城市混合交通控制设计理念与方法

针对我国城市特有的混合交通特性,在分析城市路网特征和交通流运行特征的基础上,确立了混合交通控制系统设计的基本理念。基于混合交通流理论,建立了城市交通控制的方法体系,包括匝道控制、单点控制、干线协调控制、区域协调控制以及公交优先控制。运用此设计理念与方法开发出的混合交通控制系统（HiCON）,在北京、青岛、福州三地的应用表明：车辆平均延误减少10％～20％,平均行程时间降低5%-10％。     

典型客流密集区的非机动车停放组织优化方法研究

机非混行是我国道路交通的一大特性,非机动车在城市交通中的地位不容忽视.本研究主要关注在典型的客流密集区的非机动车停放管理,其中典型地点如城市轨道交通换乘枢纽、公园、医院等公共服务性较强的客流发生吸引源.通过总结客流密集区的非机动车停放存在的问题,提出对应的可实施措施.在北京市城铁五道口附近非机动车停放改善中,通过设置双...     

城市公交站点自行车对公交车的干扰行为研究

以北京市两个不同类型的典型公交站点为例,研究了公交站点处自行车对公交车的干扰行为,并建立了不同因素影响下自行车对公交车的干扰行为模型,进而对其进行验证.最后,提出了几点减少公交站点处自行车对公交车干扰的建议.     

连续流交叉口左转非机动车优化设计方法

为了提升连续流交叉口的通行能力,消除其主信号处左转非机动车与直行机动车的冲突,提出了一种左转非机动车优化设计方法.优化模型以机动车通过量最大为优化目标,考虑了信号相位相序、周期时长、绿灯时长等约束条件,建立线性规划优化模型.通过案例和敏感性分析,验证了该设计方法的优化效益.研究结果表明,该方法不仅能在高流量情况下显著提升交叉口通行能力,使得原本处于过饱和状态的交叉口变为不饱和,而且在高流量或低流量情况下,都有助于减少交叉口延误.进一步发现,左转非机动车流量每增加100辆/h或直行机动车流量比例每增加1.5%(直行机动车流量比例大于40%),优化设计对机动车最大通过量的提升比例增加4.5%.     

基于随机森林的电动自行车骑行者事故伤害程度影响因素分析

为研究电动自行车道路交通事故对骑行者伤害程度影响因素的重要性排序,分析电动自行车骑行者事故伤害程度的影响因素。收集某市2013-2015年电动自行车交通事故数据,对其进行描述性统计分析,从中选出与交通事故严重程度相关的22个影响因素。利用随机森林模型对电动自行车骑行者受伤严重程度进行预测,并对相关因素的重要程度进行排序。研究表明,影响电动自行车骑行者受伤严重程度的最主要因素依次为车辆间事故类型、受伤部位、道路物理隔离类型等。针对交通事故相关因素提出改进建议,研究结论可为电动自行车事故预防提供决策参考。     

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混合交通现象是我国城市交叉口最为显著的交通特点之一. 本文分析了城市信号交叉口的行人自行车绿灯放行特性,提出了绿灯放行两阶段的定义：第一阶段为行人自行车以聚集群的形式通过;第二个阶段为行人自行车以随机单体的形式通过. 分析了第一阶段聚集群在通行过程的内部结构变化;提出了人行横道“虚拟网格”方法,建立了聚集群空间占有率模型,分析了放行过程聚集群空间占有率的变化. 最后通过实例,基于视频分析的方法,通过对信号交叉口行人自行车时空位移曲线图的分析,可以发现绿灯放行的前8秒为第一阶段,之后为第二阶段;由于速度差异,放行过程中自行车会逐渐超越行人到达聚集的前段. 应用聚集群空间占有率模型,发现绿灯放行过程空间占有率先增加后减小.     

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交通拥堵是当今世界的难题,而排队长度作为判断交叉口阻塞的标志,对其模型的研究具有重要意义. 针对我国混合交通的特性,结合交通冲突机理,首先考虑左转自行车对同向直行机动车的干扰,运用交通波动理论,提出了左转自行车对机动车干扰造成的排队长度计算公式. 在此基础上,研究红灯初期滞留车辆数的变化规律,提出了红灯初期滞留车辆数的动态计算公式,建立了适合于北京市实际交通状况的信号交叉口排队长度动态计算模型. 通过大量实验数据表明,该模型可行有效,在不同交通状态下均有较高的计算精度,为交叉口信号优化配时、缓解拥堵提供理论依据.     

交叉口右转机动车穿越决策BP仿真模型及灵敏度分析

机非相互穿越模型是信号交叉口混合交通微观仿真系统中反映机动车和自行车相互影响的核心模型. 为了描述交叉口处机动车穿越自行车流的决策行为,分析了两相位信号交叉口右转机动车穿越邻道直行自行车的微观行为,提出了基于BP神经网络的机动车穿越决策模型. 以北京2个交叉口调查数据为基础,对该模型验证并与Logistic模型比较,结果表明BP模型优于Logistic模型且具有较好的预测精度. 根据所建模型的映射关系计算出系统输出对输入参数的一阶灵敏度矩阵,灵敏度分析结果表明,自行车提供给机动车的穿越间隙是影响机动车穿越决策行为的决定性因素,且间隙在2.76s～2.96s变动时对机动车穿越决策行为影响最大.     

Spontaneous emergence versus technology management in sustainable mobility transitions: Electric bicycles in China

This paper describes and seeks to understand the scale of the electric bicycle (electric two-wheeler) market in China, and to begin to explain its emergence with a view to outlining the prospects for learning from this case for applications in other countries around the world. Drawing on secondary data from Chinese government sources, electric bicycle industry websites, Chinese media sites and other sources, this exploratory paper positions the development of the electric bicycle market as occurring largely in the absence of positive policy intervention – in stark contrast to the nurturing afforded the electric car sector world-wide. The paper develops a multi-scalar perspective of transitions theory in an institutional setting, with examples drawn from Beijing and Fuzhou, to explain the processes of change outside of the traditional reference context of technology policy and management. It is concluded that transitions theory has a greater flexibility and adaptability as an explanatory framework than previously shown, but empirically the electric two-wheeler is a weakly-embedded alternative to mainstream automobility.     

Introducing specific power to bicycles and motorcycles: Application to electric mobility

Electric bicycles and motorcycles have emerged as a possible way of improving the transportation system sustainability. This work’s aim was to quantify the energy consumption, the trip travel and the driving dynamics on specific routes in Lisbon, Portugal. Six electric and conventional bicycles and motorcycles were monitored, and a methodology to quantify the power required in each driving second was developed: Motorcycle and Bicycle Specific Power (MSP and BSP respectively). MSP and BSP allows characterizing energy consumption rates based on on-road data and to define real-world operation patterns (driving power distribution), as well as to benchmark the different propulsion technologies under the same baseline of specific power. For negative MSP and BSP modes, the conventional and the electric motorcycles and bicycles demonstrated a similar pattern. However, their behavior was different for positive modes, since electric technologies allow reaching higher power conditions. The methodology developed estimates accurately the energy consumption (average deviation of −0.19 ± 6.76% for motorcycles and of 1.41 ± 8.91% for bicycles). The MSP and BSP methodologies were tested in 2 Lisbon routes. For the electric motorcycle an increase in trip time (+36%) was observed when compared to the conventional one, while for the electric bicycle a 9.5% decrease was verified when compared to the conventional one. The Tank-to-Wheel (TTW) energy consumption for motorcycles was reduced by 61% when shifting to electric mobility, while a 30% Well-to-Wheel (WTW) reduction is obtained. For the electric bicycles, an additional energy use is quantified due to the battery electricity consumption.