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Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC). Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lanechanging model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

In general, Elsevier is permissive with respect to authors and electronic preprints. If an electronic preprint of an article is placed on a public server prior to its submission to an Elsevier journal or where a paper was originally authored as a thesis or dissertation, this is not generally viewed by Elsevier as "prior publication" and therefore Elsevier will not require authors to remove electronic preprints of an article from public servers should the article be accepted for publication in an Elsevier journal.However, please note that Cell Press and The Lancet have different preprint policies and will not consider articles that have already been posted publicly for publication. This is a rule agreed upon by The International Committee of Medical Journal Editors. Information on Cell Press policy on preprints is available, as is The Lancet preprint policy. Permitted scholarly postingVoluntary posting by an author on open websites operated by the author or the author's institution for scholarly purposes, as determined by the author, or (in connection with preprints) on preprint servers. Abstract This paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist [2007, Review of Accounting Studies 12, 443-477], we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of news releases in leveling the playing field of investors but also the role of uninformed investors in reducing trading cost due to information asymmetry. AbstractThis paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist [2007, Review of Accounting Studies 12, 443-477], we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of ne...

This paper takes a new approach to examine whether investors extrapolate from past returns to form expectations about future stock returns. Unlike prior research that relies on experiments or surveys to derive investors' expectations, we estimate expected returns directly from stock prices, the book value of equity, and analyst earnings forecasts. We find that the expected returns are positively related to both past market returns and past stock returns. However, investors' expectations seem to be overoptimistic (overpessimistic) for stocks that had extremely high (low) returns in the previous year. Furthermore, we find that investors' expectations about future earnings growth rates are also positively related to past growth rates. The results remain robust after we control for analyst optimism and measures of risk. Taken together, our results are consistent with the findings that investors extrapolate from past stock returns and past earnings growth rates.

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