感知不確定性環境下之感知刺激-心理物理因素-跟車行為分析與模式

Abstract

車流狀況瞬息萬變，其巨觀車流現象均由微觀駕駛行為所構成，而駕駛者行為之 形成實為一既動態又複雜之刺激－反應之動態決策過程，涉及層面與因素甚廣。然過 去車流理論多就「工程」觀點構建車流模式，僅止於適用描述形於外之車流變化與型 態，多缺乏對駕駛者決策過程中其透過「視覺感官刺激」、「心理負荷」乃至「反應行 為」予以完整且有系統之描述與模式構建，簡言之，過去交通運輸於車流理論部分， 缺乏一駕駛者視覺刺激－心理感知－直覺反應－決策行為之完整聯結橋樑。故本四年 期之研究，主要將延續本人過去於智慧型運輸系統(ITS)微觀車流理論之發展，針對感 知不確定性環境下，進行一系列之微觀車流之跟車行為之研究。其中第1 年，將應用 視覺流刺激理論為基礎，重新檢視並分析駕駛者跟車行為中與視覺刺激及反應相關之 心理、生理影響因素，再據以構建一感知不確定性環境下之「刺激－反應式跟車行為」， 並藉由實驗與模式證明傳統跟車理論實僅為「刺激－反應式跟車行為模式」所描述之 跟車行為之一特例；第2、3 年之研究則進一步探索所構建之「刺激－反應式跟車行為 模式」中重要心理物理相關影響因素(包括反應時間、感知安全車間距、感知相對速度、 感知視覺流刺激強度、頻率等)，在駕駛人感知的不確定性下，是否亦在如量子力學之 「海森堡不確定性原理」(Heisenberg Uncertainty Principle)中所描述之某種消長關係 (trade-off relationship)，並進行模式構建及實驗設計；第4 年則進一步將外在環 境影響因素(如駕駛環境之明亮度)及駕駛者特性(如年齡、性別、駕駛時間等)加以考 量，探索量子不確定性下不同「駕駛環境」及「駕駛者特性」對駕駛行為之影響。本 四年期計畫期望能發展出一套完整之動態駕駛者視覺刺激－反應之駕駛行為模式，用 以解析並預測微觀車流行為，進而彌補過去車流理論部分，對於駕駛者心理及感官刺 激等因素對於駕駛行為之影響知識不足之部分。

A better understanding of psychophysical influencing factors of drivers and the resulting driving maneuvers in response to dynamic traffic phenomena is vital to the improvement of traffic flow theory and its applications in Intelligent Transportation Systems (ITS). This 4-year research project aims to propose a generalized car-following behavior model under driver perception uncertainties to explicate the dynamics of driver car-following decision process. The 1st-year research project aims to characterize driver behavior during car following under perception uncertainty conditions. Car following is deemed the outcome of the intuitive response of a driver to instantaneous optical stimuli in the visual field driven by changes in surrounding traffic environments. Such optical stimuli are transformed into psychophysical momentums, and then used to approximate the driver speed adjustment in the optical-flow-induced stimulus-response process. The 2nd and 3rd year projects further investigate the potential trade-off relationships among psychophysical factors including reaction time, perceived safety distance, perceived relative speed, as well as stimulus intension/frequency. My study purpose here is to improve the proposed generalized car-following model so as to comprehensively characterize the dynamics of driver car-following behavior under perception uncertainty contexts. The 4th-year project will further take account of external factors (e.g., lightness/darkness) and driver characteristics in the proposed model so as to comprehend the resulting influence in the proposed model. In the aspect of model testing and experimental design, I plan to use both a microscopic traffic simulator PARAMICS and driver simulator calibrated using processed video-based data to demonstrate the proposed model’s validity for real applications. Hopefully, the proposed generalized car-following behavior model is expected to link the gaps among the areas of traditional car-following theory, driving psychophysics, and ITS. It is also expected that such a proposed generalized perception-stimulus-response car-following behavior model can throw more light into its application to driver psychology and response in anomalous traffic environments to improve road safety. Furthermore, the study can be regarded as a frontier research of social physics providing in-depth understanding and applications of applied physics in social science.