Driving-style estimation via Intertial Measurements (2009-2010)
mOve control team, Politecnico di Milano (Milan, Italy) and Teleparking Srl (Milan, Italy)
A massive usage of public transport systems gives a big contribution in term of pollution reduction thanks to the smaller ratio of fuel per passenger per kilometer compared to the private mobility. Bus is an example of public transport mean widely used in urban mobility. It is characterized by a big mass and, in the urban area, its average speed is usually low. In these conditions, the aerodynamic power is almost an order of magnitude less than the inertial power. So, how the driver accelerate and brake – the so-called driving style – has a direct impact on the fuel consumption, which corresponds to the emissions of CO2 and NOx. However, it affects the safety and the comfort of the passengers.
A method for the quantification of the driver-style economy and safety via the measurements of the longitudinal speed and the longitudinal and lateral acceleration has been developed.
Transportation mode identifcation and real-time CO2 emission estimation using smartphones (2010)
SENSEable City Lab, MIT (Cambridge, MA, USA) and SNCF (Paris, France)
In a context where one third of global CO2 emissions are generated by transportation, assessing an individual’s personal contribution to the emissions of a city becomes highly valuable. Prior eff orts in this direction have resulted in web-based CO2 emissions calculators, smartphone-based applications, and wearable sensors that detect a user’s transportation modes. Yet, high energy consumption and ad-hoc sensors have limited the potential adoption of these methodologies
We developed a method which estimates in real-time the CO2 emissions using inertial information gathered from mobile phone sensors. Then, user’s transportation mode is classified using a data mining technique based on Decision Trees. Integration of GPS readings and Google Maps queries allow to accurately compute the distance travelled with a small impact on the battery life. A working application for Google Android platform demonstrates the approach.
Project web page: http://senseable.mit.edu/co2go
Smartphone-based environment sensing and electric bicycle control for Copenhagen Wheel (2010)
SENSEable City Lab, MIT (Cambridge, MA, USA)
Copenhagen Wheel is a project from SENSEable City Lab. It turns a regular bicycle into an electric bicycle with energy regeneration and real-time environmental sensing capabilities. The wheel harvests the energy the user inputs while braking and cycling and stores it for when he/she needs a boost. At the same time, sensors in the wheel are collecting information about air and noise pollution, congestion and road conditions.
The mobile application for Google Android platform has been developed. The application allows the user to interact with the bike, changing gears or selecting the level of motor assistance. In the same time, the application senses and gathers information about the surroundings, such as values of carbon dioxide, noise, temperature and humidity through a wireless sensor. The data are than collected locally and let available for the user, both locally and through a web interface.
Project web page: http://senseable.mit.edu/copenhagenwheel
Smartphone Based Vehicle-to-Driver/Infrastructure Interaction System for Motorcycles (2008-2010)
mOve control team, Politecnico di Milano (Milan, Italy) and MV Agusta Motor Spa (Varese, Italy)
In the last decade the research interest in two wheels vehicles has been driven by two peculiar features: on one hand motorcycles are means for personal mobility with a low environmental impact. On the other hand they are responsible of about the 20% of road incidents. One of the possible solutions to ensure a better safety in a motorcycle is to increase the informative interaction between the vehicle and the driver. The problem of audio and video vehicle-to-driver interaction and remote maintenance have been tackled by several works, mainly focused on automobiles. The problems in motorcycles are less explored, although the interaction behavior between the vehicle and the driver is extremely different.
The object of this work is to study a system capable of implementing a bidirectional audio interaction with the driver and to provide a remote monitoring of the vehicle parameters. Both the audio and remote connection are based on a smart-phone connected wireless to the vehicle control unit by the means of a dedicated embedded electronic.
Implementation of the SAFESPOT architecture on a Powered Two-Wheeler vehicle (2008-2010)
mOve control team, Politecnico di Milano (Milan, Italy) and Piaggio & C. Spa (Pontedera, Italy)
The Safespot Integrate Project is a European co-founded project which aims to improve the awareness of the vehicle’s surrounding situation through a concurrent and synergic behavior between vehicle and infrastructure. The Safespot platform is composed by many sub-systems, among which the most important are the communication, the positioning and the scenario analysis. The communication is based on the standard IEEE 802.11p, designed for the requirements of Intelligent Transportation Systems. The positioning relies on GPS with differential correction. Finally, the scenario analysis is based on the data stored in a dynamic representation of the environment called Local Dynamic Map.
The research focuses on the implementation of the Safespot hardware architecture on a Powered Two-Wheeler vehicle (the Piaggio MP3), on the development of applications for the scenario analysis and on the design of a human-machine interface for motorcycles. Two use cases are considered: the lane change maneuver and the safe overtaking.