Explanations given by automation are often used to promote automation adoption. However, it remains unclear whether explanations promote acceptance of automated vehicles (AVs). In this study, we conducted a within-subject experiment in a driving simulator with 32 participants, using four different conditions. The four conditions included: (1) no explanation, (2) explanation given before or (3) after the AV acted and (4) the option for the driver to approve or disapprove the AV's action after hearing the explanation. We examined four AV outcomes: trust, preference for AV, anxiety and mental workload. Results suggest that explanations provided before an AV acted were associated with higher trust in and preference for the AV, but there was no difference in anxiety and workload. These results have important implications for the adoption of AVs.

This study proposes an autonomous vehicle incentive program design (AV-IPD) problem for a local government, which aims to promote the adoption of autonomous vehicles (AVs) by deploying AV lanes and subsidizing the purchase of AVs with the objective of system optimum subject to a fixed budget. As it is difficult to anticipate the changing AV market conditions in the future, we take into account the uncertainty in AV purchase price. For the AV-IPD problem, we firstly decide which regular lanes should be converted into exclusive AV lanes. Secondly, we determine the AV purchase subsidy for each realization of AV purchase price with a given AV lane deployment scheme. A binary logit model is applied to characterize the vehicle choice behavior of users. The AV-IPD problem is formulated as a two-stage stochastic programming model with equilibrium constraints. To solve the AV-IPD problem, we develop a solution method based on linear approximation techniques and duality theories. Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and solution method. 1. Introduction The last few years have witnessed an explosive development on autonomous vehicle (AV) technology. Compared to the conventional vehicles (CVs), AVs can achieve a wide range of benefits in terms of traffic capacity, safety and vehicular emission. A successful implementation of AVs depends on the deployment of transport infrastructure catered for AVs and sufficient AV adoption. To promote the market penetration of AVs, a local government could design an AV incentive program to deploy exclusive AV lanes and subsidize users to purchase AVs subject to a fixed budget. The purpose of setting AV lanes is to separate AVs and CVs and exploit AV's advantage in improving road capacity. Current studies demonstrated that the road capacity could become up to triple in full AV environment by a shorter headway (Tientrakool et al., 2011). However, AVs become less beneficial under the mixed traffic with AVs and CVs. With a low AV ratio, the road capacity is possible to decrease due to speed variation and shock waves (Van Arem et al., 2006). To eliminate the issues arising from the mixed traffic, a local government can divide roads into regular lanes and AV lanes (Talebpour et al., 2017) so that AVs can travel with very short headway on AV lanes. The AV users have right of way on both regular and exclusive lanes while CV users can only travel on regular lanes. Different from conventional road construction projects, deploying AV lanes does not increase the number of lanes but converts some regular lanes into AV exclusive lanes. Some sensors are installed to facilitate the vehicle-to-vehicle (V2V) and vehicleto-infrastructure (V2I) communications (Jia et al., 2016). Some roads may require a novel traffic signal system (Li and Zhou, 2017). Besides, the users' vehicle choice between AVs and CVs is another feature needed to consider for the deployment of AV lanes. This is

Trust is a vital determinant of acceptance of automated vehicles (AVs) and expectations and explanations are often at the heart of any trusting relationship. Once expectations have been violated, explanations are needed to mitigate the damage. This study introduces the importance of timing of explanations in promoting trust in AVs. We present the preliminary results of a within-subjects experimental study involving eight participants exposed to four AV driving conditions (i.e. 32 data points). Preliminary results show a pattern that suggests that explanations provided before the AV takes actions promote more trust than explanations provided afterward.

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