Potier, A. Turel, J. Transport Policy: the European Laboratory; P. Jones, P. Meersman, E. Van de Voorde. Finland: Mobility on the Top of Europe; L. Hilska, V. Heidemann, U. Kunert, D. Salomon, E. Italy: Transport along the Peninsula; G. De Sole, M. Korver, G. Jansen, P. Norway: Crossing Fjords and Mountains; A. Hervik, T.
Tretvik, L. Sweden: Moving towards a Safer Environment; K. Switzerland: Neutrality at the Center of Europe; R. Maggi, M. Mentes, A. Turel, T. Appendix A: Currency Exchange Table Appendix B: Purchasing Power Parities In Stock. Capital in the Twenty-First Century. Breaking the Sheep's Back. Australia's Welfare Wars The players, the politics and the ideologies. Market Society History, Theory. Europe, Austerity and the Threat to Global Stab This Changes Everything Capitalism vs. View Wishlist. Our Awards Booktopia's Charities.
Are you sure you would like to remove these items from your wishlist? The first one comes from the forest industry and concerns the location of logging camps for workers. The second one focuses on the location of vehicle inspection facilities, taking into account the allocation of patrols.
The third one is a facility location problem for an express package delivery company. His research interests focus on the optimization of logistics and transportation networks. Given a graph with a partition of its vertex set into several clusters , one wants to select one vertex per cluster such that the chromatic number of the subgraph induced by the selected vertices is minimum. This problem appeared in the literature under different names for specific models. Here, I will describe different models -- some already discussed in previous papers and some new ones -- in very different contexts under a unified framework based on this graph problem.
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Each model motivates the problem in some graph classes and I will discuss the related complexity in these classes. I will also conclude by introducing the maximum version of the problem. This talk covers recent papers co-authored with T. Ekim Bogazici University, Istanbul , J. Ries University of Fribourg , C. Pop University of Baia Mare, Romania. During his career he has taught a large range of topics in Computer Science, Operational Research and Discrete Mathematics.
His research interests, in Combinatorial Optimisation, are centred around the notion of efficient algorithms with performance guarantees, mainly polynomial approximation, complexity theory, algorithmic graph theory, online algorithms and inverse combinatorial optimisation. He is co author of more than 50 papers in international journals or book chapters. We focus on the case where g is not available in closed form and can only be evaluated at a given point by running a long simulation process. The results of interest are prices formed from the gradient of g. It is assumed that the function g is convex or can be reasonably approximated by a convex one.
We choose to use an approximation of g defined as a pointwise supremum over a family of piecewise affine functions. This part of the procedure is carried out offline, and uses evaluations of g to define the approximation from its epigraph. We report on using the Moreau-Yosida regularization on our approximation function to return a smoothed value of the gradient that reduces the volatility in the prices. We outline some results in the context of a reserve energy market planning problem. His research interests include the applications of complementarity theory and variational inequalities, in particular for the simulation and control of physical systems.
The price of parking is a direct cost of driving and a market based pricing policy that can efficiently manage transportation demand. In particular, variable pricing when applied to parking can have great potential, just as it has been successfully shown to manage demand through congestion pricing or peak period tolling. Understanding the impact of parking pricing on transportation and parking behavior is critical for determining the type of pricing structure that is most effective for managing demand and scarce land resources, reducing externalities, yet at the same time, generating adequate economic revenue.
This study examines parking pricing impact with the consideration of various payment type, parking location, transit incentives, flexibility of work schedule, income, and walking time at the University of California, Berkeley. A discrete choice experiment was designed to analyze changes in transportation and parking behavior under various parking pricing scenarios using revealed and stated preferences data. Her recent research focuses on the evaluation of transportation demand management measures, including parking pricing, and their impact on travel demand and behavior.
Elisabetta Cherchi DTU, Lyngby, Denmark Measuring the effect of social conformity in individuals' preference for electric vehicles October 23, , , Abstract: According to Crutchfield individuals consciously or unconsciously tend to "yield to group pressures" and consequently to act in agreement to the majority position.
Social conformity has been extensively studied in psychology with also several applications to transport problems. Field experiments are typically used to evaluate the impact of social influence on self-reported changes toward environmentally sustainable transport behaviours.
In this research, we discuss various aspects of social conformity and present a stated preference experiment set up to measure their effect on individual preferences. The choice of electric cars is used as an illustrative example. In particular, we explicitly measure how individuals' preference change before and after they have received social information on other's experience about driving range, about the need to adapt the activity schedule and about the benefit of parking policies. The effect of descriptive norm and other-signalling concern are also measured as part of the stated preference experiment, while injunctive norms are measured with typical statements on a 7-point Likert scale.
Results from the estimation of mixed logit model and hybrid choice models, clearly confirms that the experience especially negative of other people has a powerful effect on individual preferences for range and parking policies. Results also confirm that individuals' behaviour is affected by the image they want other people to have of them, making them "more honest" in their answers.
Her research interest is in data collection, in the behavioural background of demand modelling and in how to use and expand it to study emerging problems such as understanding what drives sustainable transport behaviour and how it can be promoted. Angelo Guevara Universidad de los Andes, Santiago, Chile Detecting and Modelling the Decoy Effect in Transportation October 09, , , Abstract: Empirical evidence suggests that, under some circumstances, the introduction of a new option in a choice-set can increase the choice probability of other alternatives.
This result, known as the decoy effect, defies the basic regularity assumption, which is at the root of standard models of choice that are based on a compensatory approach under the Random Utility Maximization RUM framework. The goal of this research was threefold. First, we worked toward the development of a practical probabilistic choice-model that could account for the decoy effect, building upon various types of choice behaviors that that been described in cognitive psychology.
Then, we used the proposed choice model to study, with Monte-Carlo simulation, the power of different statistical tests for detecting the presence of this phenomenon. Finally, we designed and applied a Stated Preferences SP survey to detect and to characterize the decoy effect in route choice. Results of this research showed first that all the decoy effect types that have been described in the literature, can be replicated by the Random Regret Minimization RRM discrete-choice model. Regarding statistical testing for the presence of the decoy effect, we found that McNemar and Proportions tests showed larger power when the effect size was modeled as RRM.
Finally, four conclusions were driven from the application of the SP survey. The first was that the decoy effect was present in route choice, but that it was hard to detect it in the context of commuting trips or when alternatives were far from the true trade-off line. The second result of the SP experiment was that the magnitude of the average sample effect obtained from it was coherent with a data generation process based on the RRM model.
Third, the SP survey showed that the larger decoys found were of the compromise type, and that the more robust ones were those of the range type. Finally, the SP survey indicated that, although an emergent-values Logit model showed slightly better fit, the RRM had substantially superior performance in outer-sample forecasting. This final result suggests that the RRM does capture, to some extent, the underlying behavior that is causing the decoy effect, but that this choice-model may still be somehow incomplete for this purpose.
Four future steps of this line of research can be identified. The first is to improve the RRM model. The second step corresponds to the design and application of a Revealed Preference RP experiment to detect the decoy effect in real transportation behavior. The next, is to deepen the analysis of the circumstances under which the decoy effect occurs.
The final step corresponds to the study of possible transportation public policies that can benefit from the decoy effect, such as seated-only buses to favor the use of public transportation or different pricing strategies. Short bio: C. His main research interest is in the modeling of choice behavior, with recent contributions on endogeneity, sampling of alternatives, behavioral economics.
One of them presented a convex mixed integer formulation that could be implemented in a Branch and Bound algorithm. This work presents techniques to improve the performance of the algorithm in order to implement this formulation. After, we present a mathematical programming model for the problem of covering solids by spheres of different radii. Given a set of spheres, possibly with different diameters, and a solid, the goal is to locate the spheres in such a way their union forms a coverage for this solid, using the smallest possible number of spheres of this set.
This problem has an application in the radio-surgical treatment planning known as Gamma Knife and can be formulated as a non-convex optimization problem with quadratic constraints and a linear objective function. Yoram Shiftan Technion, Israel The future of activity based models and their contribution to policy making April 20, , , Abstract: Activity-based models are the new generation of travel demand models. These models treat travel as being derived from the demand for personal activities. The explicit modelling of activities and the consequent tours and trips enables a better understanding of travel behaviour and more credible analysis of response to policies and their effect on traffic and air quality.
These models have various advantages in support of transport project evaluation by being able to provide detailed disaggregate individual and vehicle activity output that can improve our analysis of emissions and provide various accessibility measures important for equity and other economic evaluation. This presentation will demonstrate these various advantages for policy-making and discuss future challenges in using these models to forecast the impact of new transportation services and technologies promoting sustainable. Short bio: Yoram Shiftan is a Professor of Civil and Environmental Engineering in the Technion, where he teaches and conducts research in travel behavior with a focus on activity-based modeling and response to policies, the complex relationships between transport, the environment and land use, transport economics and project evaluation.
Shiftan received his Ph. The case where users are assigned to cheapest paths, which is naturally formulated as an NP-hard bilevel program, has been extensively studied and will serve as the background for an extension where user assignment is performed according to a discrete choice model of the logit family. Following a description of the model and its theoretical properties, we develop an algorithmic framework for determining a near-optimal solution of this nonconvex problem, based on a variety of approximations involving mixed integer programs, either linear or quadratic.
Through a battery of tests performed on a variety of network topologies, we reach the conclusion that very crude approximations that scale well perform surprisingly well.
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Short bio: Professor at the department of computer science and operations research of the University of Montreal, Patrice Marcotte has published over 80 articles related to network design, variational inequalities, bilevel programming, network pricing and revenue management, traffic assignment, and badminton. He his also the author of two guides and a large website devoted to cycling, and currently sits on the editorial board of the following journals: Operations Research, Transportation Science, Journal of Optimization Theory and Applications, Operations Research Letters, European Journal of Combinatorial Optimization.
Asad Lesani Mcgill University Towards a WIFI-Bluetooth system for traffic monitoring in different transportation facilities October 30, , , Abstract: Intelligent transportation systems depend on technologies to obtain valuable road metrics, such as travel times, speeds, and volumes. Novel ways of collecting anonymous data from road users across multiple modes are becoming more recognized in literature and industry. Bluetooth detectors have been widely researched as a way of detecting smartphones and vehicles while maintaining anonymous identity across multiple detection sites.
This paper proposes a smartphone detection system using wireless Internet WIFI signatures from mobile devices in a similar way to Bluetooth, but with a higher detection rate due to the higher usage of WIFI over Bluetooth. Short bio: Asad Lesani completed his M. Sc and B. Prof Vinayak V. This presentation provides an overview of my current work on the use of Experimental Economics in understanding behaviour with respect to interactions of risk attitudes and subjective beliefs on crash propensity, route choice and information, and finally evaluating policies in emergency management.
Experimental economics has been used intermittently since the s to conduct controlled experiments to evaluate policies, but recently has gained significant interest to test theories. The presentation will also present trends, strengths and pitfalls of these methods. Miranda-Moreno Department of Civil Engineering, McGill University A smartphone-based system for collecting and analyzing route GPS data coming from motorized and non-motorized road users July 22, , , Abstract: The seminar presents the current development of a smartphone-based system for collecting and analyzing route GPS data coming from cyclists and drivers routes.
Using GPS functionality on Android and iOS smartphones to log route data, a large database containing thousands of trips is collected in a short period of time after a mass-media campaign in Canadian cities. For motorists, a platform is built for mapping traffic congestion using link-level indicators such as speeds or travel times, speed differentials, etc.
Work in progress is discussed at the end of this presentation. His specialty is in transportation safety, data collection and monitoring methods and technologies, and sustainable transport strategies. His research interests include the development of crash-risk analysis methods, the development and integration of systems for traffic monitoring, the impact of climate on mobility, energy efficiency measures and non-motorized transportation.
Mohammad Yousef Maknoon Polytechnique Montreal Scheduling cross-docks in transportation network July 03, , , Abstract: Cross-dock is a center that transships freight between trucks with minimal usage of storage in between. Cross-docking reclaims transportation efficiency by bundling arriving freight into full truckloads. Cross docks are beneficial as long as they are well coordinated with transportation plans when their operational cost does not overwhelm their savings in inventory.
In this talk, I present scheduling problems at macro and micro level and show variety of models to address their issues. His research focuses on scheduling and optimization in transportation network. He completed his Master and Ph. Song Gao University of Massachusetts Amherst Route Choice in an Uncertain Environment: Algorithms and Behavioral Studies May 28, , , Abstract: Transportation systems are inherently uncertain due to disruptions such as bad weather and incident, and the randomness of traveler' choices.
Real-time information allows travelers to adapt to actual traffic conditions and potentially mitigate the adverse effect of uncertainty. Both algorithmic and behavioral studies of adaptive routing are presented. A series of optimal adaptive routing problems are investigated, where time-dependent travel times are modeled as correlated random variables and various assumptions on the real-time information accessibility are made.
Behavioral studies of adaptive route choice in both one-shot and day-to-day learning contexts based on stated preferences data show that travelers can plan ahead for traffic information not yet available. Two modeling paradigms for route choice under unreliable travel times, utility maximization based on the prospect theory and non-compensatory heuristic, are compared. The non-compensatory heuristic is found to be potentially a suitable alternative to the conventional utility maximization approach.
The ongoing work of developing a history-dependent route choice learning model for realistic networks is also discussed. Gao's research focuses on optimization in stochastic networks, econometric and psychological models of travel behavior, equilibrium analysis of stochastic networks with traveler information, with applications in intelligent transportation systems ITS , transportation planning under both normal and emergency conditions, and sustainable transportation systems. Prior to joining the faculty of the University of Massachusetts Amherst in , Dr.
Gao worked as a transportation engineer at Caliper Corporation, Newton, MA for three years, and developed advanced traffic assignment modules for TransCAD, a GIS-based transportation planning software and provided consultancy to transportation demand forecasting projects of state, regional and local planning agencies. She is on the editorial board of the Journal of Intelligent Transportation Systems. Gao received her Ph. She received her B. Sofia Kalakou Instituto Superior Tecnico, Lisbon, Portugal From passenger route choice models to airport flexibility November 08, , , Abstract: In spite of the transport mode, all the travellers are primarily pedestrians.
Transport terminals are considered as infrastructure planned for pedestrians and capable of employing tools that will let them respond with flexibility and efficiency to future challenges. It is suggested that pedestrian flows should have an active role in the definition of the flexibility of a transport building configuration and that pedestrian behavior should be integrated in this process at an early stage. This talk aims to present some preliminary thoughts on the structure of passenger route choice models for an airport building and the way that they can be used in airport flexibility analysis.
Travel time, wayfinding, space characteristics and available free time are important for passenger route choices and pillar sources for the specification of passenger route choice models. This combination allows us to explore any latent relationships between space characteristics, route choices and flows of passengers, to model more efficiently pedestrian route choices and to designate the properties of efficient terminal configurations. In terms of planning policy and flexibility, it gives some indications for the value of each area as derived from the way the passengers perceive it and the value they add to it.
In this way route preferences can be incorporated in flexibility analysis as inputs that have the potential to indicate areas that are often preferred. Her research project deals with flexibility of airport passenger buildings. In her thesis projects she evaluated the performance of Greek airports with Data Envelopment Analysis NTUA and she developed a pedestrian model to simulate passenger movements in Lisbon Portela airport and evaluate the airport processes IST.
Her research interests focus on transport terminal planning and management, non-motorized transportation, behavior and activity models and operations research. To maximize revenue, these systems use historical data. However, due to booking limits, registered reservations do not represent the real demand. We first present a comprehensive review on different aspects of demand modeling in the context of revenue management systems.
Then, we propose a new non-parametric global optimization approach which is able to model demand by using choice probabilities. Our proposed model is able to extract seasonal features of demand and customer utilities for a given product. Finally, in a comparative study, we investigate the impact of different methods of customer preference estimation on revenue.
She is presently a postdoctoral fellow at Polytechnique Montreal. Gunnar Floetteroed KTH Royal Institute of Technology A simple and fast queueing model of bi-directional pedestrian flow in long channels October 18, , , Abstract: We derive an utmost simple microscopic queueing model of bidirectional pedestrian flow through long channels. The model is to the extent possible consistent with the Kinematic Wave Model and requires the calibration of only four parameters.
Its fundamental diagram is derived and compared to real data joint work with Gregor Laemmel, FZ Juelich. Since , he is on a junior faculty position in transport modeling at KTH. Certain containers from one eco-point may need to be moved to another one or to a repair facility if they have been damaged. Moreover, every container needs to be cleaned on site over a planning horizon.
The container movement problem is solved as a dial-a-ride problem. A genetic algorithm is used to find a good assignment of movements to vehicles. The quality of the assignments is determined by a routing heuristic which considers the specified problem constraints and provides the resulting route's cost. The cleaning problem is solved with minimum changes to the above methodology. The algorithm has been tested on real data and is currently being integrated by the client company. The algorithmic part is complemented by a graphical user interface with route plotting capabilities. In recent years, Iliya has published several book chapters and journal articles in the fields of finance and optimization.
He is currently working in the field of operational research, and in particular vehicle routing, and would like to pursue an academic career in this domain. In the near term, this means that greener modes must compete more effectively with, and coexist more harmoniously with, automobile traffic. The presentation explores ideas in this realm, beginning at the scale of a city block.
I first focus on busy, multi-berth bus stops where multiple bus lines converge and on the bus queues that form when these stops have insufficient numbers of berths. Queueing models are developed to predict the bus-carrying capacities of these stops, and analytical solutions are derived by exploiting renewal processes that are embedded in the unique operating features of serial bus berths. I then examine bus stops that reside near signalized intersections, where dwelling buses can impede cars from discharging into or out of the intersections.
Using kinematic wave theory, analytical models are formulated, both to quantify negative impacts and design mitigation strategies. The presentation ends with brief discussion of ongoing work, e.
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His research interests include public transit systems, multimodal urban transportation systems, freeway traffic operations, queueing models, and infrastructure management. He received his B. His awards include a Gordon F. In this vein, emerging technologies continually offer new communication capabilities that can be used to improve performance. The aim of this study is to develop a novel Ramp Metering strategy, exploiting communication capabilities to further reduce congestion at motorway junctions.
This new system rearranges gaps present in the motorway traffic by requesting cooperation from participating vehicles in order to facilitate merging. Macroscopic traffic flow theory is used to develop the control algorithm, and microscopic simulation of individual vehicles is used to evaluate the system traffic performance. Results indicate reduction of congestion occurrence, improvement in merging capacity and increase in travel time reliability. This shows how the use of new communication technologies can improve the performance of current ITS and lead to a reduction of congestion on motorways.
Traditional models of travel mode choice assume that 1 that all individuals are aware of the full range of travel modes at their disposal and make a rational mode choice based on level-of-service and 2 individual modal preferences are characteristics of the individuals that are exogenous to the choice situation and stable over time. Though these assumptions simplify the model, they risk overlooking the impact of more deeply entrenched individual variations in modal preferences.
This talk presents a latent class choice model LCCM that allows modal preferences to be endogenous to the choice situation and variable across individuals. The model is applied to analyze modality styles and travel mode choice behavior of 25, people in the San Francisco Bay Area. The study identifies six distinct modality styles in the sample population that differ in terms of their taste parameters and choice sets. Most notably, nearly a third of the sample is found not to consider any mode other than auto. Results show that an individual's value of time is sensitive to the level-of-service, and an increase in congestion can induce decision-makers to lower their value of time.
Findings further reveal that incremental improvements in the transportation system result in far smaller changes in travel behavior than predicted by traditional models; what is needed is a dramatic change to the transportation system that forces individuals to reconsider their modality styles.
Short bio: Joan Walker's research focus is behavioral modeling, with an expertise in discrete choice analysis and travel behavior. She works to improve the models that are used for transportation planning, policy, and operations. Ricardo Hurtubia University of Chile Modelling preferences of urban form with latent classes and psychometric indicators April 15, , , Abstract: A method to use psychometric indicators in the estimation of latent classes for discrete choice models is presented.
The method attempts to use latent constructs accounting for qualitative or hard to measure attributes of the alternatives by relating them with the perception of users, captured through psychometric indicators. His research interests include modeling behavior in the urban context and simulation of land use and transportation systems. Franziska Borer Blindenbacher Transport Consulting Market-based approaches applied to transportation issues: the Heavy Vehicle Fee - a Swiss success story April 11, , , Abstract: Various countries have meanwhile adopted market incentives to meet transport needs in an economically efficient way.
The seminar will touch on different types of approaches for financing passenger and freight transportation, and for addressing transportation-related externalities. There will be a special emphasis on the unique Swiss Heavy Vehicle Fee HVF , which will serve as an example of the practical and political issues that need to be addressed in order to implement sustainable national transportation policies.
The objectives of this seminar are to encourage students to familiarize themselves with a range of transportation and related environmental, social and economic policy issues and to develop an understanding of the complexity, inter-connection and potential resolution of some of these issues. Short bio: Franziska Borer Blindenbacher is an economist and works as an international consultant and teacher in the fields of transport, spatial planning and the environment. Ms Borer Blindenbacher is the author of various publications in the field. Luis F. Miranda-Moreno McGill University Monitoring and modeling of non-motorized mobility and safety: data needs, applications and issues December 14, , , Abstract: Monitoring and analyzing non-motorized pedestrians and bicycle flows over time and space in a urban road network is essential for various reasons, including i evaluation of the impacts of new infrastructure, programs and policies to encourage cycling and walking, ii identification of current traffic patterns and prediction of future demand for the planning, design and operation of facilities, iii mapping injury risk for the identification of dangerous facilities and inappropriate designs, etc.
This work provides a discussion of the non-motorized traffic data needs and the emerging technologies for traffic monitoring and data collection. Using the City of Montreal as an application environment, this work also presents a framework for monitoring and modeling safety and mobility of non-motorized flows in an urban environment. As an input data, automatic long-term and manual sort-term traffic counts are combined. This framework allows identifying factors affecting non-motorized traffic flows and safety, such as weather, built environment and road designs.
The proposed framework will also help monitoring changes in non-motorized mobility and safety in the study network. His research interests include road safety, non-motorized transportation, and the relationship between transportation and the environment. More specifically, his research interests include developing methods and tools for crash risk analysis, monitoring and modeling pedestrian and bicycle flows, as well as identifying strategies to reduce fuel consumption and greenhouse gases.
Bruno F. Santos University of Coimbra, Portugal Optimization approaches applied to the strategic planning of transportation infrastructures December 06, , , Abstract: The strategic decisions with regard to the investments in transportation infrastructures usually involve large amounts of money.
Therefore, decisions should be carefully analyzed. Cost-benefit analysis, usually based on trial-and-error approaches, does not allow the full exploration of the solution space. This can only be done using optimization techniques. This talk will give an overview of the work developed by the author on the usage of optimization approaches to solve strategic transportation investment planning problems.
Short bio: Bruno F. He had published several works on transportation planning topics and has been involved, besides other research initiatives, in the MIT-Portugal research and teaching program. Dick Ettema Utrecht University, Netherlands An activity-based approach to analyzing walking November 01, , , Abstract: Studies of walking behavior have gained momentum over the past years, due to improved data collection techniques and further development of modeling approaches.
In most cases, such studies emphasize the detailed movement of pedestrians in relation to aggregate pedestrian flows, and decisions regarding route or destinations during a walking trip. This presentation aims to look upon walking behavior from a broader perspective, by discussing the options of applying an activity based approach to walking behavior. In particular, it will be discussed to what extent decisions made regarding the daily or longer term activity pattern influence decisions regarding the walking trip such as where to walk, for how long, with whom , decisions during the walking trip such as routes, places to visit and activities to pursue while walking and the experience of the walking trip how pleasant, stressful etc.
It will be argued that looking upon walking from this broader perspective gives rise to the inclusion of addition variables in our analyses, including functional characteristics of places and routes amenities, functions as well as ambient conditions and aesthetics. Since then, he has published widely on activity based analysis, activity based modeling and time-use studies. Evanthia Kazagli The Royal Institute of Technology KTH , Stockholm, Sweden Estimation of arterial travel time distributions from automatic number plate recognition data using mixture models August 14, , , Abstract: Automatic Number Plate Recognition ANPR data have been widely used for estimation of travel time and travel time distributions, mainly in the case of freeways.
The objective of this work is to formulate a finite mixture model for the estimation of arterial travel time distributions based on ANPR data. Assuming that the population of ANPR travel times is generated by two different subpopulations components -one deriving from non-stopped valid vehicles and one from the stopped- finite mixture models can be used at a first level as clustering technique to separate these two components. In an attempt to reinforce the model, explanatory variables such as weather conditions are included in the estimation. In arterial networks, route travel times are likely to vary among the valid observations, even over small time intervals.
This is due to such factors as traffic lights, buses stopping, vehicles turning mid-link delaying following vehicles, etc Robinson, , resulting in a multimodal probability density function of travel time. In this context mixture models can be used - at a second level - for the estimation of route travel time distribution. A very important aspect is the assumption for the underlying distribution. The common assumption of normal distribution of travel time is replaced by log-normal in this case mixture of log-normal distributions.
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Haris Koutsopoulos. Her work deals with the estimation of arterial travel time distributions. Her research interests include among others intelligent transportation systems and travel time estimation and reliability. August 09, , , Abstract: The multi-trip vehicle routing problem with time windows is a variant of the classical vehicle routing problem with time windows, where a vehicle can perform several trips during the planing time horizon. Multiple trips are beneficial to the carrier by limiting the number of vehicles and drivers necessary to the deliveries, especially in the cases where vehicle capacities, distances or time constraints naturally imply short distribution routes.
However, this feature generate many combinatorial issues due to the mutual exclusion constraints that appear between two trip performed by the same vehicle. We propose a set covering formulation, where variables represent trips, and an exact method based on Branch and Price scheme to solve it. Computational results on Solomon's benchmarks evaluate the method on small to middle-sized instances.
He recieved his Ph. Even if his PhD research topic was focused on designing a Branch and Price algorithm to solve a spraying agricultural problem, his main research topic is more generally expanded to the combinatorial optimization methods used in transportation science. Carlo L. Bottasso Department of Aerospace Engineering, Politecnico di Milano, Italy Rotary Wings: the Modeling and Simulation of Helicopters and Wind Turbines June 27, , , Abstract: Helicopters and wind turbines are very different complex engineering systems, that however share some common physical processes.
For both, rotating flexible blades interact in a highly unsteady manner with air to make a vehicle fly in one case and to generate energy from wind in the other.
In this talk we will first review some mathematical models that are used for the simulation of both systems. Then, we will describe some challenging applications, ranging from the simulation of helicopters flying extreme maneuvers at the boundaries of their flight envelope, to the passive and active mitigation of loads on large wind turbines.
These examples will help highlight the differences between these two engineering systems and will illustrate their very different design drivers. In both cases, the ability to model the relevant coupled physical processes to a high level of fidelity is key for achieving the ever more ambitious design goals posed by industry. Short bio: Carlo L. Bottasso earned a Ph. His research interests are in multibody dynamics, aero-servo-elasticity and control. Specific interests are in flexible multibody dynamics with application to the modeling of rotary wing vehicles and wind turbines, and corollary modeling and numerical technologies, including system identification, model reduction, methods for the solution of algebraic-differential equations, non-linear finite elements, adaptive and optimal control.
On these topics he has co-authored over publications, including 90 peer review journal papers. Thereby, each data source usually needs to be read individually via its specific data access possibilities. The solution also offers a possibility of complex filtering data from different sources. The SCADA-UMS system, which this solution is implemented for, is a smart grid software system for monitoring and management of a power distribution network. The main part of the solution is the GDA Smart Proxy component, which behaves as the central data source from the system's point of view.
GDA Smart Proxy combines data from existing sources and implements a module for complex filtering. Maya Abou Zeid American University of Beirut, Lebanon Travel Behavior Models and Applications to Time-of-Travel, Value of Time, and Mode Switching Decisions April 26, , , Abstract: Travel behavior models predict individual decisions related to various travel dimensions, such as the choice of auto ownership, activity patterns, destinations visited, modes of transportation, routes, and departure times. They are used as part of decision support systems by transportation planners and policy makers to predict travelers' responses and traffic impacts resulting from infrastructure e.
The accuracy of these decision support tools depends on the richness embedded in the travel behavior models. This talk will give an overview of some recent developments in the area of travel behavior modeling with applications to modeling time-of-travel choice accounting for the cyclicality of time-of-travel, modeling heterogeneity across individuals in the value of travel time savings arising from different attitudes towards travel modes, and modeling mode switching from car to public transportation in relation to travel happiness using recent experiments conducted with habitual car drivers in Switzerland and in Boston.
The applications show how insights from behavioral theories can be used to enrich the travel demand models and make them more policy-sensitive. Her research interests include travel behavior modeling, urban transportation planning, market research, and road safety. Under the atmosphere, the competition among port container terminals has become acute and such drives the managers in port container terminals to maintain seamless flows of containers through terminals while to keep the operational costs as low as possible.
To this end, operational research methods have received considerable importance for the operations management in port container terminals. This seminar will cover Mr. Chen's studies on quayside operation problem in port container terminal including both mathematical modeling and algorithm development. Firstly, for mathematical modeling, there are two highlights in Mr. Chen's studies: 1 the technology updates and innovative implementations have been reflected; 2 the integration issues to synchronize the decision-making processes for each key component of the quayside operation problem have been stressed.
Secondly, for problem solving, a spectrum of methods has been devised to handle the proposed models. In this seminar, Mr. Chen will also introduce the problem-oriented meta-heuristics, approximation algorithms, and exact algorithms like Benders' Cut Method developed for the quayside operation problem. Short bio: Mr. Chen Jiang Hang obtained B. His PhD research topic focuses on port container terminal operation management especially for the quayside operation problem which includes the berth allocation problem, the quay crane assignment problem, and the quay crane scheduling problem.
As global air traffic volume is continuously increasing, it has become a priority to improve air traffic control in order to deal with future air traffic demand. During this decade, European and United States initiatives were launched to design the future of air traffic management. One of their objectives is to increase air traffic density and optimize flight route plans. This can be achieved through en-route deconfliction. Potentials air conflicts occur when two or more aircraft are predicted to be below a separation norm in a near future. Efficiency of the method has been validated through simulations including humanin- loop experiments thus opening the door to conflict resolution algorithms based on speed regulation.
We propose an optimization-oriented formulation for the speed regulation problem. We start by presenting a potential conflict detection and resolution framework. Uncertainty is then introduced in the model, aiming at reproducing realistic air navigation conditions. We conclude with a case study on real air traffic instances and results are discussed to assess the potential of the proposed algorithm. His research topic is focused on the minimization of potential air conflicts using speed control. Winnie Daamen Delft University of Technology, The Netherlands Behaviour near evacuation doors: data analyses and modelling February 10, , , Abstract: Emergency doors may be bottlenecks in the evacuation of a building.
As neither the capacities of these doors are not known, nor details on the behaviour of people near these doors, large scale laboratory experiments have been performed. Using video images, we have identified the relation between the capacity and a number of factors, such as door width, population composition and stress level. In addition, the collected trajectory data have been used to calibrate our pedestrian simulation model Nomad and to compare the resulting behavioural parameters between evacuation conditions and normal conditions.
To do this, an automated calibration procedure has been developed, which yields parameter estimates for individual pedestrians. The existing calibration procedure has been extended by including data from multiple pedestrians into a single estimate. The resulting parameter distributions provide insight into pedestrian behaviour. So far, dedicated parameter sets have been estimated for elderly, adults and children.
It could be shown that not only the pedestrian behaviour changed between normal and evacuation conditions, but also between the different types of persons. This evaluation methodology specifically focuses on the inclusion of the different actors that are involved in the project, the so called stakeholders. As the traditional multi criteria analysis, it allows to include qualitative as well as quantitative criteria with their relative importance, but within the MAMCA they represent the goals and objectives of the multiple stakeholders and by doing so allow to include the stakeholders into the decision process.
The theoretical foundation of the MAMCA method will be shown together with several applications in the field of transport appraisal. She teaches courses in operations and logistics management, as well as in transport and sustainable mobility. Her research group MOSI-Transport and logistics focuses on establishing linkages between advanced operations research methodologies and impact assessment. She has been involved in several national and European research projects dealing with topics such as the location of intermodal terminals, assessment of policy measures in the field of logistics and sustainable mobility, electric and hybrid vehicles, etc.
She is the chairwoman of Brussels Mobility Commission. Trends and policy options September 22, , Abstract: This article examines long-term trends and broad policy options and challenges related to the road transport sector and its congestion and environmental impacts. A brief review of long-term projections of demand for road transport suggests that problems related to road network congestion and greenhouse gas emissions are likely to become more pressing in the future than they are now.
Next we review, from a macroscopic perspective, three policy measures aimed at addressing these problems: stimulating shifts in transport modes to decrease congestion and greenhouse gas emissions, boosting low carbon technology adoption to reduce greenhouse gas emissions from cars, and regulating land use to reduce road transport volumes.
We find that although these policies can produce tangible results, they may also have unintended and costly consequences. He is director of a group of 10 researchers at the Center for Economic Studies that deals with environment, energy and transport topics. He is specialised in using mathematical models to address public policy questions: optimal pricing and investment in transport, choice of policy instruments for environmental policy, energy pricing questions.
Policy issues he studied over the last years include the deepening of the Scheldt, the Iron-Rhine, the Oosterweel bridge in Antwerp, the selection of TEN-T projects, the introduction of road pricing and the climate policy in the transport sector. The RRM-approach to discrete choice-modeling provides an alternative to the conventional, Random Utility Maximization RUM -based approach which has dominated the field since its inception. In contrast with RUM-theory, RRM-theory postulates that when choosing, decision-makers are concerned with avoiding the situation where one or more non-chosen alternatives perform better than a chosen one in terms of one or more attributes.
From this central behavioral premise, semi-compensatory decision-making and choice set-composition effects like the compromise effect emerge as RRM-model features. In past years, he was visiting scientist at Cornell University, assistant professor at Eindhoven University of Technology, visiting doctoral student at MIT and doctoral student at Delft University of Technology.
His research is concerned with increasing the behavioral realism of travel demand models. The Random Regret Minimization-approach he developed has been succesfully applied in various research groups around the world, and is being incorporated in the newest version of the NLOGIT-software package.
Ricardo A. Daziano School of Civil and Environmental Engineering, Cornell University Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range July 08, , , Abstract: Range anxiety - consumers' concerns about limited driving range - is generally considered an important barrier to the adoption of electric vehicles.
If consumers cannot overcome these fears it is unlikely that they will consider purchasing an electric car. Hence, for planning a successful introduction of low emission vehicles in the market it becomes essential to fully understand consumer valuation of driving range. Analyzing experimental data on vehicle purchase decisions in California, in this paper I derive and study the statistical behavior of three Bayes estimates that summarize consumer concerns toward limited driving range.
Independence Metropolis-Hastings appears as a well-behaved sampler for nonlinear transformations of the marginal utilities. One of the empirical results is the posterior distribution of the driving range that makes an electric vehicle equivalent to internal combustion vehicles. Interestingly, this posterior is centered at driving range parity. The credible interval for the willingness to pay for an increase in range is also analyzed. Daziano is a specialist in theoretical and applied microeconometrics of consumer behavior, specifically on discrete choice models applied to sustainable behavior, technological innovation, and transportation demand.
Daziano's specific empirical research interests include the analysis of pro-environmental preferences toward low-emission vehicles, modeling the adoption of sustainable behavior, estimating willingness-to-pay for renewable energy, and forecasting consumers' response to environmentally-friendly energy sources.
Daziano completed his undergraduate studies and a masters' degree in engineering in Santiago at the University of Chile. After working four years as a demand analyst consultant in the private sector, he decided to pursue an academic career in discrete choice modeling. In January he joined the faculty of the School of Civil and Environmental Engineering at Cornell University, adding a new dimension to the area of sustainable systems engineering in both teaching and research.
Additionally, Daziano continues to serve as a consultant in consumer choice modeling in areas such as transportation and sustainable tourism. Such techniques typically involve the design of a process model, detailed simulations as well as the development of control systems leading to optimum plant operation. Many times the skills and techniques used by process engineers overlap those applied and developed in operations research.
In this seminar, I would like to talk about a chemical transport process I was involved during an internship and about a model on which I am currently working in the framework of my Master thesis. The goal of the former project was to optimize an industrial plant with respect to several criteria by employing a purely statistical analysis; the aim of my current work is to analyze a micro reaction using a physical non-parametric model and subsequently to optimize the reaction yield. I will keep my focus on the philosophy of process engineering which can be appreciated without an engineering background.
He has been a member of the Swiss Study Foundation since ; during his studies he concentrated on modeling and optimization of both technical and non-technical systems. Samer Madanat Civil and Environmental Engineering Dpt, University of California, Berkeley Reliability-based optimization of maintenance and replacement policies for a heterogeneous system of infrastructure facilities June 14, , , Abstract: This research addresses the determination of optimal maintenance and replacement policies for a heterogeneous system of facilities.
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