Data Collection for Traffic and Drivers’ Behaviour Studies: A Large-scale Survey

AbstractStudies of driving behaviour are of great help for different tasks in transportation engineering. These include data collection both for statistical analysis and for identification of driving models and estimation of modelling parameters (calibration). The data and models may be applied to different areas: i) road safety analysis; ii) microscopic models for traffic simulation, forecast and control; iii) control logics aimed at ADAS (Advanced Driving Assistance Systems). In this paper we present a large survey based on the naturalistic (on-the-road) observation of driving behaviour with a view to obtaining microscopic data for single vehicles on long road segments and for long time periods. Data are collected by means of an instrumented vehicle (IV), equipped with GPS, radar, cameras and other sensors. The behaviour of more than 100 drivers was observed by using the IV in active mode, that is by observing the kinematics imposed on the vehicle by the driver, as well as the kinematics with respect to neighbouring vehicles. Sensors were also mounted backwards on the IV, allowing the behaviour of the driver behind to be observed in passive mode. As the vehicle behind changes, the next is observed and within a short period of time the behaviour of several drivers can be examined, without the observed driver being aware. The paper presents the experiment by describing the road context, aims and experimental procedure. Statistics and initial insights are also presented based on the large amount of data collected (more than 8000km of observed trajectories and 120hours of driving in active mode). As an example of how to use the data directly, apart from calibration of driving behaviour models, indexes based on aggregate measures of safety are computed, presented and discussed

Human-like Adaptive Cruise Control systems through a learning machine approach

In this work a learning machine model is proposed in order to develop an Adaptive Cruise Control (ACC) system with human-like driving capabilities. The system is based on a neural network approach and is intended to assist the drivers in safe car-following conditions. The proposed approach allows for an extreme flexibility of the ACC that can be continuously trained by drivers in order to accommodate their actual driving preferences as these changes among drivers and over time. The model has been calibrated against accurate experimental data consisting in trajectories of vehicle platoons gathered on urban roads. Its performances have been compared with those of a conventional car-following model

A system of location models for the evaluation of long term impacts of transport policies

In this article an analytical model able to deal with the complex interactions among the activities of an urban system is presented. The model is based on a consistent and rigorous analytical framework, where the urban pattern results from the location choices of various decision-makers. The model ca be stated in a disaggregate from where choices are simulated within a behavioral framework based on the random utility theory. Aggregation issues can also be consistently treated. An operative specification of the model is also presented, as well as its application to the urban area of Naples

I progetti europei: AIUTO

Vengono presentati i principali risultati di un progetto di ricerca europeo (AIUTO) finalizzato a studiare e dimostrare le potenzialità di politiche di controllo della domanda (Travel Demand Management). Particolare attenzione viene dedicata ai risultati dell'implementazione di tali politiche sul test-site della città di Salerno

Modelli di assegnazione e progettazione delle informazioni

Si approfondiscono gli effetti indotti sul traffico dalla presenza di un sistema ATIS (Advanced Traveller Information System) e si propongono formalizzazioni modellistiche utili a trattare il problema sia in caso di informazione predittiva e congruente che in presenza di diverse strategie di informazione. I modelli proposti evidenziano il ruolo e le modalità di rappresentazione modellistica del cosiddetto problema della anticipatory route guidance