怡萱 asked in 社會與文化語言 · 1 decade ago

英翻中,請幫我翻翻”APC Data”這一篇

請不要用翻譯器直接翻哦!謝謝!

Prediction Model of Bus Arrival and Departure Times Using AVL and APC Data.

Abstract

The emphasis of this research effort was on using AVL and APC dynamic data to

develop a bus travel time model capable of providing real-time information on bus

arrival and departure times to passengers (via traveler information services) and to

transit controllers for the application of proactive control strategies. The developed

model is comprised of two Kalman filter algorithms for the prediction of running

times and dwell times alternately in an integrated framework. The AVL and APC

data used were obtained for a specific bus route in Downtown Toronto. The performance

of the developed prediction model was tested using “hold out” data and other

data from a microsimulation model representing different scenarios of bus operation

along the investigated route using the VISSIM microsimulation software package.

The Kalman filter-based model outperformed other conventional models in

terms of accuracy, demonstrating the dynamic ability to update itself based on new

data that reflected the changing characteristics of the transit-operating environment.

A user-interactive system was developed to provide continuous information on the

expected arrival and departure times of buses at downstream stops, hence the expected

deviations from schedule. The system enables the user to assess in real time transit stop-based control actions to avoid such deviations before their occurrence,

hence allowing for proactive control, as opposed to the traditional reactive control,

which attempts to recover the schedule after deviations occur.

1 Answer

Rating
  • 魔神
    Lv 5
    1 decade ago
    Best Answer

    你好!

    以下為我個人英文程度所翻過來的解釋

    預測模型的巴士抵達和啟程時間利用定位和APC數據。

    摘要

    強調這項研究工作是利用定位和APC動態數據

    制定一個巴士旅行時間模型能夠提供實時信息總線

    抵港及離港時間的乘客(通過旅客信息服務)和

    過境控制器應用主動控制策略。發達國家

    模型是由兩個卡爾曼濾波算法的預測運行

    時間和駐留時間輪流在一個綜合框架。船隻和裝甲運兵車

    使用的數據,獲得特定巴士路線在多倫多市中心。性能

    發達國家預測模型進行了測試使用“舉行了”數據和其他

    數據從微觀模擬模型代表不同情景的巴士運作

    沿調查路線使用VISSIM微觀軟件包。

    卡爾曼濾波模型優於其他常規模式

    術語的準確性,體現了動態的自我更新能力的基礎上新

    數據反映了不斷變化的特點,過境的經營環境。

    用戶互動系統,提供不間斷的信息

    預計抵港及離港時間的巴士站上下游,因此預期

    偏離附表。該系統使用戶可以實時評估過境的控制行動,以避免這種偏離發生之前,

    因此,允許積極的控制,而不是傳統的被動控制,

    試圖恢復後的時間安排出現偏差。

    回答完畢

    Source(s):
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