Currently my research activities are focused on freeway traffic management, traffic safety and shared vehicle systems.
Cooperative freeway driving strategies in a mixed environment – autonomous and traditional vehicles
Automatic driving is evolving quickly and highly autonomous cars will be a reality in the next decade. Today, research on driverless cars is mostly vehicle centric. However, in order to obtain all the potential benefits of autonomous cars, in terms of traffic efficiency, traffic management strategies will be more important than ever before. In this context, cooperative driving appears as a way to go. Autonomous vehicles will need to cooperate in order to be globally efficient. One possible strategy of cooperative management of driverless cars would allow creating dense vehicle platoons, with very small spacings emulating a physical linkage between them and creating “road trains”. With such management, autonomous driving will be, not only safe and convenient, but also efficient.
My research in this topic aims to develop a macroscopic traffic model able to reproduce the mixed lane behavior for different penetration levels of autonomous vehicles and platooning. The result will be a robust model, based on few parameters, allowing to identify the existing trade-offs and the best management strategies. This analytical model will be programmed into a mesoscopic simulator, in order to ease the assessment of the proposed strategies on realistic environments.
PATH 1997 Automated Vehicle Platoon Demo on I-15 San Diego
This research is partially funded by the Spanish Ministry of Economy, Industry and Competitiveness, within the National Programme for Research Aimed at the Challenges of Society (grant ref. TRA2016-79019-R).
Freeway traffic management
With the collaboration of the Servei Català del Trànsit (the Catalan Traffic Administration), we developed a real size experiment regarding dynamic speed limits (DSL) on freeways. We built a highway lab on a 13km stretch of the B-23 freeway, accessing the city of Barcelona from the west. Inductive loop detectors, non-intrusive traffic detectors, TV cameras and license plate recognition devices were used to measure detailed traffic data (including lane changing activity) in different speed limit contexts. During a total of 7 weekdays, we used the dynamic speed signals installed on the freeway (approx. every km) in order to create completely different contexts and assess the effects of DSL on the traffic stream. We finished the experiment by the end of June 2013 and we are now working on the resulting database. Our intention is to make these priceless data publicly available to the whole research community. Here you can find the experiment description.
Modeling shared vehicle systems
This line of research aims to model shared vehicle systems at strategic and tactical levels. The objective is to obtain a simple model that establishes the existing trade-offs between the agency costs (i.e. vehicle fleet, stations, repositioning costs) and the user costs (i.e. access, wait and no service penalties). This would allow optimizing the main strategic and tactic variables of the system (i.e. total number of vehicles, density of stations; size of each station, vehicle occupancy at each station after a complete rebalancing period, etc). Also, the model will be able to assess different system configurations, like free-floating versus station-based implementations. Alternatively, for given values of these variables (e.g. for actual designs) the model will allow evaluating the key performance indicators of the system and its costs.
Currently the model is being applied to bike sharing systems (e.g. the Bicing system in Barcelona) and to car-sharing implementations. In both applications, the additional restrictions due to the use of an electrical fleet of vehicles is considered. A second phase of the research will consist on the development of a simulation model suitable for the fine tuning or the original macro solution.
I am also working on the development of a driver feedback mobile app. The idea is to use the smartphones’ capabilities in order to monitor the driving performance. This would allow providing feedback to the driver, making evident his faults and risks. With some guidelines, this will help in achieving a more safe and sustainable driving. Special attention is paid to develop a motorbike friendly app, in order to address this vulnerable group of drivers with high accident rates in Catalonia.
This research project was recipient of a mobility fellowship under the NILS Science and Sustainability Programme for Individual Mobility (ABEL‐IM‐2014B: Driver Feedback Mobile APP – A tool for road safety improvement).