Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

Traffic modelling in system boundary expansion of road pavement life cycle assessment

This paper uses a case study of a UK inter-urban road, to explore the impact of extending the system boundary of road pavement life cycle assessment (LCA) to include increased traffic emissions due to delays during maintenance. Some previous studies have attempted this but have been limited to hypothetical scenarios or simplified traffic modelling, with no validation or sensitivity analysis. In this study, micro-simulation modelling of traffic was used to estimate emissions caused by delays at road works, for several traffic management options. The emissions were compared to those created by the maintenance operation, estimated using an LCA model. In this case study, the extra traffic emissions caused by delays at road works are relatively small, compared to those from the maintenance process, except for hydrocarbon emissions. However, they are generally close to, or above, the materiality threshold recommended in PAS2050 for estimating carbon footprints, and reach 5–10% when traffic flow levels are increased (hypothetically) or when traffic management is imposed outside times of lowest traffic flow. It is recommended, therefore, that emissions due to traffic disruption at road works should be included within the system boundary of road pavement LCA and carbon footprint studies and should be considered in developing guidelines for environmental product declarations of road pavement maintenance products and services.     

Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.     

Optimization of horizontal alignment geometry in road design and reconstruction

This paper presents a general formulation for optimization of horizontal road alignment, composed of tangential segments and circular curves suitably connected with transition curves (clothoids). It consists of a constrained optimization problem where the objective function is given by a line integral along the layout. The integrand is a function representing the cost of the road going through each point and, by considering different costs, a wide range of problems can be included in this formulation. To show it, we apply this methodology to three different situations. The two first cases are related with the design of a new road layout and used to solve a pair of academic examples. The third problem deals with the improvement of a road adapting the old path to current legislation, and it is solved taking as case study the reconstruction project for a regional road (NA-601) in the north of Spain.     

Integrated approach to determine highway flooding and critical points of drainage

Among the natural hazards that threaten transportation infrastructure, flooding represents a major hazard to highways as it challenges their design, operation, efficiency and safety. In extreme cases, it may lead to massive obstruction of traffic and direct damages to the road structures themselves and indirect damages to the economic activity and development of the region. To enable the prevention of such consequences, and the proposition of adaptive measures for existing infrastructure, this paper presents an integrated framework to identify the most vulnerable points to flooding along a highway. This is done through the combination of remote sensing information (e.g. LiDAR based Digital Elevation Model, satellite imagery), a high-quality dataset, and a quasi-2D hydrodynamic model. The forcing condition is defined using a hyetograph associated to a storm with duration of 1 day and return period of 100 years. The selected highway is located in the Mexican state of Tabasco, where extreme precipitation events and floods are frequent. Results demonstrate the ability of the methodology to identify critical water levels along the road (h > 1.50 m) at those locations where flooding has been experienced, as well as points of inspection for the highway drainage. These locations were visited in the field and maintenance problems were detected that do increase its level of exposure. We show that this framework is useful for the generation of a flood management strategy to the analyzed highway, which includes an optimum location of adaptive measures to an anticipated more intense future climate.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Estimation of road profile variability from measured vehicle responses

When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.     

马达加斯加武海马尔墓地的发掘与研究

马达加斯加武海马尔墓群有近六百座墓,其墓葬形制与同时期东非地区阿拉伯穆斯林的墓葬形制有着明显的不同,有些墓葬与中国穆斯林的墓葬形制有较多相似之处。部分墓葬中出土了大量元、明时期的瓷器和其他随葬品,反映出武海马尔墓群主人可能是元、明时期来自中国东南沿海地区或东南亚的色目、回回商人,以及附属于他们的汉人、马来人或武海马尔当地土著,如他们的妻妾、子女、随从、伙计等,其中有些是受雇于穆斯林商人的汉人或者受穆斯林影响的汉人,因此,其葬俗保留了一些中国传统丧葬礼仪的痕迹。     

基于公路隧道内车辆对火灾影响数值研究

以武汉长江公路隧道为工程背景,利用FDS5.0数值模拟软件建立隧道实体模型,进行火灾数值模拟分析。研究不同火灾热释放率、车辆长度、火源车辆阻塞比以及附近车辆之间间距、附近车辆长度、附近车辆阻塞比6种因素下,隧道内拱顶温度和人平均身高Z=1.70 m处CO浓度的分布规律,并对这6种因素进行敏感性分析。结果表明:隧道的拱顶温度随着热释放率和阻塞比的增加而增加,随着着火车辆长度的增加而减小;Z=1.70 m处CO浓度随着火灾热释放率和车辆长度的增加而增大,随阻塞比的增大而减小;影响隧道火灾的主要因素是热释放率和车辆阻塞比,应有针对性地对这二种因素进行有效的管理。     

“中—尼—印铁路通道”线路设计及建设可行性分析

随着我国"一带一路"倡议的推进,跨国运输通道的建设成为倡议实施的关键环节之一,而我国建设复杂地质条件下跨国基础设施的经验尚不丰富。"中—尼—印铁路通道"是一条途经尼泊尔,连接中国和印度2个大国的运输通道,基于实地考察,分析该通道建设的必要性及建成后的效益,对线路进行初步规划,并总结该通道建设的难点:铁路轨道坡度大;沿线区域地质构造复杂;周边基础设施落后,施工条件恶劣;大量深长隧道以及大跨径高桥梁;环境以及气候条件复杂。同时对沿线隧道以及桥梁的建设可行性进行分析,并给出施工建议:沿线隧道采用以TBM法为主、钻爆法为辅的施工方法;桥梁建设则因地制宜,根据不同区间的地质特点,采用相应的建设方法。