The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of energy efficient vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (±0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008, i.e., 519 privately owned, exempt EEVs.     

Assessment of energy-saving techniques in direct-current-electrified mass transit systems

Railway rapid transit systems are key stones for the sustainability of mass transit in developed countries. The overwhelming majority of these railway systems are direct-current (DC) electrified and several energy-saving techniques have been proposed in the literature for these systems. The use of regenerative-braking in trains is generally recognised as the main tool to improve the efficiency of DC-electrified mass transit railway systems but the energy recovered in braking cannot always be handled efficiently, above all in low traffic-density situations. Several emerging technologies as energy storage systems or reversible traction substations have the potential for making it possible to efficiently use train-braking. However, a systematic evaluation of their effect is missing in the literature.In this paper, a deep, rigorous and comprehensive study on the factors which affect energy issues in a DC-electrified mass transit railway system is carried out. This study clarifies what the actual potential is for energy saving in each situation. Then, a methodology to asses several energy-saving techniques to improve energy efficiency in DC-electrified mass transit systems is presented, constituting the main contribution of this paper. This methodology has been conceived to help operators in assessing the effect of railway-infrastructure emerging technologies in transit systems, so making it possible to shape planning, capacity, etc. It is stepped out in three basic movements. First of all, a traffic-density scan analysis is conducted in order to clarify the effect of the headway on system behaviour. Secondly, several traffic-density scenarios are simulated for a set of infrastructure-expanded cases. Finally, annual energy saving is evaluated by applying a realistic operation timetable. This methodology has been applied to a case study in Madrid Metro (Spain) to illustrate the steps of its application and the effect of several energy-saving techniques on this specific system. Results confirm that regenerative braking generally leads to an important increase of system energy efficiency – especially at high traffic-density scenarios. It has also been proved that infrastructure improvements can also contribute to energy savings and their contributions are more significant at low traffic densities. Annual energy results have been obtained, which may lead to investment decisions by carrying out an appropriate economic assessment based on cost analysis.The main results of the study presented here are likely to apply to other electric traction systems, at least qualitatively.     

Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control

The performance of container terminals needs to be improved to handle the growth of transported containers and maintain port sustainability. This paper provides a methodology for improving the handling capacity of an automated container terminal in an energy-efficient way. The behavior of a container terminal is considered as consisting of a higher level and a lower level represented by discrete-event dynamics and continuous-time dynamics, respectively. These dynamics represent the behavior of a large number of terminal equipment. The dynamics need to be controlled. For controlling the higher level dynamics, a minimal makespan problem is solved. For this, the minimal time required by equipment for performing an operation at the lower level is needed. The minimal time for performing an operation at the lower level is obtained using Pontryagin’s Minimum Principle. The actual operation time allowed by the higher level for processing an operation at the lower level is subsequently determined by a scheduling algorithm at the higher level. Given an actual operation time, the lower level dynamics are controlled using optimal control to achieve minimal energy consumption while respecting the time constraint. Simulation studies illustrate how energy-efficient management of equipment for the minimal makespan could be obtained using the proposed methodology.     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.     

Weight threshold estimation of falling UAVs (Unmanned Aerial Vehicles) based on impact energy

Different weight thresholds for drone operations have been specified by regulatory agencies in different countries, without detailed backgrounds of guidelines. Therefore, this paper aims to study weight thresholds by focusing different levels of injuries caused by the impact of the drones on human head of different weights dropped at various heights. The work covers drone free drop modelling, FEM (finite element method) based impact modeling, and comparable drop impact experiments. The analyses and experiments were conducted accordingly to two individual commercially-available groups: small and large drones in weights. Two well-established indicators defining head injuries due to impact, which are known as Head Injury Criterion (HIC) and Abbreviated Injury Scale (AIS), are used in the present weight threshold study. The proposed AIS level for the weight threshold estimation has been set at AIS level 3, which indicates major skull fracture, in the further analysis through the probability of fatality. The main focus of the present work is to perform a parametric study and to present a reliable model to estimate the weight thresholds of the drone operations based on HIC and AIS. In conclusion, the results obtained and presented in this paper have demonstrated and provided a comprehensive analysis of possible direct injuries of a falling drone impacting a human head, with relevant data of impact or injury levels associated with HIC and AIS obtained for a drone with different weights falling from various heights.     

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from whatever data are available. This paper presents a generic data assimilation framework to reconstruct such plausible trajectories on signalized urban arterials using microscopic traffic flow models and data from loops (individual vehicle passages and thus vehicle counts); traffic control data; and (sparse) travel time measurements from whatever source available. The key problem we address is that loops suffer from miss- and over-counts, which result in unbounded errors in vehicle accumulations, rendering trajectory reconstruction highly problematic. Our framework solves this problem in two ways. First, we correct the systematic error in vehicle accumulation by fusing the counts with sparsely available travel times. Second, the proposed framework uses particle filtering and an innovative hierarchical resampling scheme, which effectively integrates over the remaining error distribution, resulting in plausible trajectories. The proposed data assimilation framework is tested and validated using simulated data. Experiments and an extensive sensitivity analysis show that the proposed method is robust to errors both in the model and in the measurements, and provides good estimations for vehicle accumulation and vehicle trajectories with moderate sensor quality. The framework does not impose restrictions on the type of microscopic models used and can be naturally extended to include and estimate additional trajectory attributes such as destination and path, given data are available for assimilation.     

汽车发动机排气门辅助制动系统试验分析

文章介绍了排气门辅助制动系统的构造及其工作原理,通过平板式制动试验台试验与整车道路试验,验证了排气门辅助制动系统对汽车运行的安全性、经济性和驾乘舒适性都有着显著的提高。     

冲击压实工艺在客运专线施工中的应用

文章以新建的武汉-广州铁路客运专线施工工程为例,对冲击压实工艺试验的检测结果进行分析,介绍了冲击压实作用机理及施工工艺,同时针对不同的冲击压实的适用范围提出了建议。     

Mining missing train logs from Smart Card data

This paper shows how to recover the arrival times of trains from the gate times of metro passengers from Smart Card data. Such technique is essential when a log, the set of records indicating the actual arrival and departure time of each bus or train at each station and also a critical component in reliability analysis of a transportation system, is missing partially or entirely. The procedure reconstructs each train as a sequence of the earliest exit times, called S-epochs, among its alighting passengers at each stations. The procedure first constructs a set of passengers, also known as reference passengers, whose routing choices are easily identifiable. The procedure then computes, from the exit times of the reference passengers, a set of tentative S-epochs based on a detection measure whose validity relies on an extreme-value characteristic of the platform-to-gate movement of alighting passengers. The tentative S-epochs are then finalized to be a true one, or rejected, based on their consistencies with bounds and/or interpolation from prescribed S-epochs of adjacent trains and stations. Tested on 12 daily sets of trains, with varying degrees of missing logs, from three entire metro lines, the method restored the arrival times of 95% of trains within the error of 24 s even when 100% of logs was missing. The mining procedure can also be applied to trains operating under special strategies such as short-turning and skip-stop. The recovered log seems precise enough for the current reliability analysis performed by the city of Seoul.