Giuseppe Guido

Comparing Safety at Signalized Intersections and Roundabouts Using Simulated Rear-End Conflicts

The safety implications of adopting roundabouts in place of conventional signalized intersections have not been adequately assessed. A microscopic simulation model was used to compare the pattern of traffic conflicts at roundabouts with conflicts for signalized intersections. Three indicators of safety performance were defined: (a) time to collision (TTC), (b) deceleration rate to avoid the crash (DRAC), and (c) crash potential index (CPI). For each indicator, traffic conflict profiles were obtained in terms of number of vehicles in conflict and number of conflicts per vehicle for selected directional maneuvers. The exposure time to conflict for each maneuver and vehicle was also determined. Twelve combinations of geometric and traffic attributes (traffic scenarios) were simulated over a 15-min period. The results suggested that roundabouts yield reduced exposure times to rear-end conflicts compared with signalized intersections. On average, signalized intersections also reflected increased number of vehicles in conflict and percentage of vehicles in conflict compared with roundabouts. This relationship was found to be independent of input volumes and pavement surface condition and applied consistently to all safety indicator measures (TTC, DRAC, and CPI).

Comparing Safety Performance Measures Obtained from Video Capture Data

Safety performance is evaluated by using measures obtained experimentally from a videotaping of traffic operations at an urban roundabout situated in Cosenza, Italy. Five different expressions of safety performance from the perspective of “rear-end” vehicle interactions include maximum deceleration rate to avoid a crash (DRAC), time-to-collision (TTC), proportion of stopping distance (PSD), time integrated time-to-collision (TIT), and crash potential index (CPI). Differences in safety performance are discussed with respect to the type of measure, traffic conditions, and variations in roundabout geometry. The results of this analysis suggest that safety performance is highly sensitive to the way it is measured; different measures can highlight different locations or geometric features of the roundabout as posing potential safety problems. This study underscores the usefulness of safety performance measures for providing meaningful experimental indicators of potential safety problems at roundabouts and how ...

Motorway traffic parameter estimation from mobile phone counts

Abstract In this paper a new method for real time estimation of vehicular flows and densities on motorways is proposed. This method is based on fusing traffic counts with mobile phone counts. The procedure used for the estimation of traffic flow parameters is based on the hypothesis that “instrumented” vehicles can be counted on specific motorway sections and traffic flow can be measured on entrance and exit ramps. The motorway is subdivided into cells, assuming that mobile phones entering and exiting every cell can be counted during the observation period. An estimate of “instrumented” vehicle concentration is obtained and propagated on the network in time and space. This allows one to estimate traffic flow parameters by sampling “instrumented” traffic flow parameters using a “concentration” (the ratio of the densities of instrumented vehicles to the density of overall traffic) propagation mechanism.

A co-operative methodology to estimate car fuel consumption by using smartphone sensors

AbstractThe European Commission has recently promoted research programs aimed at finding solutions to the ever more compelling problem of air pollution from road vehicles and has also indicated a better sustainability among the possible impacts of co-operative Intelligent Transportation Systems. In fact, many practical solutions can be developed that allow drivers and management to optimise resources and to contain costs and the emissions of pollutants by applying communication systems between vehicles (Vehicle-to-Vehicle – V2V) and between vehicles and infrastructure (Vehicle-to-Infrastructure – V2I). Along this mainstream this paper present a co-operative system which offer drivers the ability to manage their consumption and driving style, suggesting corrections to the usually adopted behaviour. The new contribution of this paper is both the co-operative approach between drivers to achieve a common goal of a better common energy consumption strategy and a methodology to estimate fuel consumption just by...

Using Smartphones as a Tool to Capture Road Traffic Attributes

Road network management under critical conditions is achievable by adopting technologies that trace vehicles and capture unsafety events to provide users with real time traffic information. Most common approaches used to acquire vehicle tracking data are based on video image processing algorithms and satellite navigation systems. However, many studies are increasingly focused on the emerging smartphone technologies for tracking vehicles. The aim of this study is to present a procedure for acquiring vehicle tracking data from smartphone sensors, supporting managers of transportation systems to take effective decisions on their networks, especially in conjunction with special events and/or critical road safety issues.

Ecosmart and TutorDrive: Tools for fuel consumption reduction

The European Commission has recently promoted research programs aimed at finding solutions to the ever more compelling problem of air pollution from road vehicles and has also indicated among the possible impacts of cooperative Intelligent transportation a better sustainability, by cutting down pollutant emissions and reducing consumptions. In fact many practical solutions will develop that allow drivers and managements to optimize resources and to contain costs and the emissions of pollutants by applying communication systems between vehicles (V2V) and between vehicles and infrastructure (V2I). Along this mainstream this paper present a cooperative system which offer drivers the ability to manage their consumption and driving style, suggesting corrections to the behavior usually adopted. The new contribution of this paper is the cooperative approach between drivers to achieve a common goal of a better common energy consumption strategy. Since the fuel consumption has to be evaluated with regards to the specific vehicle type the system is based also on crowdsourcing of the specific vehicle consumption performances. The paper describes a system that gathers data on fuel consumption from the cooperating drivers that by can build together the data set necessary to the system itself and accept this new paradigm: crowd sourced cooperation for a better world.

Traffic data acquirement by unmanned aerial vehicle

ABSTRACT This paper presents a methodology aimed to acquire traffic flow data through the employment of unmanned aerial vehicles (UAVs). The study is focused on the determination of driving behavior parameters of road users and on the reconstruction of traffic flow Origin/Destination matrix. The methodology integrates UAV flights with video image processing technique, and the capability of geographic information systems, to represent spatiotemporal phenomena. In particular, analyzing different intersections, the attention of the authors is focused on users’ gap acceptance in a naturalistic drivers’ behavior condition (drivers are not influenced by the presence of instruments and operators on the roadway) and on the reconstruction of vehicle paths. Drivers’ level of aggressiveness is determined by understanding how drivers decide that a gap is crossable and, consequently, how their behavior is critical in relation to a moving stream of traffic with serious road safety implications. The results of these experiments highlight the usefulness of the UAVs technology, that combined with video processing technique allows the capture of real traffic conditions with a good level of accuracy.

Traffic Delays Estimation in Two-lane Highway Reconstruction

Abstract An increasingly important issue, as congestion levels increase more and more, is that freeways become subject to rebuilding and restructuring when traffic cannot be re-routed. It has already been asserted that traffic simulation provides a better approach to the analysis of freeway reconstruction than the traditional Highway Capacity Manual. In fact the users’ delay on freeway under reconstruction, when traffic flow is under capacity, cannot be evaluated by the standard HCM procedures. The impacts on existing traffic patterns are significant: the costs of delay and safety suffered by users even for low flows requires to take adequate management actions. From the point of view of direct reconstruction costs, every attempt to reduce user cost brings an increase in the direct costs of rebuilding. So there is a clear trade-off between reducing direct costs and mitigating the costs to travellers and economic activities. The object of this paper is to allow the evaluation of the delay that is suffered by the users of two-lane freeways when only one lane is available. The delays for different flow levels and different lengths of the reconstruction area are evaluated with the use of a tailored new developed microscopic traffic simulation model.

The Use of Adaptive Traffic Signal Systems Based on Floating Car Data

This paper presents a simple concept which has not been, up to now, thoroughly explored in scientific research: the use of information coming from the network of Internet connected mobile devices (on vehicles) to regulate traffic light systems. Three large-scale changes are going to shape the future of transportation and could lead to the regulation of traffic signal system based on floating car data (FCD): (i) the implementation of Internet connected cars with global navigation satellite (GNSS) system receivers and the autonomous car revolution; (ii) the spreading of mobile cooperative Web 2.0 and the extension to connected vehicles; (iii) an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety, and environmental issues. Up to now, the concept of floating car data (FCD) has only been extensively used to obtain traffic information and estimate traffic parameters. Traffic lights regulation based on FCD technology has not been fully researched since the implementation requires new ideas and algorithms. This paper intends to provide a seminal insight into the important issue of adaptive traffic light based on FCD by presenting ideas that can be useful to researchers and engineers in the long-term task of developing new algorithms and systems that may revolutionize the way traffic lights are regulated.

A smartphone based DSS platform for assessing transit service attributes

This paper presents a methodology for determining public transportation quality attributes, based on a decision support system (DSS). The platform, once set up, combines the capability of geographic information systems (GIS) to analyze spatial attributes and the smartphone mobile technology, which is a “smart” solution to collect dynamically bus locations and their cinematic variables. The DSS has been applied to a real case study in order to test its reliability. The results highlight a good flexibility of the platform combined with a good level of scalability and interoperability of the system that can be applied in any context. Moreover, the high penetration rate of smartphones among users and the system capability of disaggregating data in both space and time, makes the DSS useful to identify operational problems and take appropriate actions with a non-intrusive approach.