References of "IEEE Intelligent Transportation Systems Magazine"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailEcological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in IEEE Intelligent Transportation Systems Magazine (2018)

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and ... [more ▼]

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a real-time risk-sensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behavior to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction. [less ▲]

Detailed reference viewed: 196 (8 UL)
Full Text
Peer Reviewed
See detailLuxembourg SUMO Traffic (LuST) Scenario: Traffic Demand Evaluation
Codeca, Lara UL; Frank, Raphaël UL; Faye, Sébastien UL et al

in IEEE Intelligent Transportation Systems Magazine (2016)

Both the industrial and the scientific communities are working on problems related to vehicular traffic congestion, intelligent transportation systems, and mobility patterns using information collected ... [more ▼]

Both the industrial and the scientific communities are working on problems related to vehicular traffic congestion, intelligent transportation systems, and mobility patterns using information collected from a variety of sources. Usually, a vehicular traffic simulator, with an appropriate scenario for the problem at hand, is used to reproduce realistic mobility patterns. Many mobility simulators are available, and the choice is made based on the type of simulation required, but a common problem is finding a realistic traffic scenario. The aim of this work is to provide and evaluate a scenario able to meet all the basic requirements in terms of size, realism, and duration, in order to have a common basis for evaluations. In the interest of building a realistic scenario, we used information from a real city with a typical topology common in mid-size European cities, and realistic traffic demand and mobility patterns. In this paper, we show the process used to build the Luxembourg SUMO Traffic (LuST) Scenario, and present a summary of its characteristics together with our evaluation and validation of the traffic demand and mobility patterns. [less ▲]

Detailed reference viewed: 410 (52 UL)
Full Text
Peer Reviewed
See detailDriver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring
Castignani, German UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

in IEEE Intelligent Transportation Systems Magazine (2015), 7(1), 91-102

Today's smartphones and mobile devices typically embed advanced motion sensors. Due to their increasing market penetration, there is a potential for the development of distributed sensing platforms. In ... [more ▼]

Today's smartphones and mobile devices typically embed advanced motion sensors. Due to their increasing market penetration, there is a potential for the development of distributed sensing platforms. In particular, over the last few years there has been an increasing interest in monitoring vehicles and driving data, aiming to identify risky driving maneuvers and to improve driver efficiency. Such a driver profiling system can be useful in fleet management, insurance premium adjustment, fuel consumption optimization or CO2 emission reduction. In this paper, we analyze how smartphone sensors can be used to identify driving maneuvers and propose SenseFleet, a driver profile platform that is able to detect risky driving events independently from the mobile device and vehicle. A fuzzy system is used to compute a score for the different drivers using real-time context information like route topology or weather conditions. To validate our platform, we present an evaluation study considering multiple drivers along a predefined path. The results show that our platform is able to accurately detect risky driving events and provide a representative score for each individual driver. [less ▲]

Detailed reference viewed: 602 (50 UL)