出借身份证给他人登记车辆负事故连带责任

1998年12月某日,河北省涞水县卢某驾驶一辆农用四轮运输车与卢某某一起前往北京送货时,将骑自行车的初中学生王某撞倒。卢某正不知所措时,坐在旁边的卢某某告诉他快跑。卢某一踩油门开车狂奔起来。驶出800多米后,挂在底盘上的王某才脱落下来。王某因伤势过重,经抢救无效死亡。事后二卢投案自首。     

出借身份证给他人登记车辆负事故连带责任

江苏省东台市吴某将自己的身份证借给他弟弟登记了一辆小轿车的入户手续。2001年10月26日,他弟弟驾驶该车在姜堰市某路段行驶时撞上一骑自行车的人,造成此人脊髓损伤伴右下肢不全瘫、脑震荡、多发性软组织挫伤,医院治疗出院后被评为十级伤残。姜堰市公安局交警大队做出的《道路交通事故责任认定书》认定,吴某的弟弟负这起事故的全部责任。交警大队就此起事故的损害赔偿进行了两次调解,双方当事人未达成协议,调解终结。受害人向姜堰市人民法院提起诉讼。姜堰市人民法院经审理,判决吴某的弟弟赔偿受害人医药费、住院费、误工费、残疾者生活补助费和其他损失合计37893元,     

尾板的"春天"何时到来

春天代表的是希望、是新生、是喜悦，正如《贫嘴张大民的幸福生活》中三民的一句“我的春天也来了。”喊出了他对新生活的渴望和心中的喜悦。同样，在当今物流逐渐成为国民经济一个重要的组成部分，也受到了越来越多的关注。与此同时，和物流相关的配套设备也逐渐从幕后走向台前。     

冻雨冰雪中的车辆"急救技巧"

近来各地冻雨不断,不少将车停在露天的驾驶人发现,爱车要么车门打不开,要么车窗被“冻结”,甚至因为雨刷被冻,不少私家车的雨刷电机都被烧坏。面对冻雨天气,不少车主倒是有不少“应对办法”,例如热水泼车窗、雨刷刮风挡等等。但是汽修专家提醒,这些做法往往容易伤及爱车,建议车主学习一些冻雨、冰雪天气中的车辆“急救技巧”。     

汽配电子身份证

假冒伪劣汽配不仅仅是导致安全事故的一个重要“杀手”,还直接影响了车辆技术性能的发挥。据统计,交通事故中因装配假冒伪劣汽配导致车辆安全性能降低而肇事的比例占了整个交通事故的20％左右。某国有汽配企业负责人估计,目前假冒伪劣汽配泛滥,汽配市场中有近七成的配件来路不明。许多小作坊式的工厂根本不具备生产条件,但他们以低廉的价格推销其产品,其中有许多是事关安全的配件,     

"四小车辆"规费征收问题及建议

“四小车辆”（三轮、四轮农用车及农用巴士车；变型拖拉机；二轮及三轮摩托车；其他简易机动车辆）交通规费是各地村级公路建设、养护、水毁补助和基层交管站工作经费的惟一来源。     

Potential for electric vehicle adoption in Australia

Data from the New South Wales (NSW) Household Travel Survey (2014/15 NSW, T. f. (2014/15, 9/15/2016). SA3 Household Travel Survey (HTS). Retrieved from https://drive.google.com/open?id=0B12S3-OIR0hOT3oyYzJnMVp1UWs [Google Scholar]) was analyzed to determine the trip-by-trip range of automobile travel in NSW. The results show that 88% of trips were less than 30?km, which could readily be provided by electric vehicles, consuming a total of 18?GWh in electrical energy per weekday. Even if all electric vehicles were recharged from non-renewable coal-fired power plants, the greater efficiency of electric vehicles would result in a reduction of greenhouse gas emissions across NSW by 18% carbon dioxide equivalent (CO_2(eq))_. Additionally, we mapped the average state of charge distribution of the electric vehicles at key times during the day, indicating the maximum net load (for recharging) and/or available energy (for vehicle-to-grid services) across NSW. The results are consistent with other international studies and demonstrate the potential for wide scale electric vehicles adoption in Australia.     

Temporal dynamics in local vehicle ownership for Great Britain

This article explores the stability of local vehicle ownership rates in Great Britain using the technique of spatial Markov chain analysis. Non-spatial Markov chain processes describe the transition of neighbourhoods through levels of ownership with no regard to their neighbourhood context. In reality however, how a neighbourhood transitions to different levels of ownership could be influenced by its neighbourhood context. A spatial Markov chain accounts for this context by estimating transition properties that are conditioned on the surrounding neighbourhood. These spatial Markov chain properties are estimated using a long run census time series from 1971 to 2011 of household vehicle ownership rates in Great Britain. These processes show that there is different behaviour in how neighbourhoods transition between levels of ownership depending on the context of their surrounding neighbours. The general finding is that the spatial Markov process will lead to a greater homogeneity in levels of ownership in each locality, with neighbourhoods surrounded by relatively low ownership neighbourhoods taking longer than a non-spatial Markov process would suggest to transition to higher levels, whilst neighbourhoods of high ownership surrounded by high ownership neighbourhoods take longer to transition to lower levels. This work corroborates Tobler's first law of geography “Everything is related to everything else, but near things are more related than distant things” but also provides practical guidance. Firstly, in modelling ownership, spatial effects need to be tested and when present, accounted for in the model formulation. Secondly, in a policy context, the surrounding neighbourhood situation is important, with neighbourhoods having a tendency towards homogeneity of ownership levels. This allows for the effective planning of transport provision for local services. Thirdly, vehicle ownership is often used as a proxy for the social and aspirational nature of an area and these results suggest that these properties will persist for a prolonged period, possibly perpetuating and exacerbating differentials in society.     

A Lagrangian heuristic for the real-time vehicle rescheduling problem

When a public transit vehicle breaks down on a scheduled trip, one or more vehicles need to be rescheduled to serve that trip and other service trips originally scheduled for the disabled vehicle. In this paper, the vehicle rescheduling problem (VRSP) is investiaged to consider operating costs, schedule disruption costs, and trip cancellation costs. The VRSP is proven to be NP-hard, and a Lagrangian relaxation based insertion heuristic is developed. Extensive computational experiments on randomly generated problems are reported. The results show that the Lagrangian heuristic performs very well for solving the VRSP.     

Specification for a dynamic vehicle routing and scheduling system

In an e-commerce environment, order fulfilment is driven by customer demands and expectations. A dynamic vehicle routing and scheduling system may be specified which allows e-commerce customers to select their own delivery Time Windows and have these confirmed on-line as they place their order. The methodology is based upon demand forecasting, which leads to the generation of phantom orders and phantom routes. Subsequently, actual orders substitute for phantom orders in an on-line customer order process. The routing and scheduling method includes using both parallel tour-building and parallel insertion algorithms. Customer service levels are confirmed using GPS tracking and tracing, and a feedback loop uses expert systems or artificial intelligence as an input to the demand forecasting data to restart the whole process.     

A hybrid population heuristic for the heterogeneous vehicle routing problems

The heterogeneous vehicle routing problem (HVRP) plays an important role in supply chain logistics. Two variants of HVRP are treated in this paper: one with fixed and variable costs (HVRPFD), and the other with only variable cost (HVRPD). A hybrid population heuristic that is able to solve both variants is proposed, in which a population of solutions are progressively evolved by crossovers and local searches. Computational results on a set of eight benchmark test problems from literature show that the proposed heuristic produces excellent solutions in short computing times.     

A model for taxi pooling with stochastic vehicle travel times

Taxi pooling means the sharing of a taxi by more than one passenger with at least a semi-common route. Currently, a trial-and-error process is adopted, taking into account expected travel times, for taxi pooling, a method which is neither effective nor efficient. This is because stochastic disturbances arising from variations in the taxi travel times that occur in actual traveling are neglected. In the worst case scenario, where vehicle travel times fluctuate wildly during operations, the planned schedule can be disturbed enough to lose its optimality. Therefore, in this study, a network flow technique is used to construct a stochastic taxi pooling model incorporating stochastic vehicle travel times. A solution algorithm is also proposed to efficiently solve the problem. The performance of the proposed models and the use of the solution method in practice are evaluated by executing numerical tests using real data with suitable assumptions. The test results show that the stochastic model and the solution method could be useful references for practice.     

Combining service frequency and vehicle routing for managing supplier shipments

This paper proposes a new approach to designing inbound material collection routes that considers pick-up frequency and spatial design as joint decisions to minimize total logistics (transportation plus inventory) cost. The clustering-based optimization uses an approximation to the actual cost of a routing solution without actual route construction. We show that the problem is analogous to a single-source fixed-charge facility location problem, and near-optimal solutions can be found using an efficient heuristic algorithm. Tests show the effectiveness of how this model is formulated and a case study demonstrates that substantial total cost savings can be achieved in realistic applications.     

Optimization models for placement of an energy-aware electric vehicle charging infrastructure

This paper addresses the problem of optimally placing charging stations in urban areas. Two optimization criteria are used: maximizing the number of reachable households and minimizing overall e-transportation energy cost. The decision making models used for both cases are mixed integer programming with linear and nonlinear energy-aware constraints. A multi-objective optimization model that handles both criteria (number of reachable households and transportation energy) simultaneously is also presented. A number of simulation results are provided for two different cities in order to illustrate the proposed methods. Among other insights, these results show that the multi-objective optimization provides improved placement results.     

A decision support system for vehicle relocation operations in carsharing systems

This paper presents a novel three-phase optimization-trend-simulation (OTS) decision support system for carsharing operators to determine a set of near-optimal manpower and operating parameters for the vehicle relocation problem. Tested on a set of commercially operational data from a carsharing company in Singapore, the simulation results suggest that the manpower and parameters recommended by the OTS system lead to a reduction in staff cost of 50%, a reduction in zero-vehicle-time ranging between 4.6% and 13.0%, a maintenance of the already low full-port-time and a reduction in number of relocations ranging between 37.1% and 41.1%.     

An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.