共享自动驾驶汽车经营策略优化分析

研究共享自动驾驶汽车(SAV)与普通汽车共存背景下，SAV公司如何根据运营目标优化经营策略并影响通勤者出行方式选择. 假设高速公路上存在一定数量的独驾通勤者，无车通勤者在SAV和地铁之间进行权衡. 分析固定需求和弹性需求下，SAV公司追求系统总成本最小或系统净收益最大和利润最大时的最优经营策略，即SAV票价和容量，进而得到均衡时模式划分情况，SAV最优发车数，系统总成本或系统净收益，以及公司利润等指标. 算例对均衡结果进一步验证发现，SAV公司垄断经营会收取较高的票价，提供容量较小的车型. 在系统最优情形下，SAV公司无法获得正利润，需要政府补贴运营.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.     

Validation of an extended discrete first-order model with variable speed limits

This paper validates the prediction model embedded in a model predictive controller (MPC) of variable speed limits (VSLs). The MPC controller was designed based on an extended discrete first-order model with a triangular fundamental diagram. In our previous work, the extended discrete first-order model was designed to reproduce the capacity drop and the propagation of jam waves, and it was validated with reasonable accuracy without the presence of VSLs. As VSLs influence traffic dynamics, the dynamics including VSLs needs to be validated, before it can be applied as a prediction model in MPC. For conceptual illustrations, we use two synthetic examples to show how the model reproduces the key mechanisms of VSLs that are applied by existing VSL control approaches. Furthermore, the model is calibrated by use of real traffic data from Dutch freeway A12, where the field test of a speed limit control algorithm (SPECIALIST) was conducted. In the calibration, the original model is extended by using a quadrangular fundamental diagram which keeps the linear feature of the model and represents traffic states at the under-critical branch more accurately. The resulting model is validated using various traffic data sets. The accuracy of the model is compared with a second-order traffic flow model. The performance of two models is comparable: both models reproduce accurate results matching with real data. Flow errors of the calibration and validation are around 10%. The extended discrete first-order model-based MPC controller has been demonstrated to resolve freeway jam waves efficiently by synthetic cases. It has a higher computation speed comparing to the second-order model-based MPC.     

Expertise in decision-making for large infrastructure projects: from UK trunk roads to High Speed Rail 2

At the decision-making stage, a large-scale infrastructure project is essentially a broad concept, and this means the expert analyses will differ from each other and become contested over time, leading to the emergence of rival narratives. It is only where there is a limited range of expert analyses that the bases for decision-making will remain relatively clear-cut. Over time the contested nature of expertise can significantly inhibit the construction of effective narratives, either for or against the project, and also make decision-making more complex and problematic. Decision makers may also seek greater clarification through the construction of narratives that rise above these disputed areas of expertise, and the scientific evidence becomes less important. This paper examines the changing nature of contested expertise through a comparative analysis of political decision-making between UK trunk roads policy and the case of High Speed Rail 2, through the framework of epistemic communities.     

LED灯具在高速列车照明系统中的应用

随着我国高速铁路事业的发展,旅客对车内照明环境品质的要求越来越高,在我国高速列车照明设计中广泛采用LED灯具作为光源。通过对高速动车组车载灯具与25T型列车传统车载灯具的测试对比,总结出LED灯具在发光效率等方面相对于传统灯具的优势,为高速动车组室内照明设计提供依据。     

Integrated vehicle and powertrain optimization for passenger vehicles with vehicle-infrastructure communication

This research proposes an optimal controller to improve fuel efficiency for a vehicle equipped with automatic transmission traveling on rolling terrain without the presence of a close preceding vehicle. Vehicle acceleration and transmission gear position are optimized simultaneously to achieve a better fuel efficiency. This research leverages the emerging Connected Vehicle technology and utilizes present and future information—such as real-time dynamic speed limit, vehicle speed, location and road topography—as optimization input. The optimal control is obtained using the Relaxed Pontryagin’s Minimum Principle. The benefit of the proposed optimal controller is significant compared to the regular cruise control and other eco-drive systems. It varies with the hill length, grade, and the number of available gear positions. It ranges from an increased fuel saving of 18–28% for vehicles with four-speed transmission and 25–45% for vehicles with six-speed transmission. The computational time for the optimization is 1.0–2.1 s for the four-speed vehicle and 1.8–3.9 s for the six-speed vehicle, given a 50 s optimization time horizon and 0.1 s time step. The proposed controller can potentially be used in real-time.     

Point-to-point speed enforcement systems: Speed limits design criteria and analysis of drivers’ compliance

Point-to-point (P2P) speed enforcement is a relatively new approach to traffic law enforcement. Its technology allows vehicles whose average speed exceeds the speed limit over the controlled section to be fined. It therefore encourages compliance over distances longer than those where spot enforcement policies have been in place.In this paper, a procedure for consistently setting speed limits with such enforcement systems is proposed. Such a method has been applied to design the speed limits on two motorways in the district of Naples, Italy, where P2P enforcement systems became operational in 2009 and 2010. The speed limits, which were set using the Italian geometric design standard to assess vehicle stability and stopping sight distance, have been compared with those provided by using well-known international standards.The impact of the newly designed speed limits and of the P2P enforcement system on drivers’ speeding behaviour has been quantified for each highway section and vehicle type. In fact, accurate measurements of the average travel speeds of each vehicle crossing the enforced sections, before and after the activation of the system, were available. The migration from the old speed limits with spot speed enforcement to the new approach resulted in a notable increase in drivers’ compliance to the speed limits with a remarkable decrease in both the average of individual speeds and in their standard deviation.In addition, the analysis of 3 years of data shows that a gradual adaptation of drivers’ behaviour to the system took place. In particular, a decreasing compliance to the speed limits points to a non-optimal system management. Finally, the results of a revealed preference survey allowed us to make a behavioural interpretation regarding the significantly different impacts measured on the two motorways.     

对地铁信号系统列车运行速度制约因素的探讨

信号系统是保障地铁运行安全及提高运行效率的重要设备,列车超速防护功能是信号系统一个非常关键的功能。信号系统防护下的列车运行速度由车辆、线路、轨道、限界及信号系统等条件共同决定。由于相关专业对信号系统安全制动模型不了解,在实际工程中易造成"速度浪费"现象。从信号系统安全制动模型的原理出发,对车辆、线路、轨道、限界等专业对列车运行速度的制约因素进行分析,提出建议。     

多元评价体系组合模型在铁路隧道变形预测中的应用

为克服传统预测模型结构单一、预测精度及稳定性不足等缺陷,提出多元体系组合预测模型的建模思路。首先,基于支持向量机、BP神经网络及ARMA模型3种单一预测模型,构建铁路隧道变形预测体系;再以均方根误差、误差平方和及平均绝对误差等为评价准则或指标,构建各预测结果的误差评价体系,求解各单项预测模型的权值贡献指数,得到最优组合权值;然后利用后验差检验、残差检验和关联度检验构建预测精度校验体系,对组合预测结果进行检验,评价预测模型的有效性;最后,结合工程实例,对多元体系组合预测模型在特大断面隧道中的变形预测效果进行检验。结果表明:多元评价体系组合模型预测相对误差值均小于2%,具有较高的预测精度,且较单一预测模型具有更高的预测精度,也一致通过相关检验,验证了多元体系组合预测模型的有效性。     

美国限速制定方法及启示

为使我国道路限速的制定更为合理,借鉴国外相关经验是必不可少的。总结了美国设置限速时考虑的主要因素、限速设置方法及其适用条件。对美国部分城市的州际道路及主干路的限速实施状况进行了分析,认为测速相机等自动执法设备的辅助使用能够在很大程度上提高驾驶人对限速的遵守程度。在借鉴美国限速方法及实施经验的基础上,指出我国在制定道路相关限速标准时,应结合国情确定限制速度与运行速度、设计速度之间的互动关系,以及限速与安全、执法等之间的关系。然后针对不同的道路类型、等级等特性研究采用不同的限速方案,解决速度区限速取值及不同速度区之间如何平滑过渡衔接等问题,明确了我国限速研究的基础性内容。