利用資通訊科技建構一個智慧城市，以解決人口不斷增長以及快速都市化所帶來的問題，已成為當局者急需解決的挑戰。
隨著智慧型運輸系統(ITS，Intelligent Transportation Systems)的發展，增進了運輸系統之安全、效率與舒適，以及減少都市化對交通環境的衝擊，其中自動駕駛車被認為是提升道路安全、效率、解決交通擁擠、能源消耗以及環境污染等問題的解決方案，亦被認為是可以解決交通第一哩路與最後一哩路的有效方法。
然而台灣車流有汽機車共存的特性，若是將共享自駕車(SAV，Shared Autonomous Vehicles)服務導入在台灣的路網中將會有不同的情況發生；再加上新興科技的出現伴隨的是人們接受度與信賴度的問題。
故本研究採用個體選擇模式中的多項羅吉特模式，建構消費者運具之選擇行為，以分析消費者對於共享自動駕駛車之偏好以及推估共享自駕車的需求量，本研究使用Biogeme軟體對其模式參數進行校估與分析。接著，利用交通指派模擬軟體DynaTAIWAN，觀察整體系統績效，評估共享自駕車加入台灣路網的影響。
模式校估結果顯示，常搭乘大眾運具、有共乘體驗以及女性較偏好使用共享自駕車，而共享自駕車之運具占有率也高於汽車、機車和大眾運具。在模擬結果則表明，若是需求有轉移至共享自駕車，則引進共享自駕車可以舒緩交通壅塞、改善空氣汙染和節省能源。
最終產生之結果，能讓公私部門使用更準確的方式來推廣以及佈署自動駕駛車，亦可驅動未來有關自動駕駛車之研究。

The growing population and rapid urbanization have become an urgent challenge for the authorities. Utilizing the information and communication technologies (ICT) to construct a smart city is considered as a solution.
The development of Intelligent Transportation Systems (ITS), the safety, efficiency, and comfort of the transportation system are enhanced, as well as the impact of urbanization on the traffic environment is reduced. Autonomous vehicles (AVs) are considered to be a solution to improve road safety, relieve congestion, save energy, and reduce air pollution; moreover, it is also deemed to be a solution to solve first mile and last mile problem.
If the shared autonomous vehicle (SAV) service is introduced into Taiwan, different situations will happen due to the mixed traffic flow. Moreover, an emerging technology breakthrough is accompanied by people’s adoption and reliability.
In view of this, this study constructs Multinomial Logit Model (MNL) firstly to analyze consumers’ preferences for SAVs and use Biogeme software to estimate parameters. Secondly, in order to evaluate the impact of SAVs on the traffic network, we utilize DynaTAIWAN, a dynamic traffic assignment simulation, to observe the overall system performance.
Estimation results show that SAV is more likely to be used by people who use public transportation frequently, have a ridesharing experience, and female. SAV mode share is the highest compared with cars, motorcycles, and public transportation in both Scenario 1 (8KM) and Scenario 2 (16KM).
On the other hand, simulation results indicate that SAVs can relieve congestion (because the average travel time and stop time of system decreased), reduce air pollution (because SAVs are electrification), and save energy (because the number of cars and motorcycles decreased) when demand does shift from private mode to SAVs.
The research results will allow the government and operators to use more accurate approaches to promote and develop SAV service. It also can drive future research on AVs or SAVs.

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