| 31. |
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| 32. |
- Sandberg, David, 1980, et al.
(författare)
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The Characteristics of Sleepiness During Real Driving at Night - A Study of Driving Performance, Physiology and Subjective Experience
- 2011
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Ingår i: Sleep. - 1550-9109 .- 0161-8105. ; 34:10, s. 1317-1325
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Tidskriftsartikel (refereegranskat)abstract
- Study Objectives: Most studies of sleepy driving have been carried out in driving simulators. A few studies of real driving are available, but these have used only a few sleepiness indicators. The purpose of the present study was to characterize sleepiness in several indicators during real driving at night, compared with daytime driving. Design: Participants drove 55 km (at 90km/h) on a 9-m-wide rural highway in southern Sweden. Daytime driving started at 09: 00 or 11: 00 (2 groups) and night driving at 01: 00 or 03: 00 (balanced design). Setting: Instrumented car on a real road in normal traffic. Participants: Eighteen participants drawn from the local driving license register. Interventions: Daytime and nighttime drives. Measurement and Results: The vehicle was an instrumented car with video monitoring of the edge of the road and recording of the lateral position and speed. Electroencephalography and electrooculography were recorded, together with ratings of sleepiness every 5 minutes. Pronounced effects of night driving were seen for subjective sleepiness, electroencephalographic indicators of sleepiness, blink duration, and speed. Also, time on task showed significant effects for subjective sleepiness, blink duration, lane position, and speed. Sleepiness was highest toward the end of the nighttime drive. Night driving caused a leftward shift in lateral position and a reduction of speed. The latter two findings, as well as the overall pattern of sleepiness indicators, provide new insights into the effects of night driving. Conclusion: Night driving is associated with high levels of subjective, electrophysiologic, and behavioral sleepiness.
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| 33. |
- Sandberg, David, 1980, et al.
(författare)
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The impact of sleepiness on lane positioning in truck driving
- 2013. - 1
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Ingår i: Driver Distraction and Inattention. - Farnham : Ashgate. - 9781409425854 - 9781315578156 ; 1, s. 405-416
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Bokkapitel (refereegranskat)abstract
- This chapter concerns the detection of sleepiness in truck drivers. Data obtained from a driver sleepiness study involving real-world driving are used in order to analyse the performance of several sleepiness indicators based on driving behavior; such as, for example, variability in lateral position and heading angle. Contrary to the results obtained for passenger cars, for heavy trucks it is found that indicators based on variability provide little or no information; their performance does not rise significantly above chance levels.However, the data indicate that there is a significant difference in the average lane position for sleepy and alert drivers, respectively, such that a sleepy driver generally places the vehicle closer (by about 0.2 m) to the centre of the road than an alert driver. The analysis also shows a significant, monotonous, increase in average lateral position (measured from the right, outer, lane boundary towards the lane centre) between the four cases of (i) daytime alert driving, (ii) daytime sleepy driving, (iii) night-time alert driving and (iv) nighttime sleepy driving.
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| 34. |
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| 38. |
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| 39. |
- Torabi, Sina, 1990, et al.
(författare)
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A method for performance analysis of a genetic algorithm applied to the problem of fuel consumption minimization for heavy-duty vehicles
- 2019
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Ingår i: Applied Soft Computing Journal. - : Elsevier BV. - 1568-4946. ; 80, s. 735-741
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a general method for assessment of the performance of a genetic algorithm (GA)in cases where the global optimum of the objective function is unknown. The method involves discretization of the search space, making it possible to apply a brute force calculation to find the global optimum for the discretized case. Then, this method is used to study the performance of a GA applied to the problem of speed profile optimization for heavy-duty vehicles, in which the optimization must be carried out within a rather short time. In this performance analysis, the discretization involves generating speed profiles as piecewise linear functions. It is demonstrated that the GA is able to find near-optimal solutions for the cases considered here: The speed profiles generated by the GA have objective function values that are typically within 2% of the global optimum.
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| 40. |
- Torabi, Sina, 1990, et al.
(författare)
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Energy minimization for an electric bus using a genetic algorithm
- 2020
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Ingår i: European Transport Research Review. - : Springer Science and Business Media LLC. - 1867-0717 .- 1866-8887. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Background and methods: This paper addresses, in simulation, energy minimization of an autonomous electric minibus operating in an urban environment. Two different case studies have been considered, each involving a total of 10 different 2?km bus routes and two different average speeds. In the proposed method, the minibus follows an optimized speed profile, generated using a genetic algorithm. Results: In the first case study the vehicle was able to reduce its energy consumption by around 7 to 12% relative to a baseline case in which it maintains a constant speed between stops, with short acceleration and deceleration phases. In the second case study, involving mass variation (passengers entering and alighting) it was demonstrated that the number of round trips that can be completed on a single battery charge is increased by around 10% using the proposed method.
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