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.     

车辆牌照信息调查法在公路OD调查中的应用

分析停车问询调查法和车辆牌照信息调查法在公路OD调查中的优缺点,结合浙江省两次全省公路OD调查的实际经验,指出公路OD调查自动化和常态化的发展方向.     

基于传播模型的非机动车违规过街行为研究

为研究信号交叉口非机动车违规过街行为，选取西安市的7个信号交叉口，通过视频拍摄获取资料，应用复杂网络来分析非机动车网络的结构特征和演化规律.建立了交叉口非机动车网络，基于SI模型的基本思想，提出了非机动车违规过街行为的传播模型.并通过python程序进行模拟分析，在不同的网络结构和不同的传播率下，获取了非机动车违规过街的行为趋势.结果表明：随着等待时间的增加，一旦有骑行者闯红灯，更多的骑行者将加入到违规过街的行列；在内向度和外向度方面，电动自行车均高于普通自行车；非机动车违规行为随着传播率及非机动车流量的增加而增加.     

Statistical assessment of EV usage potential from user’s perspective considering rapid-charging technology

The aim of the German Government is the licensing of one million electric vehicles (EV) in Germany until 2020. However, the number of battery electric vehicles (EVs) today still is just above 25,000. There are several reasons for deciding against an EV, but especially low battery ranges as well as too long perceived charging duration inhibit the usage of an EV. To eliminate the negative influence of these two reasons on the decision to purchase an EV, a novel charging technology is established. The rapid-charging technology enables the user to recharge the battery to 80% of its state of charge (SOC) within 20–30 min. For the examination of the technology’s impact from (potential) user’s perspective, users and nonusers of battery electric vehicles were questioned about the perceived additional value of public rapid-charging infrastructure by taking into account different trip purposes and running comparisons to regular charging options. The results show an increased perceived value especially for trips with leisure purpose, considering their share of all trip purposes in Germany, according to the MiD 2008. In order to increase the number of licensed EVs in Germany, the study’s results also suggest further dissemination of information on rapid charging which might influence the perceived usefulness of the technology and consequentially the perceived usefulness of an EV.     

Real-time trip purpose prediction using online location-based search and discovery services

The use of smartphone technology is increasingly considered a state-of-the-art practice in travel data collection. Researchers have investigated various methods to automatically predict trip characteristics based upon locational and other smartphone sensing data. Of the trip characteristics being studied, trip purpose prediction has received relatively less attention. This research develops trip purpose prediction models based upon online location-based search and discovery services (specifically, Google Places API) and a limited set of trip data that are usually available upon the completion of the trip. The models have the potential to be integrated with smartphone technology to produce real-time trip purpose prediction. We use a recent, large-scale travel behavior survey that is augmented by downloaded Google Places information on each trip destination to develop and validate the models. Two statistical and machine learning prediction approaches are used, including nested logit and random forest methods. Both sets of models show that Google Places information is a useful predictor of trip purpose in situations where activity- and person-related information is uncollectable, missing, or unreliable. Even when activity- and person-related information is available, incorporating Google Places information provides incremental improvements in trip purpose prediction.     

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.     

Vehicle electrification in a developing country: Status and issue,from a well-to-wheel perspective

The increase of public attention, scientific research and political interest in environmental problems associated with transportation has provided the motivation for re-invention of electric vehicles. However the usage of grid-dependent EVs with a high-carbon electricity grid might produce more damage to the environment. This study aims to provide an environmental impact comparison of ICEVs, HEVs and EVs during their usage cycle, by modeling their energy consumption (electricity or fuel) and the supply chains of the supplied energy, (well-to-wheel) based on a life cycle assessment. The results show that running EVs with the existing mixed sources of electrical energy produce larger impacts on the environment 60% of the time; when compared to HEVs. When compared to ICEVs, EVs produce a larger environmental impact on 7 out of 15 environmental impact categories. Overall the environmental impacts of EVs are substantial based on the well-to-wheel analysis. It will continue to be so if no change is made to the methods of electricity generation in the near future. Given that the environmental profile of EVs is linked with the existing national electricity generation mix, the national electricity supply must be made cleaner before the electrification of the urban transport system.     

浅埋顶管沉井周边土体的三维破坏形状及沉降研究

为研究顶管沉井及周边土体在顶进力作用下的形变范围与大小，以加固旋喷桩作为沉井周围加固体建立ABAQUS软件计算模型，并将模拟结果与工程实例、PLAXIS 3D软件所得结果进行对比分析。同时，采用广州地区花岗岩残积土进行室内沉井模型试验，并通过试验结果对数值模拟结论进行验证，得出结论如下： 1）在开挖基坑前达到设计强度的旋喷桩能有效减小基坑周边土体塌陷变形、坑底隆起。2）在施加工作顶推力下，前侧主动区首先出现贯通裂缝，竖向位移斜率增大出现明显拐点；继续增大顶推力，土体位移会急剧增大导致地表沉降严重。3）对于后背土体，在顶推力作用下，地表破裂线的切线角度从0°逐渐增大至45°+φ/2，导致破裂范围也不断扩大；达到45°+φ/2处后，继续施加顶推力会导致短轴方向破坏范围扩大的速度较长轴方向的速度更快；三维空间中被动区破坏土体在地表处产生形状为椭圆的破坏面，椭圆长轴方向为顶推轴线方向，被动破坏体呈现为牛角状椭圆楔体。     

Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

Promoting public bike-sharing: A lesson from the unsuccessful Pronto system

In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.