Vehicle rollover avoidance by application of gain-scheduled LQR controllers using state observers

Many researches have been conducted in the area of control applied to vehicle dynamics, aiming at reducing the possibility of the occurrence of the type of accident known as rollover. In this research, based on a common nonlinear model and its linearisation, a method for properly selecting matrices for solving the Riccati equation considering different speeds was proposed. The method showed in which ways speed really influences the choice of controller gains. By developing the dynamic equations for the yaw- and roll-coupled motions and modelling of controllers and state observers, it is possible to compare the efficacy of this control strategy using both linear and nonlinear simulations using Matlab. Significant results were obtained regarding the reduction of the rollover coefficient for a double-lane change manoeuvre at different speeds, thus indicating advantages of using this controller in practical cases.     

Lap time optimisation of a racing go-kart

The minimum lap time optimal control problem has been solved for a go-kart model. The symbolic algebra software Maple has been used to derive equations of motion and an indirect method has been adopted to solve the optimal control problem. Simulation has been successfully performed on a full track lap with a multibody model endowed with seven degrees of freedom. Geometrical and mechanical characteristics of a real kart have been measured by a lab test to feed the mathematical model. Telemetry recorded in an entire lap by a professional driver has been compared to simulation results in order to validate the model. After the reliability of the optimal control model was proved, the simulation has been used to study the peculiar dynamics of go-karts and focus to tyre slippage dynamics, which is highly affected by the lack of differential.     

Comparison of direct and indirect methods for minimum lap time optimal control problems

Minimum lap time simulations are especially important in the design, optimisation and setup of race vehicles. Such problems usually come in different flavours, e.g. quasi-steady state models vs. full dynamic models and pre-defined (fixed) trajectory problems vs. free trajectory problems. This work is focused on full dynamic models with free trajectory. Practical solution techniques include direct methods (i.e. solution of an nonlinear programming problem problem, widespread approach) and indirect method (i.e. based on Pontryagin's principle, less common, yet quite efficient in some cases). In this contribution the performance of the direct and indirect methods are compared in a number of vehicle-related problems.     

Air traffic management: Optimization models and algorithms

Current air traffic control systems are mainly conceived to ensure the safety of flights by means of tactical interventions, because of the difficulty of accurately foreseeing the traffic evolution. In fact, in real traffic conditions, planes are often penalized since sometimes safety standards are redundant. Today, this management philosophy is no longer valid because of congestion phenomena which often occur in the most important terminal areas. Therefore, as to future control systems it is necessary to introduce not only more automated procedures to keep adequate safety levels, but also planning functions in order to increase the system capacity and to improve system efficiency. In recent years several studies have been carried out, new control concepts have been introduced and some optimization models and algorithms developed to improve air traffic management. In this paper a survey of our early works in this field is reported and a multilevel model of air traffic management is proposed and discussed. The functions corresponding to the on-line control, that is flow control, strategic control of flights and aircraft sequencing in a terminal area, are examined and the optimization models and solution algorithms are illustrated. Finally, relevant problems coped by recent research are mentioned and new trends are indicated.     

Spatial multi-criteria assessment of potential lead markets for electrified vehicles in Europe

This study presents a modeling approach that focuses on the identification of potential lead markets for electric-drive vehicles (EDVs) in Europe. It is based on a combination of several selected economic, social, environmental, and transport-related factors. The modeling approach is implemented in a GIS-based multi-criteria decision support process with fuzzy measures, enabling an assessment at different spatial and temporal scales under different EDV market penetration scenarios for Europe. The decision support system embeds a multi-criteria analysis based on selected expert-weighted market penetration drivers. The spatial scale chosen for the application of the decision support process are NUTS2 regions and cities within EU27 member states. Three scenarios are investigated, a business as usual, a moderate change, and an accelerated innovation scenario. Across the scenario horizon, it is shown how lead regions for EDVs will be changing in time between first early-adopter areas towards other long-term potential lead regions, depending on the evolution of the market drivers. The European regions and cities which will have a higher lead market potential score in 2020 and 2030 are identified. Our model solution suggests that with the business-as-usual scenario there will be a few insular lead market areas in 2020 and a relatively limited number of more connected lead regions in 2030. The other two scenarios explored suggest a more positive picture leading for the case of the 2030 accelerated scenario to a wide distribution of EDVs across most of Germany, the Netherlands, France, the UK, Ireland, and Italy. The cities of London, Madrid, Berlin and Rome would show high EDV sales under this scenario.     

A bilevel flow model for hazmat transportation network design

In this work we consider the following hazmat transportation network design problem. A given set of hazmat shipments has to be shipped over a road transportation network in order to transport a given amount of hazardous materials from specific origin points to specific destination points, and we assume there are regional and local government authorities that want to regulate the hazmat transportations by imposing restrictions on the amount of hazmat traffic over the network links. In particular, the regional authority aims to minimize the total transport risk induced over the entire region in which the transportation network is embedded, while local authorities want the risk over their local jurisdictions to be the lowest possible, forcing the regional authority to assure also risk equity. We provide a linear bilevel programming formulation for this hazmat transportation network design problem that takes into account both total risk minimization and risk equity. We transform the bilevel model into a single-level mixed integer linear program by replacing the second level (follower) problem by its KKT conditions and by linearizing the complementary constraints, and then we solve the MIP problem with a commercial optimization solver. The optimal solution may not be stable, and we provide an approach for testing its stability and for evaluating the range of its solution values when it is not stable. Moreover, since the bilevel model is difficult to be solved optimally and its optimal solution may not be stable, we provide a heuristic algorithm for the bilevel model able to always find a stable solution. The proposed bilevel model and heuristic algorithm are experimented on real scenarios of an Italian regional network.     

Symbolic transport choice across national cultures: theoretical considerations for research design

A recently empirically isolated latent variable in transport choice is symbolism, which examines what people believe their transport choices say to others about them and how they are judged in a social context. Whilst it is well established that symbolism differs vertically across different socio-economic groups within a country, very little work has been done on how symbolism in transport may differ between similar individuals across nations as a function of national cultural values, and how this may manifest itself in transport choices. If significant differences were to be found then this could have impacts for transport policy formulation and transfer. This paper explores and discusses these issues and concludes that the initial goal of any research into symbolic transport choices across cultures is theoretical fertility, and this is best achieved by adopting Lakatosian research programmes, using theory-driven thematic analysis to develop theoretical models for testing.