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Liability attribution for crashes involving automated vehicles (AVs), if applied improperly, is a factor which can potentially hinder acceptance. The present study investigated the impact of liability attribution on intention to buy an AV. A vignette-based survey was implemented with a hypothetical crash similar to the 2018 Uber crash (which was jointly caused by driver distraction and the malfunctioning of the automated system) leading to a pedestrian's fatality. Respondents (N = 1524) chose their preferred liability attribution, ranging from human driver exclusively liable to AV manufacturer exclusively liable. Respondents were then randomly allocated to different conditions of actual liability attribution by the local authority. These conditions were then combined into, negative misattribution (the authority assigned more liability to the human driver, compared to the respondent), positive misattribution (the authority assigned less liability to the human driver), and no misattribution. Negative misattribution negatively affected intention to buy; however, positive misattribution did not have a significant impact. The results of a multiple-mediator model indicated that negative misattribution affects intention to buy through the mediating effects of trust, negative affect, and crash acceptability. Theoretical and practical implications of our results are discussed. [ABSTRACT FROM AUTHOR]

PM 10 emissions generated from the brake wear of passenger car per braking event during three test driving cycles (WLTP, LACT, and WLTP-Brake) were studied using a finite element analysis (FEA) approach in combination with the relationship among the mass emitted rate of airborne particles versus local contact pressure and sliding speed. In addition, PM 10 emissions were measured per braking event during the WLTP-Brake cycle on a brake dynamometer using an electrical low-pressure impactor (ELPI+) to validate the proposed FEA approach. The simulated and experimental results for WLTP-Brake illustrated that the proposed simulation approach has the potential to predict PM 10 from brake wear per braking event, with an R 2 value of 0.93. The FEA results of three test driving cycles showed that there was a gradient rise in pad wear on both sides from the inner to outer radii. The simulated PM 10 emission factors during the WLTP, LACT, and WLTP-Brake were 7.9 mg km -1 veh -1 , 9.8 mg km -1 veh -1 , and 6.4 mg km -1 veh -1 , respectively. Among three test driving cycles, the ratio of PM 10 to total brake wear mass per braking event was the largest for the LACT, followed by WLTP and WLTP-Brake. From a practical application perspective, reducing the frequency of high-speed braking may be an effective way to decrease the generation of PM 10 emissions., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)