Characteristics and changes of permafrost along the engineering corridor of National Highway 214 in the eastern Qinghai-Tibet Plateau

Due to a series of linear projects built along National Highway 214,the second"Permafrost Engineering Corridor"on the Qinghai-Tibet Plateau has formed.In this paper,by overcoming the problems of data decentralization and standard inconsistency,permafrost characteristics and changes along the engineering corridor are systematically summarized based on the survey and monitoring data.The results show that:1)Being controlled by elevation,the permafrost is distributed in flake discontinuity with mountains as the center along the line.The total length of the road section in permafrost regions is 365 km,of which the total length of the permafrost section of National Highway 214 is 216.7 km,and the total length of the permafrost section of Gong-Yu Expressway is 197.3 km.The mean annual ground temperature(MAGT)is higher than−1.5℃,and permafrost with MAGT lower than−1.5℃ is only distributed in the sections at Bayan Har Mountain and E'la Mountain.There are obvious differences in the distribution of ground ice in the different sections along the engineering corridor.The sections with high ice content are mainly located in Zuimatan,Duogerong Plain and the top of north and south slope of Bayan Har Mountain.The permafrost thickness is controlled by the ground temperature,and permafrost thickness increases with the decrease of the ground temperature,with the change rate of about 37 m/℃.2)Local factors(topography,landform,vegetation and lithology)affect the degradation process of permafrost,and then affect the distribution,ground temperature,thickness and ice content of permafrost.Asphalt pavement has greatly changed the heat exchange balance of the original ground,resulting in serious degradation of the permafrost.Due to the influence of roadbed direction trend,the phenomenon of shady-sunny slope is very significant in most sections along the line.The warming range of permafrost under the roadbed is gradually smaller with the increase of depth,so the thawing settlement of the shallow section with high ice-content permafrost is more significant.

考虑跨服务模式的网约车派单优化

为解决多服务模式的网约车市场中所存在的模式间供需时空不匹配的问题,打破模式间派单壁垒,减少车辆无效巡游,提升乘客体验,提出一种基于强化学习的跨模式派单算法。首先,设计跨模式派单的运行规则和相应的仿真环境为算法的训练提供环境支持。其次,针对派单过程中乘客需求动态变化的特点,设计两阶段派单流程。在第一阶段,根据车辆与需求的时空特征确定虚拟派单请求;在第二阶段,采用k最近邻算法对可行派单请求进行细化,选择与虚拟派单请求最为相似的请求作为最终的派单方案。实验表明,与基线方法相比,所提出的跨模式派单算法提升了基础服务模式中3.1%的请求响应率,同时减少了高级服务模式中车辆的空驶时间,实现了更高的经济效益与服务水平。

青藏公路边坡防护试验研究(英文)

The results brought out in the trials of slope protection along Qinghai-Tibet Highway are presented in this paper. The trials were carried out simultaneously at 5 sites in Qinghai-Tibet Plateau from 2000 to 2002. Altitudes at the experimental sites range between （4 240） m and （5 040） m. 4 sites are in permafrost area, and 1 site is in seasonally frozen ground. According to the trials of slope protection, vegetation is preferred to protect slopes along Qinghai-Tibet Highway. Road-GoodR, a chemical stabilizer, is proved as a good material for slope protection, and soil engineering system, combined with vegetative component and grade stabilization structures is proved as the best slope protection measure in these areas. The results showed that high-altitude areas at an altitude lower than （5 040） m, annual average temperatures higher than （-5.6） ℃ and annual rainfall more than 262\^2 mm, slopes can be protected using vegetative components.\;Trials for plant species selection proved that cold resistant grasses, Elymus nutans and Elymus sibiricus can be used for vegetation recovery along Qinghai-Tibet Highway. The results demonstrated that high-altitude areas at an altitude lower than （5 040） m, annual average temperatures higher than （-5.6） ℃ and annual rainfall more than 262\^2 mm, could be replanted. Hydroseeding proved to be a good planting technique, and mulch materials benefited vegetation recovery in such area.\;The experiment also proved that planting could improve slope stability, protect the ecological environment, and improve the roadside landscape.

Evaluating the flooding level impacts on urban metro networks and travel demand:behavioral analyses,agent-based simulation,and large-scale case study

With urban residents’increasing reliance on metro systems for commuting and other daily activities,extreme weather events such as heavy rainfall and flooding impacting the metro system services are becoming increasingly of concern.Plans for such emergency interruptions require a thorough understanding of the potential outcomes on both the system and individual component scales.However,due to the complex dynamics,constraints,and interactions of the elements involved(e.g.,disaster,infrastructure,service operation,and travel behavior),there is still no framework that comprehensively evaluates the system performance across different spatiotemporal scales and is flexible enough to handle increasingly detailed travel behavior,transit service,and disaster information data.Built on an agent-based model(ABM)framework,this study adopts a data-driven ABM simulation approach informed by actual metro operation and travel demand data to investigate the impact of flood-induced station closures on travelers as well as the overall system response.A before-after comparison is conducted where the traveler behaviors in disaster scenarios are obtained from a discrete choice model of alternative stations and routes.A case study of the Shanghai Metro is used to demonstrate the ability of the proposed approach in evaluating the impacts of flood-induced station closures on individual traveler behavior under normal operation and a series of water level rise scenarios of up to 5m.It was found that,when the flood-induced station closures only affect a few river-side stations in the city center,the travelers experience only minor disruptions to their trips due to the availability of unaffected stations nearby as a backup.However,as the water level increases and more stations(mainly in the suburban area)are affected,up to 25%of trips are no longer being fulfilled due to the loss of entrances,exits,or transfer links.The system experiences overall less crowdedness in terms of passenger volume and platform waiting time with a few exceptions of increased passenger load due to concentrations of passenger flows to alternative stations under flooding-induced station closures.The proposed approach can be adapted to other disaster scenarios to reveal the disaster impacts on both aggregated and disaggregated levels and guide the design of more spatio-and temporally-targeted emergency plans for metro systems.

Special Emergency Resources Preallocation Concerning Demand Time for Tunnel Collapse

Lacking timely access to rescue resources is one of the main causes of casualties in tunnel collapse.To provide timely rescue,this study proposed a multi-objective preallocation model of special emergency resources for tunnel collapse based on demand time.Efficiency,multiple coverage,and cost-effectiveness are taken as the key objectives of the model;the demand time service range is used as a coverage decision factor considering the unique nature of tunnel collapse.The weight of potential disaster-affected points and other general factors are also considered in this model in order to thoroughly combine the distribution of disaster points and service areas.Further,we take 15 main tunnel projects under construction in China as an example.When the relative proximity to the ideal point of the selected optimal schemeε_(a)is smaller than 0.5,we will adjust the weight of three objectives and reselect the optimal scheme untilε_(a)>0.5.Compared with the not preallocated case,the number of rescue rigs needed is reduced by 8.3%,the number of covered potential disaster-affected points is increased by 36.36%,the weighted coverage times are increased from 0.853 to 1.383,and the weighted distance is significantly reduced by 99%when the rescue rigs are preallocated,verifying the feasibility and superiority of the proposed model.

CHARGING STATION PLANNING FOR PLUG-IN ELECTRIC VEHICLES

A novel model for the charging station planning problem of plug-in electric vehicles is proposed in this paper considering the users＇ daily travel. With the objective of minimizing the total cost, including the charging stations＇ cost （including installing cost and management cost） and the users＇ cost （including station access cost and charging cost）, the proposed model simultaneously handles the problems where to locate the charging stations and how many chargers to be established in each charging station. Considering that different users may have different perception of station access cost and charging cost, two cases （i.e., homogeneous users and heterogeneous users） are typically investigated. The impacts of different discount rates, operating period of the charging stations, number of electric vehicles and number of charging stations on the location of the charging station are also studied. The simulation results not only show that it is very important to locate the charging stations according to the traveling behavior of users, but also verify the validity of the proposed model.