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With rapidly increasing urbanization and motorization in China, the effect of commuting on residents' subjective well-being (SWB) is likely growing. We used 13,261 individual, 124 city, and 401 neighbourhood samples from the 2014 China Labour-Force Dynamics Survey (CLDS 2014) and applied multilevel mixed-effects ordered probit regressions to investigate the relationship between commuting and SWB. We found huge differences between urban and rural areas in relation to commuting. Urban respondents' daily average commuting time was 0.56 h while rural respondents' daily average commuting time was 0.41 h. Further, the daily average commute time for residents living in cities with high urbanization rates ([ 70%) was longer than for those living in cities with low urbanization rates (\ 70%). The subjective well-being of residents who commute by walking or cycling was significantly lower than that of those who commute by other transportation modes. The regression results indicated that the longer the commute time, the lower the subjective well-being. Among residents who live in rural areas or cities with low urbanization, subjective well-being was more easily affected by commuting time.

Safety is one of the fundamental problems in robotics. Recently, a quadratic program based control barrier function (CBF) method has emerged as a way to enforce safetycritical constraints. Together with control Lyapunov function (CLF), it forms a safety-critical control strategy, named CLF-CBF-QP, which can mediate between achieving the control objective and ensuring safety, while being executable in real-time. However, once additional constraints such as input constraints are introduced, the CLF-CBF-QP may encounter infeasibility. In order to address the challenge arises due to the infeasibility, we propose an optimal-decay form for safety-critical control wherein the decay rate of the CBF is optimized point-wise in time so as to guarantee point-wise feasibility when the state lies inside the safe set. The proposed control design is numerically validated using an adaptive cruise control example.

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