Approaches for Modelling User’s Acceptance of Innovative Transportation Technologies and Systems

The gradual penetration of new transport modes and/or new technologies (advanced information systems, automotive technologies, etc.) requires effective theoretical paradigms able to interpret and model transportation system users’ propensity to purchase and use them. Along with the traditional approaches mainly based on random utility theory, it is a common opinion that numerous nonquantitative variables (such as psychological factors, attitudes, perceptions, etc.) may affect users’ behaviors. Different traditional approaches and more advanced ones (e.g. hybrid choice model (HCM) with latent variables, theory of planned behaviour, regret theory, prospect theory, etc.) may be identified and properly applied in the literature. In particular, the chapter will focus on the hybrid choice modeling with latent variables, aiming to incorporate users’ perceptions, attitudes and concerns in order to model the user’s propensity to use and the willingness to buy a new technology. The methodology overview and the results of the application at real data are discussed

Accounting for attitudes and perceptions influencing users' willingness to purchase Electric Vehicles through a Hybrid Choice Modeling approach based on Analytic Hierarchy Process

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Two Variables Algorithms for Solving the Stochastic Equilibrium Assignment with Variable Demand: Performance Analysis and Effects of Path Choice Models

In this paper a general fixed-point approach dealing with multi-user (stochastic) equilibrium assignment with variable demand is proposed. The main focus is on (i) the implementation and comparison of different algorithm solutions based on successive averages methods calculated on one (arc flows, arc costs) and on two variables (arc flows and path satisfaction; arc costs and demand flows); (ii) the effects of algorithm efficiency on different path choice models and/or travel demand choice models. In terms of the best performing algorithmic solution, the effects of different path choice models, such as Multinomial Logit model, C-Logit model and Multinomial Probit model were implemented, and algorithmic efficiency was investigated w.r.t. a real network

scheduled synchronisation based on a mesoscopic flow model with speed dispersion

Abstract This paper proposes a method for netwok signal setting design, based on enhacements of an existing coordination method aiming: 1) to extend the existing approach in order to address the Traffic Control through Scheduled Synchronisation (i.e 'one step' optimisation of stage matrix, green timings, and node offsets ); 2) to extend the considered Mesoscopic Traffic Flow model (TRAFFMED) to the vehicle platoon speed dispersion; 3) to build up a solution method suitable for both off-line and on-line applications. The proposed optimisation method is an application of the Simulated Annealing meta-heuristic. Some numerical applications are proposed, specifically analysing 'two step' optimisation (synchronisation), and'one step' optimisation (scheduled synchronisation), for off-line (pre-timed strategy) and on-line applications (on-line computation strategy). A grid network was considered as case study and the effectiveness of the proposed strategies were evaluated by comparing the obtained results with those computed through commercial (benchmark) and in-house codes

Real-time smoothing of car-following data through sensor-fusion techniques

AbstractObservation of vehicles kinematics is an important task for many applications in ITS (Intelligent Transportation Systems). It is at the base of both theoretical analyses and application developments, especially in case of positioning and tracing/tracking of vehicles, car-following analyses and models, navigation and other ATIS (Advanced Traveller Information Systems), ACC (Adaptive Cruise Control) systems, CAS and CWS (Collision Avoidance Systems and Collision Warning Systems) and other ADAS (Advanced Driving Assistance Systems). Modern technologies supply low-cost devices able to collect time series of kinematic and positioning data with medium to very high frequency. Even more data can be (almost continually) collected if vehicle-to-vehicle (V2V) communications come true. However, some of the ITS applications (as well as car-following models, on which many ADAS and ACC are based) require highly accurate measures or, at least, smooth profiles of collected data. Unfortunately, even relatively high-cost devices can collect biased data because of many technical reasons and often this bias could lead to unrealistic kinematics, incorrect absolute positioning and/or inconsistencies between vehicles (e.g. negative spacing). As a consequence, data need filtering in most of the ITS applications. To this aim proper algorithms are required and several sensors and sources of data possibly integrated in order to obtain the maximum quality at the minimal cost. This work addresses the previous issues by developing a specific Kalman smoothing approach. The approach is developed in order to deal with car-following conditions but is conceived to take into account also navigation issues. The performances are analysed with respect to real-world car-following data, voluntarily biased for evaluation purposes. Assessment is carried out with reference to different mixtures of sensors and different sensors accuracies

Estimating an Injury Crash Rate Prediction Model based on severity levels evaluation: The case study of single-vehicle run-off-road crashes on rural context

Abstract In general in case of crash situations the quality of collected data is very limited and several information are usually unreliable. Thus it is recognised that a significant effort is required in order to improve the quality of the crash prediction models moreover a crucial role is played by the identification of the factors influencing the crashes occurrence and the levels of severity estimation. In this paper two injury crash rate prediction models related to single-vehicle run-off-road crashes type are calibrated and in particular significant attributes estimated are identified not only with roadway geometric characteristics and surface conditions, but also with gender/number-of-drivers. To this aim a survey of injury crashes on two-lane rural roads collected in the Southern Italy was considered and analysed. Finally before the calibration step, a preliminary analysis of the data was provided through the estimation of the levels of severity by multinomial logit; in fact by this model only segments with highest values of severity are identified and involved in the calibration procedure

Centralised Traffic Control and Green Light Optimal Speed Advisory Procedure in Mixed Traffic Flow: An Integrated Modelling Framework

The paper aims to develop an integrated modelling framework for urban network traffic control in the presence of connected and autonomous vehicles (CAVs). The framework is further composed of two sub models: the first of which focuses on the traffic control problem in the case of hybrid flow conditions (unequipped vehicles and connected vehicles) and the second aims to control the automated vehicles in terms of speed optimisation. The traffic control strategy drew on the hybrid combination between the centralised approach based on a multi-objective optimisation and a link metering based on a single control function; whilst with reference to the speed guidance, the GLOSA (Green Light Optimal Speed Advisory) procedure was considered. Furthermore, the presence of connected vehicles has also been considered to support the estimation procedure of location and speed of unequipped vehicles. In terms of traffic flow modelling the microscopic approach has been applied. The proposed framework was applied by considering a simple real network (in the city centre of Naples, in the Southern of Italy) that was composed by one origin–destination pair and two alternative paths. The network layout is characterised by one diversion node and two alternative paths connecting the same origin - destination pair; three scenarios were tested: the first was only based on a centralised traffic control procedure, the second on speed guidance optimisation and the third was based on the combination of both sub-models. Finally, the framework effectiveness was analised in terms of within-day dynamics with respect to the travel times and queue length performance indices

Penile Length Assessment of Children Treated for Primary Buried Penis: Can Satisfying Penile Growth Always Be Achieved?

Primary buried (BP) penis is describes as a small penis caused by a penile ligaments anomaly; it is unclear if a primary BP could reach a normal length. We selected 49 patients treated at our institution between 2015 and 2020 in order to post-operatively evaluate the SPL after one year. SPL was evaluated according to the PH Tanner staging system for pre-pubertal patients according to age-normalized values. A micropenis was detected if the SPL was below 2.5 SD. A normal SPL was found in thirty-two patients, eighteen were in PH Stage 1, four were in PH Stage 2, six were in PH Stage 3, and four were in PH Stage 5. Seventeen patients showed a reduced SPL; in seven of these (four in PH Stage 4 and three in PH Stage 5), their SPL was <2.5 ST. The difference in micropenis prevalence between the pre-pubertal and post-pubertal patients was significant (p = 0.038). A primary BP grows normally during the pre-pubertal period, where patients frequently showed a normal SPL, but it seems to be unable to reach a normal length in the higher PH stages, where the SPL is used to detect a micropenis. We suggest that a primary BP should be considered not as a simple defect of the penile ligaments and surrounding tissues, but as an incomplete manifestation of a micropenis due to a growth slowdown of the organ in late puberty

Accuracy of Micro-Computed Tomography in Post-mortem Evaluation of Fetal Congenital Heart Disease. Comparison Between Post-mortem Micro-CT and Conventional Autopsy.

Aims: Early prenatal diagnosis of congenital heart disease is feasible. Conventional autopsy is the current gold standard method for post-mortem confirmation. Radiologic techniques alternative to conventional autopsy, such as post-mortem micro-computed tomography, have been proposed in case of limited diagnostic accuracy (i.e., early termination of pregnancy, samples of small dimension or of low weight). The aim of the present study was to define accuracy of micro-computed tomography for post-mortem diagnosis of congenital heart disease in gross anatomy samples.Methods and Results: Fetal heart underwent in-utero prenatal echocardiography and ex-vivo post-mortem evaluation by 9 μm resolution micro-computed tomography and conventional autopsy. For each case, 25 indices of cardiac anatomy were studied by post-mortem micro-computed tomography and conventional autopsy; these were used to compare the two post mortem techniques. Ten samples were examined (gestational age between 12 + 4 and 21 + 6 weeks of gestation). Considering comparable indices, agreement between post-mortem micro-computed tomography and conventional autopsy was of 100% and sensitivity and specificity were of 100%. In “challenging specimens,” post-mortem micro-computed tomography diagnoses more indices as compared to conventional autopsy and 84% of “not-diagnostic” indices at conventional autopsy would be diagnostic at post-mortem micro-computed tomography.Conclusion: Micro-computed tomography can be a valid diagnostic alternative to conventional autopsy for post-mortem evaluation of human fetal heart. In addition, it may prove superior to conventional autopsy particularly in cases coming from early termination of pregnancy or in samples of small dimension or of low weight