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Traffic network design problems (NDPs) play an important role in urban planning. Since there exist uncertainties in the real urban traffic network, neglecting the uncertainty factors may lead to unreasonable decisions. This paper considers the transportation network signal design problem under stochastic origin-destination (OD) demand. In general, solving this stochastic problem requires a large amount of computational budget to calculate the equilibrium flow corresponding to a certain demand distribution, which limits its real applications. To reduce the computational time in calculating the equilibrium flow under stochastic demand, this paper proposes a metamodel-based optimization method. First, a combined metamodel that integrates a physical modeling part and a model bias generic part is developed. The metamodel is used to approximate the time-consuming average equilibrium flow solution process, hence to improve the computational efficiency. To further improve the convergence and the solution optimality performance of the metamodel-based optimization, the gradient information of traffic flow with respect to the signal plan is incorporated in the optimization model. A gradient-based metamodel algorithm is then proposed. In the numerical example, a six-node test network is used to examine the proposed metamodel-based optimization method. The proposed combined metamodel is compared with the benchmark method to investigate the importance of incorporating a model bias generic part and the traffic flow gradient information in the combined metamodel. Although there is a reduction in solution optimality since the metamodel is an approximation of the original model, the metamodel methods greatly improve the computational efficiency (the computational time is reduced by 4.84 to 13.47 times in the cases of different initial points). By incorporating the model bias, the combined metamodel can better approximate the original optimal solution. Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. Numerical results show that the gradient-based metamodel method can effectively improve the computation efficiency while slightly reducing the solution optimality (with an increase of 0.09% in the expected total travel cost)., Author(s): Wei Huang [1]; Xuanyu Zhang [1]; Haofan Cheng [1]; Jiemin Xie (corresponding author) [2] 1. Introduction Traffic network design is a basic means to improve traffic flow distribution and [...]

In this paper, a closed-loop simulation of vehicle dynamics in CarSim is utilized as surrogate measures to study the effect of pavement roughness and differential settlement on risk of vehicle rollover and skidding. It is found that the influence of pavement roughness on vehicle rollover is significant and the influence of pavement roughness on vehicle skidding is insignificant. The influence of pavement roughness of grade A and B on safety margin of vehicle rollover can be negligible. Pavement roughness of grade C and D significantly reduces the safety margin of vehicle rollover. A 5cm settlement difference on pavement reduces the safety margin of vehicle skidding on a good road. When the settlement difference is 5cm, the vehicle rollover and skidding are greatly affected by the lane-changing speed. It provides an effective and general method based on vehicle dynamics for studying transportation safety as well as for setting up criteria for pavement maintenance., Author(s): Lu Sun [1]; Luchuan Chen [2]; Yanna Yin (corresponding author) [3]; Yao Tian [2]; Xuanyu Zhang [4] 1. Introduction Despite the decline in highway fatalities from 2001 to 2014 [...]

Nanoparticles have been widely adopted to improve the high-temperature performance of asphalt binder. However, the influence of moisture on high-temperature performance is not clear. Hence, the water absorption performance of the nano-SiO2-modified asphalt concrete is investigated. Based on this, to further analyze the pavement performance of the nano-SiO2-modified asphalt concrete, the coupled effects of high-temperature, moisture content, and nanoparticles content on the rutting resistance of the nano-SiO2-modified asphalt concrete are tested and revealed in this study. Results show that temperature has the most significant influence on the water absorption performance of the nano-SiO2-modified asphalt concrete. The rutting resistance of the nano-SiO2-modified asphalt concrete decreases as temperature and moisture content increase, especially for the temperature. The dynamic stability at the same temperature condition decreases approximately linearly as moisture content increases. The effect of the nano-SiO2 content is the most nonobvious. [ABSTRACT FROM AUTHOR]