考量混合車流污染排放濃度影響之適應性號誌控制模式

Adaptive Signal Control Model with Consideration of Emission Concentration under Mixed Traffic Flow Conditions

吳怡潔

指導教授 ： 邱裕鈞 ； Chiou, Yu-Chiun

國立交通大學/管理學院/交通運輸研究所/碩士(2012年)

https://doi.org/10.6842/NCTU.2012.00323

摘要

由於交通排放為能源消耗以及空氣污染主要來源，因此，建構一個可以有效模擬車輛污染的模式有其必要性。本研究建構一考量混合車流污染排放濃度影響之適應性號誌控制模式，此模式可即時偵測路側地區之污染值，甚至在敏感區域(例如醫院、學校)的偵測，其控制結果能使污染值在某一門檻之下，以降低污染濃度對於路側地區的影響。本研究將以污染排放做為績效值，並著重討論污染排放經由大氣擴散後成污染濃度對於路側地區之影響。
本研究模式建構包含四大模式：車流模式、車輛排放推估模式、污染擴散模式、適應性號誌控制模式。然而為了因應國內的機、汽車混合車流運作特性，本研究將使用混合車流格位傳遞模式(mixed traffic cell transmission models, MCTM)做為車流背景運作；並以環保署的TEDS 7.0線源排放資料庫做為車輛排放量推估依據；在計算污染濃度值上則選用高斯煙陣模式(Gaussian puff dispersion model)進行空間與時間上的推估；最後以基因模糊邏輯控制模式(Genetic fuzzy logic controller, GFLC)建構即時號誌控制系統，並以車輛到達率以及車輛等候長度作為狀態變數、綠燈延長秒數為控制變數、車輛排放量為控制績效指標。
本研究模式應用之GFLC控制結果將與定時號制做比較，在模擬時間兩小時中，GFLC皆比定時號制有效降低0.3%到25.3%的濃度值，表示路側受體感受到的污染濃度值整體都降低。確認GFLC模式後，本研究進一步設定污染濃度門檻限制模式，並研擬三種獨立路口號誌控制策略：1.固定號誌周期變動紅綠燈，2.固定綠燈變動號誌周期，3.固定綠燈時比變動號誌周期；而得到當幹道綠燈越長，以及週期越短的號誌設定，其路側污染較受到控制的結論。在連續路段情境中，本研究設定五路口路段，並將敏感區域設於下游路口4與路口5之間，擬定五路口全連鎖、下游三路口(靠近敏感區域)連鎖、以及全部獨立不連鎖三種號誌策略；策略結果顯示全連鎖設定為最佳，可將路側敏感區域濃度值降至最低。

關鍵字

適應性號誌控制 ； 基因模糊邏輯控制 ； 混合車流格位傳遞模式 ； 污染排放 ； 污染擴散濃度

並列摘要

Since road traffic is one of major sources of air pollution, a model which can replicate traffic behaviors, traffic emissions, emission dispersion so as to serve as the platform for evaluating or optimizing traffic control strategies deems necessary. Based on this, this study develops and optimizes an adaptive signal control model which can minimize the total traffic emissions and control the pollution concentration at road-side environmental sensitive areas (such as hospitals or schools) under a certain preset threshold in order to reduce the environmental impact of road traffic.

The proposed model comprising four key sub-models: traffic flow model, traffic emission model, emission dispersion model, and adaptive traffic control model. To acknowledge the prevalence of mixed traffic conditions in unban streets in Taiwan, the mixed traffic cell-transmission model (MCTM) is adopted. Additionally, this study uses the TEDS 7.0 line source emissions database as the basis of emission estimation and the Gaussian puff dispersion model to simulate the pollution dispersion and to predict the concentration temporally and spatially. The genetic fuzzy logic controller (GFLC) is used for real-time signal control by using the arrival rate and queue lengths as the state variables and the extension of green time as the control variables towards the minimization of traffic emissions.

This study compares the performances of the GFLC model and pre-timed signal control system. With two-hour simulation, the results show that the GFLC model can effectively curtail the spatiotemporal concentration values of the pre-timed signal control system by 0.3% to 25.3%. As to the control logics for concentration control, three strategies for isolated intersection are compared: 1. Vary green split by fixing cycle length, 2. Vary cycle length by fixing green time, and 3. Vary the cycle length by fixing green spilt. The comparing results show that as the green time is longer or the cycle length is shorter, the concentration of road-side sensitive area becomes less severe. For the consecutive intersections (a case study on five intersections), three strategies for arterial signal control are compared: 1. Coordinated signal for all intersections, 2. Coordinated the signal of downstream three intersections (close to sensitive areas), and 3. Without coordination. The results show that the coordinated signal for all intersections perform best. The applicability of the proposed model has been proven.

並列關鍵字

Adaptive signal control ； genetic fuzzy logic controller(GFLC) ； mixed traffic cell-transmission model(MCTM) ； emission dispersion ； pollution concentration

參考文獻

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