新能源汽车技术专业“1+X”课证融合思考

在《国家职业教育改革实施方案》当中,明确提出了开启"1+X"的证书制度,其主要目的是要利用把学历教育和技能培训进行有效融合,培养出符合时代需求的高素质技术技能人才。以新能源车技术专业作为实例,对"1+X"制度进行积极地探索,找到培养高品质应用型技术人才的新方式,从新能源汽车技术专业的课程内容、考核方式、师资力量等各方面进行探索,为"1+X"课证融合的有效开展寻找高效途径,从而提高人才的质量。     

西南地区城乡物流协同发展策略研究——以贵州省为例

我国西南地区有着复杂的地理条件,其物流业的发展在国内处于较落后的地位,本文欲从西南地区的典型省份贵州省入手,对当地物流业进行研究,讨论贵州省城乡物流发展策略,为当地政府和企业提出一些建议,旨在推动贵州省乃至西南地区城乡物流的发展作出理论贡献。     

城市郊区列车与轨道交通区域快线

通过介绍国外城市郊区列车与城市轨道交通区域快线的发展概况,分析我国城市郊区列车与城市轨道交通区域快线的特点、存在的问题,提出我国发展城市轨道交通的建议。     

党建与业务融合推进汽车服务工程专业师资队伍建设的思考与探索——以河南工学院为例

在高校开展的各项活动中,积极推进党建工作和业务工作的深度融合,以党建促业务,以融合促发展,是确保“不忘初心、牢记使命”主题教育活动持续开展的行之有效的方法和途径。车辆与交通工程学院教工第二党支部在研究如何促进党建工作和业务工作深度融合的过程中,发现师资队伍建设是党建与业务融合的桥梁,通过探索实施多途径和多措施的师资队伍建设方案,打造一支作风优良,有凝聚力、影响力、战斗力的高效队伍,为实现汽车服务工程专业的可持续发展提供了强有力的保障。     

中国智慧公交示范现状分析及展望

智慧公交示范属于智能网联示范中的特色应用场景,也是智能网联开放道路示范的先行力量。本文梳理了我国现有典型智慧公交示范情况,分析其共性特点及存在问题,并对未来发展进行了展望。旨在从智慧公交视角窥见整体智能网联汽车产业发展进程,促进智能网联汽车从封闭走向开放、从示范应用走向商业化推广。     

考虑网络外部性航运商与无车承运人竞合研究

构建由 1个海洋航运商和 2个无车承运人组成的上下游的合作与竞争关系,2个无车承运人有不同的市场地位.通过斯坦伯格博弈研究发现,航运商负责货源或处于领导地位的无车承运人负责货源会影响各方的均衡利润及渠道结构.分析比较了海洋航运商的整合策略和利润共享策略.结果表明,在网络外部性和无车承运人提供差异性服务时,纳什均衡是航运商负责货源且上下游整合或利润分享.     

道路运输车辆达标车型整车主动安全项目测试简析

道路运输车辆达标车型的实施,有效提升了道路运输车辆的安全性能。文章主要从电子稳定性控制系统、车道偏离预警系统、前向碰撞预警系统、自动紧急制动系统四个整车主动安全测试项目对道路运输车辆达标车型相应标准进行介绍,为道路运输车辆达标车型相关从业人员提供了主动安全整车项目试验参考。     

液压式盾构/TBM主机平移-空推集成装置的研制

研究目的:目前,隧道掘进机平移与空推工艺多采用不同装置分步完成,装置安装耗时费力,严重影响项目施工进程,且国内外没有可同时解决掘进机主机平移和空推的工法或装置.本文研制了一种基于液压的盾构/TBM主机平移-空推集成装置,将平移与空推工序合一,可极大提高工程施工效率,实现荷载600 t盾构/TBM主机连续移位. 研究结论...     

Flow-based accessibility measurement: The Place Rank approach

In this paper, we empirically test the viability of a flow-based approach as an alternative to transport accessibility measurement. To track where commuters travel from and to (but not commute times), we use transactional smartcard data from residents in Singapore to construct the (daily) spatial network of trips generated. We use the Place Rank method to demonstrate the viability of the flow-based approach to study accessibility. We compute the Place Rank of each of 44 planning areas in Singapore. Interestingly, even though the spatial network is constructed using only origin–destination information, we find that the travel time of the trips out of each planning area generally decreases as the area’s Place Rank increases. The same is also the case for in-vehicle time, number of transfers in the network and transfer time. This shows that a flow-based approach can be used to measure the notion of accessibility, which is traditionally assessed using travel time information in the system. We also compare Place Rank with other indicators, namely, bus stop density, eigenvector centrality, clustering coefficient and typographical coefficient to evaluate an area’s accessibility. The results show that these indicators are not as effective as the Place Rank method.     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.