عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
شماره کتابشناسی ملی
شماره
TL06q0s89w
زبان اثر
زبان متن نوشتاري يا گفتاري و مانند آن
انگلیسی
عنوان و نام پديدآور
عنوان اصلي
A Dynamic Advisory Speed Limit Algorithm of Eco-Driving Strategies Based on Phase Time Control
نام عام مواد
[Thesis]
نام نخستين پديدآور
fan, ximeng
نام ساير پديدآوران
Jin, Wenlong
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
UC Irvine
تاریخ نشرو بخش و غیره
2020
یادداشتهای مربوط به پایان نامه ها
کسي که مدرک را اعطا کرده
UC Irvine
امتياز متن
2020
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
The concept of eco-driving is based on environmental factors such as fuel consumption. A large number of existing studies have proven the effectiveness of eco-driving in environmental protection. However, there still lacks a clear understanding of the impacts of eco-driving on overall performance of a signalized road network at different congestion levels. In this paper, we systematically study the impacts of a green driving strategy based on the advisory speed limit (ASL) to smooth the vehicle trajectories. We first analyze the limitations of the static ASL algorithm and propose the dynamic ASL algorithm based on it. We then review the car-following models, including Newell's car-following model, BA Newell's car-following and intelligent driver model (IDM), that we utilize for simulating vehicle movements. For evaluation, we introduce network fundamental diagrams (NFD) and fuel consumption as indicators to measure the efficiency of our algorithm. With numerical results, we demonstrate that our dynamic ASL can change the start-up and clearance behaviors so as to smooth vehicles' trajectories and improve system mobility. In particular, it mainly plays a role under saturated conditions; with proper car-following models, capacity can be increased by up to 40% and fuel consumption can be reduced by up to 25%. We further demonstrate that our algorithm is effective cooperatively for different market penetration rates (MPR) of connected vehicles and work out a proper range of the ASL implementation area. Our algorithm can make a contribution even when 5% of the vehicles adopt our algorithm, with a higher MPR, it can be increasingly more efficient; and the recommended ASL implementation area is in the range of 100 meters to 150 meters. In the future, we are interested in extending our idea for over-saturated conditions and some more complicated transportation systems.
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
fan, ximeng
نام شخص - ( مسئولیت معنوی درجه دوم )
مستند نام اشخاص تاييد نشده
Jin, Wenlong
شناسه افزوده (تنالگان)
مستند نام تنالگان تاييد نشده
UC Irvine
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب وضعیت انتشار
فرمت انتشار
p
اطلاعات رکورد کتابشناسی
نوع ماده
[Thesis]
کد کاربرگه
276903
اطلاعات دسترسی رکورد
سطح دسترسي
a
تكميل شده
Y
