Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

潜射导弹无动力运载器的滚控暨分离技术研究

导弹水下发射无动力运载器需要滚动控制技术，但该技术在当前研制的静力分离运载器中难于实施。鉴于此，本文提出一种新的弹器分离方案－动力分离方案（即弹射分离方案），文中对动力分离运载器的结构和弹道性能作了较详细的介绍，并与静力分离方案作了较全面的比较。     

水下浇注混凝土灌注桩灌注事故预防及处理

水下混凝土灌注桩在桥梁基础结构中应用广泛，但其施工工艺复杂，受影响因素较多，作者根据多年施工经验，对水下混凝土灌注桩灌注事故预防及处理做出几点分析和总结。     

大断面水下盾构隧道管片接头抗弯刚度及其对管片内力影响研究

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水下隧道立交段设计与施工方案研究

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混合动力--未来城市公交的明星动力

本文阐述了目前国内外混合动力总成常用的几种方案,介绍了一种适合康明斯发动机的混合动力方案,展望了该动力总成的开发前景。     

车辆排放污染的综合控制

随着我国汽车保有量急剧的增加,车辆排放污染已成为亟待解决的重要课题,控制排放污染是一个大型系统工程,文中从车辆、道路交通环境、交通管理3个方面论述了对排放污染的综合控制。     

复杂路况下汽车主动避撞报警技术研究

汽车主动避撞报警技术对提高行车安全有重要意义,但如何减少复杂路况下行车时的误警率是当前需解决的关键问题。通过测量车载信息如汽车转向角度、车速、制动信号、转向灯信号等获知汽车的行驶状态,利用雷达技术感知路况和危险,基于合理的报警算法和控制策略,研制出复杂路况下的汽车主动避撞报警系统。通过实际道路报警试验,结果表明所采取的减少误警率的方法是有效的,所开发的报警系统更趋实用化。     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

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.