无人配送：解锁应急救援“新姿势”

新冠肺炎疫情之下,无人配送车和无人机等科技优势凸显,京东无疑是其中的佼佼者。今年2月6日,在湖北武汉市青山区吉林街上,一辆由京东物流自主研发的智能配送车从京东物流仁和站出发,以15公里/小时的速度,将医疗物资送到了当地收治确诊患者的武汉第九医院,完成了疫情爆发后武汉智能配送的第一单。京东物流武汉仁和站距离武汉第九医院这个疫区核心只有600米。疫情爆发后,这个站点几乎支撑起了第九医院医疗物资的配送工作,其中,无人车配送约占70%。除了无人车,无人机也应急救灾中发挥着不可小觑的作用。早在2018年7月,北京的密云区西湾子桥和怀柔区琉璃庙镇的受灾地区上空便出现了京东无人机的身影。这两架Y3货运无人机和两架侦查无人机前往灾区,一方面为断路的灾区运送面包、方便面等急需物资,另一方面可即时掌握各村庄受灾及道路桥梁损坏情况,为进一步的救援和物资输送做准备。从精准救灾的无人机到战"疫"无人车,随着京东更多无人配送科技产品的广泛应用,进一步确立了其国内无人配送的领先地位。京东表示,希望通过实际验证,推进无人配送商业化,进而带动相关产业的发展。未来还将依托科技优势开发救灾无人机,探索区块链、AI等高新技术在救灾及公益领域的应用。本期专题,特邀京东X事业部无人系统研究院院长孙勇就无人配送在应急运输中的重要作用和发展趋势做一深入探讨,以飨读者。     

什么才是智慧物流“落地”的正确姿势?

正关于智慧物流,有人曾这么形容:云平台是大脑,自动仓储设备是躯干,标准化是肌肉,信息是血液,包装是手和脚,连接升级需要全身心的配合——仓储搬运机器人、分拣机器人在无人仓中穿梭忙碌,无人机、无人车、配送机器人负责最后一公里配送,各种高效的智能化技术将物流的五大物流要素之人、货、车、节点、线路紧密串联起来,整合成一个完整的智慧物流生态圈。智慧物流已成趋势,先行的企业们都在力推"无人黑科技",构建各具特色的智慧物流场景:阿里推出机器人仓群作业,让智慧物流覆盖商品全生命周期;京东推出无人     

全球无人配送产业全景及中国未来发展

正疫情对产业发展既是挑战也是机遇。在此期间,无人配送作为现实需求被广泛应用到战"疫"之中,而作为新兴产业,无人配送未来将如何发展也成为一个重要问题。2020年伊始,突如其来的新冠肺炎病毒肆虐全国,一场没有硝烟的"战争"就此展开。自疫情发生以来,全国人民上下一心众志成城,坚决做好防疫抗疫工作。在此期间,也催生出了各种"无接触配送""无人经济"消费场景的需求,医院、社区、办公园区……无人配送被广泛应用到战     

万顺叫车成立共产党员退役军人服务车队

近日,万顺叫车各分公司成立"共产党员退役军人服务车队",司机的胸牌上写着"共产党员退役军人万顺叫车服务车队".该服务车队的成员大都是去年抗击新冠疫情"万顺叫车爱心车队"成员.2020年抗击疫情防控期间,万顺叫车共成立945支爱心车队、21000多名网约车司机在各个城市免费接送医务人员和特殊人群,受到了多地政府和社会团体的好评.     

货运物流将迎新拐点?

正时光飞逝,2015年对物流行业来说是不平凡的一年,大环境的变化给物流行业带来了巨大的影响:传统物流迎合电商需求进化仓储服务,布局航空运输;干线物流纷纷崛起,率先作为标准化服务开启整合模式;新兴最后一公里配送企业各具特色,甚至开始了个性化转型:"第四方物流"企业用大数据提高传统物流效率……在这样的后电商时代,电商仓储、城乡配送、大件物流、智慧化物流等都将成为物流发展的重点。而就国家层面而言,多式联运示范工程,集装箱铁水、公铁联运发展,甩挂运输试点经验的推广以及依托互联网平台的"无车承运人"发展     

国家发展改革委:全力畅通运输物流网络保障稳定供应

日前,国家发展改革委称,经各地各部门共同努力,目前全国货运网络运行总体正常,北京、河北、吉林、黑龙江等疫情重点地区民生物资运输基本畅通. 据介绍,为切实保障运输物流畅通,国务院联防联控机制以及交通运输部、公安部、国家邮政局印发有关通知,要求在做好疫情防控的同时,取消对货运通行的不合理限制,及时公布防疫检查措施和通行条件,优先保障民生物资车辆通行,落实司乘人员返回检测不隔离,畅通邮政快递服务"最先和最后一公里"等.     

城市配送发展迅速但困难较多——访山东聊城交通汽运集团物流部部长陈永杰

随着城市电子商务、大型百货、连锁商超等现代流通方式的蓬勃发展,在很大程度上降低了商品流通的时间和成本,而决定其发展水平的重要因素就是城市配送服务体系效率的高低。近年来,城市配送发展速度比较迅速,但在较快的发展速度背后却凸显出城市配送所面临的发展困境。"最后一公里"的难题成为城市物流不畅通的痛楚,而城市配送企业生存环境也成为城市物流能够畅通起来制约因素。     

人工智能“零”接触

正没有售货员、全程无接触、不用排队、拿了就走……今年2月,京东7FRESH七鲜超市联合京东物流X事业部,在北京通州某社区外设置了5台智能售卖柜,让居民可以在无接触环境下购买到最新鲜的食材。这种创新的购物方式为城市社区疫情防控贡献了一份力量。诚然,人工智能"零"接触,不只是"无人化"智能仓储。面对突如其来的疫情,还有不少"硬核"无人设备的研发和应用,逐渐为各地防疫抗疫探索出了高效有力的科技支持。     

“越库操作”联手“共同配送”

城市配送是现代物流的重要组成部分，与居民的生活紧密联系在一起，由于市区货车限行导致最后一公里的配送问题将居民生活用品阻隔在外，过高的物流成本致使我们的商品价格奇高，行车难、物流堵城现象最终推高了商品价格。而城市配送问题主要体现在超市配送和零担货物配送，这两部分均与居民生活息息相关，所以，发展城市配送对于适应市民消费方式的变化，满足市民的消费需要，提高市民生活质量具有巨大促进作用。     

新冠疫情背景下我国进口食品冷链物流发展和监管现状

新冠肺炎疫情全球蔓延，进口食品冷链物流因其境外疫情输入风险较高，面临较大的发展与监管压力。研究全面分析了新冠肺炎疫情发生以来我国进口食品冷链物流发展现状。在肉类和乳制品进口刚需拉动下，我国冷链食品进口规模保持继续增长，但由于水海产品和水果进口规模遭受疫情冲击，冷链食品进口规模增速逐步放缓。进口食品冷链物流涉及口岸、仓储、运输、配送、销售等环节，链条长、环节多、参与人员复杂，全过程监管涉及海关、市场监管、卫健、交通运输等行业管理部门。研究梳理了当前我国进口冷链食品管理制度和监管现状，分析了在进口冷链食品疫情防控背景下从“源头—口岸—流通”全链条的管控现状。最后，从政府、企业、消费者角度提出了加强进口食品冷链物流疫情防控相关对策。     

Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.     

The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery

Once limited to the military domain, unmanned aerial vehicles are now poised to gain widespread adoption in the commercial sector. One such application is to deploy these aircraft, also known as drones, for last-mile delivery in logistics operations. While significant research efforts are underway to improve the technology required to enable delivery by drone, less attention has been focused on the operational challenges associated with leveraging this technology. This paper provides two mathematical programming models aimed at optimal routing and scheduling of unmanned aircraft, and delivery trucks, in this new paradigm of parcel delivery. In particular, a unique variant of the classical vehicle routing problem is introduced, motivated by a scenario in which an unmanned aerial vehicle works in collaboration with a traditional delivery truck to distribute parcels. We present mixed integer linear programming formulations for two delivery-by-drone problems, along with two simple, yet effective, heuristic solution approaches to solve problems of practical size. Solutions to these problems will facilitate the adoption of unmanned aircraft for last-mile delivery. Such a delivery system is expected to provide faster receipt of customer orders at less cost to the distributor and with reduced environmental impacts. A numerical analysis demonstrates the effectiveness of the heuristics and investigates the tradeoffs between using drones with faster flight speeds versus longer endurance.     

Vehicle routing with roaming delivery locations

We propose the vehicle routing problem with roaming delivery locations (VRPRDL) to model an innovation in last-mile delivery where a customer’s order is delivered to the trunk of his car. We develop construction and improvement heuristics for the VRPRDL based on two problem-specific techniques: (1) efficiently optimizing the delivery locations for a fixed customer delivery sequence and (2) efficiently switching a predecessor’s or successor’s delivery location during the insertion or deletion of a customer in a route. Furthermore, we conduct an extensive computation study to assess and quantify the benefits of trunk delivery in a variety of settings. The study reveals that a significant reduction in total distance travelled can be achieved, especially when trunk delivery is combined with traditional home delivery, which has both economic and environmental benefits.     

A hybrid controller for autonomous vehicles driving on automated highways

This paper addresses the problem of the hybrid control of autonomous vehicles driving on automated highways. Vehicles are autonomous, so they do not communicate with each other nor with the infrastructure. Two problems have to be dealt with: a vehicle driving in a single-lane highway must never collide with its leading vehicle; and a vehicle entering the highway at a designated entry junction must be able to merge from the merging lane to the main lane, again without any collision. To solve these problems, we equip each vehicle with a hybrid controller, consisting of several continuous control laws embedded inside a finite state automaton. The automaton specifies when a given vehicle must enter the highway, merge into the main lane, yield to other vehicles, exit from the highway, and so on. The continuous control laws specify what acceleration the vehicle must have in order to avoid collisions with nearby vehicles. By carefully designing these control laws and the conditions guarding the automaton transitions, we are able to demonstrate three important results. First, we state the initial conditions guaranteeing that a following vehicle never collides with its leading vehicle. Second, we extend this first result to a lane of autonomous vehicles. Third, we prove that if all the vehicles are equipped with our hybrid controller, then no collision can ever occur, and all vehicles either merge successfully or are forced to drop out when they reach the end of their merging lane. Finally, we show the outcome of a highway microsimulation modelled after the Katy Corridor near Houston, Texas: our single-lane highway can accommodate 4000 vehicles per hour with neither drop-outs nor traffic congestion. It is entirely programmed in SHIFT, a hybrid systems simulation language developed at UC Berkeley by the PATH group. This shows that SHIFT is a well suited language for designing safe control laws for autonomous highway systems, among others.     

Comparison of energy demands of drone-based and ground-based parcel delivery services

Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation.In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot.The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.     

Designing optimal autonomous vehicle sharing and reservation systems: A linear programming approach

Autonomous vehicle (AV) technology holds great promise for improving the efficiency of traditional vehicle sharing systems. In this paper, we investigate a new vehicle sharing system using AVs, referred to as autonomous vehicle sharing and reservation (AVSR). In such a system, travelers can request AV trips ahead of time and the AVSR system operator will optimally arrange AV pickup and delivery schedules and AV trip chains based on these requests. A linear programming model is proposed to efficiently solve for optimal solutions for AV trip chains and required fleet size through constructed AVSR networks. Case studies show that AVSR can significantly increase vehicle use rate (VUR) and consequentially reduce vehicle ownership significantly. In the meantime, it is found that the actual vehicle miles traveled (VMT) in AVSR systems is not significantly more than that of conventional taxis, despite inevitable empty hauls for vehicle relocation in AVSR systems. The results imply huge potential benefits from AVSR systems on improving mobility and sustainability of our current transportation systems.     

User preferences regarding autonomous vehicles

This study gains insight into individual motivations for choosing to own and use autonomous vehicles and develops a model for autonomous vehicle long-term choice decisions. A stated preference questionnaire is distributed to 721 individuals living across Israel and North America. Based on the characteristics of their current commutes, individuals are presented with various scenarios and asked to choose the car they would use for their commute. A vehicle choice model which includes three options is estimated:

• (1)Continue to commute using a regular car that you have in your possession.
• (2)Buy and shift to commuting using a privately-owned autonomous vehicle (PAV).
• (3)Shift to using a shared-autonomous vehicle (SAV), from a fleet of on-demand cars for your commute.

A factor analysis determined five relevant latent variables describing the individuals’ attitudes: technology interest, environmental concern, enjoy driving, public transit attitude, and pro-AV sentiments. The effects that the characteristics of the individual and the autonomous vehicle have on use and acceptance are quantified through random utility models including logit kernel model taking into account panel effects.Currently, large overall hesitations towards autonomous vehicle adoption exist, with 44% of choice decisions remaining regular vehicles. Early AV adopters will likely be young, students, more educated, and spend more time in vehicles. Even if the SAV service were to be completely free, only 75% of individuals would currently be willing to use SAVs. The study also found various differences regarding the preferences of individuals in Israel and North America, namely that Israelis are overall more likely to shift to autonomous vehicles.Methods to encourage SAV use include increasing the costs for regular cars as well as educating the public about the benefits of shared autonomous vehicles.     

Assessment of alternative ventilation schemes at public transport interchange

The provision of mechanical ventilation in a semi-confined public transport interchange is mandatory in Hong Kong. The authority recommends the general use of low-level-supply and high-level-exhaust airflow schemes that different from the traditional ventilation concept in that low-level emitted vehicle pollutants are best removed at source. Analyses of air quality at typical public transport interchange environments are conducted for the two airflow schemes. The CFD simulations are generalized by studying light and heavy traffic conditions with adjusted ventilation rates to match the change in vehicle emission levels to examine pollutant concentrations at passenger waiting areas and the elevated footbridges. While the conventional high-level-supply and low-level-exhaust scheme could perform better during light traffic loads, the difference diminishes with increased traffic loads during peak hours. On the other hand, the high-level exhaust scheme has an advantage of serving as a smoke extraction system during a fire outbreak.     

Lane change algorithm for autonomous vehicles via virtual curvature method

This paper addresses the lane changing problem of autonomous vehicles when there is no road infrastructure support. The autonomous vehicle should drive from the current lane to the adjacent lane in the absence of a reference path to guide the vehicle to the new lane. We suggest an algorithm that incorporates a virtual road curvature with bicycle model for lane change guidance. As the name suggests, the virtual road curvature does not physically exist. It is a user assigned radius of a curved path which connects the current lane to the adjacent lane. Since the lateral sensor readings during lane changing maneuver are erroneous, the steering angle along with the virtual curvature is fed into a bicycle model to estimate the lateral position during the transition to the next lane. Details of the algorithm and the virtual road curvature determination are presented in the paper. In contrast to other lane changing methods, controller switching is not required and the same controller is for both lane keeping and lane changing. The algorithm is verified experimentally and the results are comparable with lane changing with physical transition lane.     

Advanced Driver Assistance Systems from Autonomous to Cooperative Approach

Abstract

Advanced Driver Assistance Systems (ADAS) have been one of the most active areas of ITS studies in the last two decades. ADAS aim to support drivers by either providing warning to reduce risk exposures, or automating some of the control tasks to relieve a driver from manual control of a vehicle. ADAS functions can be achieved through an autonomous approach with all instrumentation and intelligence on board the vehicle, or through a cooperative approach, where assistance is provided from roadways and/or from other vehicles. In this article, recent research and developments of longitudinal control assistance systems are reviewed including adaptive cruise control, forward collision warning and avoidance, and platooning assistants. The review focuses on comparing between autonomous systems and cooperative systems in terms of technologies used, system impacts and implementation. The main objective is to achieve common understanding on ADAS functional potentials and limitations and to identify research needs for further studies.