Predictive driving strategies under urban conditions for reducing fuel consumption based on vehicle environment information

Abstract

This brief deals with the improvement of a vehicle's pass-through of predictively known urban driving situations concerning its fuel consumption. Today's technology enables the prediction of information about traffic events. This information can be used to identify efficient driving strategies. The main aim is to reduce the dynamics in the velocity profiles of driving situations and with it the corresponding fuel consumption in urban traffic. An algorithm has been built to calculate fuel consumption optimized driving trajectories. Input parameters are temporal and spatial depending constraints of the driving situation as well as other restrictions like a speed-limit. The main objective of the function was to enable a situation adaptive reaction to every predictively known forthcoming traffic event. Thus an optimized driving trajectory can be steadily calculated for the next route section of the vehicle provided that predictive information about the traffic events are available. The higher the availability of information the better an optimization of the driving strategies will be possible.Fuel characteristics and other energetically relevant data for a real-world vehicle have been created by detailed simulation to evaluate the fuel consumption of the driving strategies. For demonstration purposes the common driving situation "traffic light" was chosen. The fuel consumption calculated for the predictive driving strategies is compared to the consumption of a simulated average driver without predictive information.The calculated potentials have been verified by measuring the fuel consumption of an experimental vehicle for the simulated driving strategies.

A Planning Tool to Assess Advanced Vehicle Sensor Technologies on Traffic Flow, Fuel Economy, and Emissions

“…In academic literature, these efficiency increases from simulations found in literature range from 10% [58], to 40% [61], for standard powertrain vehicles. Just as with V2V technology, V2I 40 technology can be integrated with an adaptive cruise control system and perform more efficient driving behaviors automatically.…”

“…Essentially, a driver of a vehicle is approaching an intersection that is about 20 seconds of travel away and the driver receives a message on their dashboard stating that the signal is red while also displaying the recommended speed with which to begin approaching this intersection. In addition, such systems could also display information on how long the traffic light will remain in that particular phase [58], [63]. This concept has been measured to improve fuel economy by 10% when tested on standard powertrain vehicles [58].…”

“…In addition, such systems could also display information on how long the traffic light will remain in that particular phase [58], [63]. This concept has been measured to improve fuel economy by 10% when tested on standard powertrain vehicles [58].…”

“…That is, the core technologies of data transfer are largely the same, but the data is transferred between vehicles and infrastructure sources such as traffic lights. This survey will highlight how V2I technology can enable a hybrid vehicle to have an awareness of infrastructure (such as changing stoplights) for a potential fuel economy benefit somewhere between 10-25% for standard powertrain vehicles [58], [59].…”

Cloud-Based Velocity Profile Optimization for Everyday Driving: A Dynamic-Programming-Based Solution

“…The authors used a short-range radar and traffic signal information to predictively schedule a suboptimal velocity trajectory and implemented the algorithm in an existing cruise control system. A similar approach was proposed by Raubitschek et al [12], where the authors divided the velocity profile into a number of modes and generated a velocity profile combined with these modes to ensure arrival at a green traffic light. In [13], we developed an analytical solution to generate an optimal velocity profile to minimize energy consumption on a given route with the existence of a single traffic light.…”