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In this paper, we present the "Slow Start Problem" in participatory sensing applications where a service is provided based on data collected by participants. The slow start problem refers to the initial stage in participatory sensing service deployment, during which service adoption remains sparse and, hence, the collected data does not offer adequate coverage. Predictive models, learned...
Ability to model and predict the fuel consumption is vital in enhancing fuel economy of vehicles and preventing fraudulent activities in fleet management. Fuel consumption of a vehicle depends on several internal factors such as distance, load, vehicle characteristics, and driver behavior, as well as external factors such as road conditions, traffic, and weather. However, not all these factors may...
Predictive operational strategies enable fuel savings by optimizing the powertrain operation of a vehicle taking lookahead data like velocity limits and slopes of the planned route into account. Gear changes, free-wheeling, speed and operational modes are optimized along that route to achieve minimal fuel consumption. However, these optimizations assume complete information on the route properties...
Advanced driver assistant systems (ADAS) like adaptive cruise control (ACC) are primarily developed to increase safety and driving comfort and nowadays applied to upper class production vehicles. Additional benefits like improvement of fuel economy is a widespread field in research. In this paper a fuel efficient predictive adaptive cruise control (PACC) approach is performed experimentally with a...
In this paper a cooperative adaptive cruise control approach using stochastic, linear model predictive control strategies is presented. The presented approach deals with an urban traffic environment where vehicle to vehicle and vehicle to infrastructure communication systems are available. The goal is the minimization of a vehicle's fuel consumption in a vehicle-following scenario. This is achieved...
Start-stop system of an internal combustion system of a hybrid drive is designed to reduce energy consumption of the drive and reduce the produced emissions. Effectiveness of the start-stop system heavily depends on its ability to correctly predict when the combustion engine will be idle. This makes the problem suitable for model predictive control. In this contribution, we study the case of a hybrid...
Models for predicting vehicular emissions of carbon dioxide (CO2) are usually insensitive to vehicle modes of operation (such as cruise, acceleration, deceleration, and idling) as they are based on the average speed of motor vehicles. In the present study, real world on-road second-by-second data are used to improve the accuracy of air quality models by considering modal emissions of CO2 in terms...
The deployment of predictive driving styles reduces fuel consumption of vehicles significantly, while assistance systems can support drivers in this task. This paper describes a modular approach to consider various sources of information as well as different driver and vehicle types in the prediction and the optimization of the vehicle's longitudinal dynamics to reduce fuel consumption. Energy efficient...
Reducing exhaust emissions is one of the biggest challenges facing the automotive engineering community today. In order to comply with future more stringent emission standards, the air-fuel ratio control must be improved. Commonly used control concepts do not account for the oxygen storage ability of the three-way catalyst, even though the storage state mainly influences post-catalyst exhaust emissions...
A vehicle predictive eco-cruise control system is developed that minimizes vehicle fuel consumption levels utilizing roadway topographic information. The predictive eco-cruise control system consists of three components: a fuel consumption model, a powertrain model, and an optimization algorithm. The developed system generates an optimal vehicle control plan using anticipated roadway grade information...
In order to assess environmental impacts of local traffic flow, a two-stage parameter tuning approach is proposed for recalibration of the Comprehensive Modal Emission Model (CMEM) using on-road emission measurements collected in Chinese cities. Based on the procedure comprising of grid search and nonlinear simplex optimization, the fuel- and emission-related parameters in the model are estimated...
Ecological driving aiming at optimizing energy consumption is highly desirable for sustainable intelligent transportation systems. This paper presents a unique development of ecological vehicle driving system in model predictive approach. The vehicle's fuel consumption model and the model based anticipation of future road-traffic situations are used in this rigorous reasoning approach of deriving...
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