On numerical testing of the regularity of semidefinite problems

This paper is devoted to study regularity of Semidefinite Programming (SDP) problems. Current methods for SDP rely on assumptions of regularity such as constraint qualifications and wellposedness. Absence of regularity may compromise characterization of optimality and algorithms may present numerical difficulties. Prior that solving problems, one should evaluate the expected efficiency of algorithms. Therefore, it is important to have simple procedures that verify regularity. Here we use an algorithm to test regularity of linear SDP problems in terms of Slater’s condition. We present numerical tests using problems from SDPLIB and compare our results with those from others available in literature

Two-Step-SDP approach to clustering and dimensionality reduction

Inspired by the recently proposed statistical technique called clustering and disjoint principal component analysis (CDPCA), this paper presents a new algorithm for clustering objects and dimensionality reduction, based on Semidefinite Programming (SDP) models. The Two-Step-SDP algorithm is based on SDP relaxations of two clustering problems and on a K-means step in a reduced space. The Two-Step-SDP algorithm was implemented and tested in R, a widely used open source software. Besides returning clusters of both objects and attributes, the Two-Step-SDP algorithm returns the variance explained by each component and the component loadings. The numerical experiments on different data sets show that the algorithm is quite efficient and fast. Comparing to other known iterative algorithms for clustering, namely, the K-means and ALS algorithms, the computational time of the Two-Step-SDP algorithm is comparable to the K-means algorithm, and it is faster than the ALS algorithm

Safety and emissions algorithms for the interaction between motor vehicles and vulnerable road users

Road traffic has been responsible for high levels of pollutant emissions, several injuries and deaths. Many studies have been focused on safety or emissions issues, but an integrated approach considering safety-emission hotspots is rather rare, particularly, with respect to impacts involving Vulnerable Road Users (VRU), such as pedestrians and cyclists. The recent advancements in technology and in vehicle automated functions will reshape the road traffic environment, and soon, there will be a transition phase where Conventional Vehicles (CVs) and Connected and Autonomous Vehicles (CAVs) will coexist and share the road infrastructure. Therefore, this Ph.D. research seeks to develop an integrated approach focused on advanced algorithms to reduce driving behavior volatility through safety and emissions warnings in an urban environment focusing on the transition phase. Real data will be used to evaluate driving volatility and pollutant emissions. Safety and emissions will be combined through an integrated methodology under a statistics-optimization-data mining framework. The expected contributions of this Ph.D. research will be: 1) a thorough and microscopic characterization of individual driver decision mechanisms focused on safety and emissions hotspots in urban areas, with a major concern on VRU exposure; 2) a tool of driver warning and control assistance mechanism to be applied in both CVs and CAVs.publishe

Statistical Methods and Optimization in Data Mining

The main objective of this work is to test the ability of the new tech- nique CDPCA - Clustering and Disjoint Principal Component Analysis on biological data sets to make possible visual representation of relevant characteristics for data interpretation. For this purpose, we im- plemented CDPCA in R language and conducted several experiments. Numerical results show its efficiency

A Generator of Nonregular Semidefinite Programming Problems

Regularity is an important property of optimization problems. Various notions of regularity are known from the literature, being defined for different classes of problems. Usually, optimization methods are based on the optimality conditions, that in turn, often suppose that the problem is regular. Absence of regularity leads to theoretical and numerical difficulties, and solvers may fail to provide a trustworthy result. Therefore, it is very important to verify if a given problem is regular in terms of certain regularity conditions and in the case of nonregularity, to apply specific methods. On the other hand, in order to test new stopping criteria and the computational behaviour of new methods, it is important to have an access to sets of reasonably-sized nonregular test problems. The paper presents a generator that constructs nonregular Semidefinite Programming (SDP) instances with prescribed irregularity degrees and a database of nonregular test problems created using this generator. Numerical experiments using popular SDP solvers on the problems of the database are carried out and permit to conclude that the most popular SDP solvers are not efficient when applied to nonregular problems

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

Sem resumo disponível.publishe

Micro driving behaviour in different roundabout layouts: pollutant emissions, vehicular jerk, and traffic conflicts analysis

Driving behaviour affects both road safety and the environment, either positively or negatively. An unsafe driving behaviour characterized by hard acceleration/braking (also called driving volatility) can lead to an increase in emissions. Driving volatility can occur due to driving style, traffic, or road conditions. Although roundabouts present better safety performance than other traffic-control treatments, different layouts may lead to different levels of traffic-related impacts. This paper aims to evaluate vehicle movements through three types of roundabouts (Single-lane (SL), Compact two-lane (CTL), and Multi-lane (ML)) focusing on assessing the impact of driving volatility on traffic conflicts and pollutant emissions. A micro driving behaviour analysis of emissions, driving volatility, and conflicts were conducted for the links of the entry, circulating, and exit areas of the studied roundabouts. Speed was used as a variable parameter directly related to the driver while vehicular jerk and traffic conflicts, as well as global (carbon dioxide – CO2) and local (nitrogen oxides – NOx) pollutants were used to evaluate the traffic safety and emissions performance, respectively. Field measurements obtained from a light-duty probe vehicle equipped with an on-board diagnostic reader on three different layout roundabouts located in suburban environments were used to develop a microscopic traffic simulation for the baseline. Simulations were conducted using VISSIM, emissions were estimated using the Vehicle Specific Power (VSP) methodology, and the Surrogate Safety Assessment Model (SSAM) was applied for estimating the traffic conflicts between motor vehicles. Four speed-distribution scenarios were considered, and associated impacts were evaluated for each roundabout. In general, speed variation and subsequently vehicular jerk had more impact on traffic conflicts than pollutant emissions. The number of conflicts in the exit area was less than entry and circulating in all roundabout designs but ML presented more traffic conflicts.publishe

Exploring new ways to charge intercity mobility: impact on road traffic externalities

Around 70% of transport-related emissions in the EU (European Union) came from road transportation. A major contribution to the transport-related emission externalities comes from all the passenger car trips generated in intercity corridors. In Portugal, these trips represent 65% of the kilometers travelled and more than 55% of CO2 and NOx emissions. Portugal is the second worst country withing EU, only followed by Luxembourg, in terms of the relationship between external costs of transport and the country GDP (Gross Domestic Product)., the external costs of transport account for 7.2% of the country GDP. This work intends to assess how generalized GPS-based toll systems can reduce emissions compared with a flat-electronic collection system. The model for estimating network demand and traffic assignment is PTV VISUM. Emissions are estimated using a macroscopic methodology. The variables under study are the CO2 and NOx emissions, emissions-related external costs, total revenue, user costs. A trade-off will be performed to discuss the best strategy for different periods under study (peak and off-peak hours). Previous research efforts related to GPS-based toll collection systems do not refer to the environmental impacts of the application. These research gaps are addressed in this work by proposing a methodology focused on innovative road pricing emission-based tolls (e.g. GPS-based tolls) in intercity corridors. Simulation experiment results on a case study in Portugal comprising alternative routes of approximately 60km show that two different strategies are recommended for the peak and off-peak hours period. A GPS-based toll collection is only applicable on the Motorway for peak hours, and a GPS-based toll collection is applied in both road options off-peak hours. This strategy in a 24-hour span would allow a total decrease in emissions-related externalities (-1.4%) with only a small decrease of the total revenue without sacrificing the cost each user would pay to travel through this intercity corridor. Bearing in mind the residual emission reductions and the level on uncertainty associated with the model, these results are promising in that they suggest that it is plausible to implement a system that internalizes emission costs more directly as a function of demand, driving conditions and speed.publishe

Integrating environmental impacts in an intercity corridor level pricing scheme

A significant part of the transport sector externalities occurs in intercity corridors, which account for 65% of the total of the kilometers travelled in for example, Portugal (for 2017). A thorough analysis of intercity corridors characteristics has been receiving less attention compared to urban roads. The objective of this work is to propose a methodology to tackle intercity corridors issues with respect to environmental impacts. It will focus on suggesting smart and dynamic toll systems, integration of impacts in pricing schemes, and optimization of public transport fares, coupled with a scheme based on the “polluter pays” principle. This vision paper presents the main objectives and methodology of an ongoing research in which the final objective is to lead to a more efficient usage of the infrastructures. The optimization is mainly focused on an environmental perspective, which can be important for decision-makers to improve specific intercity corridor measures/policies.publishe

Clustering and disjoint principal component analysis of emissions and driving volatility data collected from a hybrid electric vehicle in real drive conditions

Despite the fuel use and emission benefits of Hybrid Electric Vehicles (HEVs), few studies have characterized in detail emission patterns and driving volatility profiles from HEVs in different road types under Real Driving Emission (RDE) conditions. This paper characterized second-by-second tailpipe emissions, vehicle engine, and dynamics from a 2020 Toyota HEV sub-compact on a 44 km driving route over rural, urban, and highway roads in the Aveiro region (Portugal). Driving volatility was represented by six driving styles based on combinations of acceleration/deceleration and vehicular jerk (the rate at which an object’s acceleration changes with respect to the time). Clustering and Disjoint Principal Component Analysis (CDPCA) was applied to examine the relationships between emissions, engine, internal combustion engine (ICE) status, roadway characteristics, and vehicular jerk types. Although the urban route yielded lower carbon dioxide and nitrogen oxides emissions than rural and highway routes did, it resulted in highly volatile driving behaviors at low speeds (< 45 km.h-1). Both route type and HEV ICE operating behavior showed to have an impact on the distribution of vehicular jerk types. CDPCA constrained to road sector exhibited different shapes in the clusters of the jerk types between ICE operation status. This paper can provide insights into RDE analysis of the new generation of HEVs about the characterization of volatile driving behaviors. Such information can be integrated into vehicle electronic car units and navigation systems to provide feedback for drivers about their driving behavior in terms of high emission rates and jerkings to the vehicle.publishe