural connection between the different shapes and structures emerging in the solution space of such problems and the underlying route choice behaviour. We specifically investigate how changes in the active equilibrium route set exert direct influence on the solution space's structure and behaviour. Based on this result, we then formulate and validate a constrained version of the original problem, yielding desirable properties in terms of solution space regularity. © 2017. [less ▲] Detailed reference viewed: 75 (3 UL)Exact and approximate route set generation for resilient partial observability in sensor location problems Rinaldi, Marco ; Viti, Francesco in Transportation Research. Part B : Methodological (2017), 105 Sensor positioning is a fundamental problem in transportation networks, as the location of sensors strongly determines how traffic flows are observable and hence manageable. This paper aims to develop a ... [more ▼] Sensor positioning is a fundamental problem in transportation networks, as the location of sensors strongly determines how traffic flows are observable and hence manageable. This paper aims to develop a methodology to determine sensor locations on a network such that an optimal trade-off solution is found between the amount of sensors installed and the resilience of the sensor set. In particular, we propose exact and heuristic solutions for identifying the optimal route sets such that no other route would include any additional information for finding optimal full and partial observability solutions. This is an important contribution to sensor location problems, as route-based link flow inference problems have non-unique solutions, strongly depending on the used link-route information. The properties of the new methodology are analyzed and illustrated through different case studies, and the advantages of the algorithms are quantified both for full and for partial observability solutions. Due to the route sets found by our approach, we are able to find full observability solutions characterized by a small number of sensors, while yet being efficient also in terms of partial observability. We perform validation tests on both small and real-life sized network instances. © 2017 Elsevier Ltd [less ▲] Detailed reference viewed: 95 (3 UL)An extended coordinate descent method for distributed anticipatory network traffic control Rinaldi, Marco ; in Transportation Research. Part B : Methodological (2015), 80 Anticipatory optimal network control can be defined as the practice of determining the set of control actions that minimizes a network-wide objective function, so that the consequences of this action are ... [more ▼] Anticipatory optimal network control can be defined as the practice of determining the set of control actions that minimizes a network-wide objective function, so that the consequences of this action are taken in consideration not only locally, on the propagation of flows, but globally, taking into account the user's routing behavior. Such an objective function is, in general, defined and optimized in a centralized setting, as knowledge regarding the whole network is needed in order to correctly compute it. This is a strong theoretical framework but, in practice, reaching a level of centralization sufficient to achieve said optimality is very challenging. Furthermore, even if centralization was possible, it would exhibit several shortcomings, with concerns such as computational speed (centralized optimization of a huge control set with a highly nonlinear objective function), reliability and communication overhead arising.The main aim of this work is to develop a decomposed heuristic descent algorithm that, demanding the different control entities to share the same information set, attains network-wide optimality through separate control actions. © 2015 Elsevier Ltd. [less ▲] Detailed reference viewed: 58 (1 UL)Assessing partial observability in network sensor location problems Viti, Francesco ; ; et al in Transportation Research. Part B : Methodological (2014), 70 The quality of information on a network is crucial for different transportation planning and management applications. Problems focusing on where to strategically extract this information can be broadly ... [more ▼] The quality of information on a network is crucial for different transportation planning and management applications. Problems focusing on where to strategically extract this information can be broadly subdivided into observability problems, which rely on the topological properties of the network, and flow-estimation problems, where (prior) information on observed flows is needed to identify optimal sensor locations. This paper contributes mainly to the first category: more specifically, it presents a new methodology and an intuitive metric able to quantify the quality of a solution in case of partial observability, i.e. when not all flow variables are observed or can be uniquely determined from the observed flows. This methodology is based on existing approaches that can efficiently find solutions for full observability (i.e., the set of sensors needed to make the system fully determined), and exploits only the algebraic relations between link, route and origin-destination flow variables to quantify the information contained in any arbitrary subset of these variables. The new metric allows, through its adoption within simple search algorithms, to efficiently select sensor locations when the number of available sensors is limited by, for example, budget constraints and is less than the number needed to guarantee full observability. The chosen positions aim at selecting those locations that contain the largest information content on the whole network. This is an important contribution in this field, since even in small sized networks the solution for full observability requires an exceedingly large amount of sensors. The assessment of partial observability solutions, based on explicit route enumeration, allows one to categorize families of full observability solutions, and shows that these contain different information potential. This way, it is possible to rank solutions requiring a lower number of sensors while containing the same information content. We tested this new methodology both on toy networks, in order to analyse the properties of the metric and illustrate its logic, and to explain and test heuristic search algorithms for optimal sensor positioning on a real-sized network. Analysis of partial observability solutions shows that the basic search algorithms succeed in finding the links that contain the largest deal of information in a network. [less ▲] Detailed reference viewed: 123 (8 UL) |
||