一种改进的移位左转车道信号控制方法及其效用分析

针对交叉口传统移位左转交通组织存在的交通冲突与通行效率问题，提出了一种改进的移位左转车道设置方法，并分析改进前、后的交通冲突状况。综合考虑行人与非机动车的过街需求，分析路段左转信号与交叉口主信号之间的协调控制关系，设计改进的移位左转交叉口相位方案，建立移位左转交叉口设计要点计算模型，包括移位左转车道长度、路段左转变道段长度、路段左转车储存段长度。假设车辆到达服从泊松分布，推导并建立改进的移位左转交叉口各相位的延误计算模型。以车均延误最小为目标，构建改进的移位左转交叉口信号控制参数优化模型，采用穷举法给出其求解算法。从左转交通量、移位左转车道长度、交叉方向右转车辆比重3个方面分析改进方法的适用条件，并借助VISSIM仿真，使用在哈尔滨市交叉口收集的数据验证改进方法的效用。研究结果表明：当移位左转车道长度为100 m左右时，该交通组织方式可以发挥最大效益；改进的移位左转交通组织较改进前交叉口车均延误下降了16.1%，验证了所提改进方法的有效性；当左转交通量小于400 pcu·h^-1，交叉方向右转交通量比重大于25%时，采用改进的移位左转方法，交叉口的通行效率改善更加显著。研究成果可为移位左转车道的设置及信号配时提供依据。     

多目标优化问题中目标间矛盾性关系的研究

在定义一个具有通用意义的满意解之后,分析了满意解质量标准之间的矛盾性,确定了描述质量标准矛盾关系的数量指标－矛盾度及归一化矛盾度,为多目标优化问题中目标间的折 选取提供了参考依据。     

信息不对称下交通运输管理中的最优激励

应用信息经济学的委托代理理论,将政府作为委托人,交通运输管理人员作为代理人,研究了在委托人对代理人的能力水平有不完全信息的逆向选择和在管理活动中代理人的努力程度等行为不可能跟踪监督的道德风险同时存在的广义委托代理中的最优激励机制.通过建立非线性规划的数学模型,获得了在风险中性的委托人为具有"勤能补拙"特征的风险厌恶的代理人设计的最优激励工资合同的混同均衡的显式解,混同的工资合同解释了岗位工资的合理性和激励作用.     

基于Epsilon 约束法的高速铁路客票多目标定价研究

高铁客票定价是多目标定价问题,既要保障旅客福利,又要增加企业合理利润. 以企业利润和旅客福利作为高铁定价目标,考虑旅客差异和不同运距情境下的多种运输方式竞争,研究高铁客票多目标定价. 结合Epsilon约束法构建双层规划模型,根据分层序列思想分解多目标问题,设计松弛算法得到纳什均衡解,由解对应的目标值得到帕累托边界,确定多目标定价最优决策. 计算结果表明,对比量价波动和目标值改进,多目标定价适合票价改革要求,时间敏感型客票和短途客票有较高涨价空间,多种运输方式竞争影响定价实施效果. 将 Epsilon 约束法应用于求解高铁客票定价多目标问题,有利于优化客运企业与旅客利益,为铁路部门提供高铁客票定价思路.     

公交线路配车问题的不确定双层规划模型

为合理优化公交线路配车,考虑现实中公交站点乘客数量不确定性因素,引入不确定理论构建公交线路配车的不确定双层规划模型. 上层目标为公交运营企业的收益最大化,下层目标为乘客出行时间和费用总成本最小,约束条件是政府要求的服务水平、乘车率,通过 MATLAB进行编程求解. 以南昌市210 路公交为例,利用所构建的不确定双层规划模型对早高峰07:00-08:00 配车进行优化,在给定80%乘车率的约束条件下,单方向配车数量由26 辆减少到23 辆,减少11.5%;优化后高峰小时乘客总加权成本相比优化前小幅增加0.5%,基本持平;高峰小时该线路的利润比优化前增加了112 元,提高29.6%. 结果显示,利用所构建模型优化早高峰小时线路配车效果明显. 该研究为公交运营者考虑现实中不确定因素更合理地优化线路配车提供了理论支持.     

Development of a signal-head-free intersection control logic in a fully connected and autonomous vehicle environment

Establishment of effective cooperation between vehicles and transportation infrastructure improves travel reliability in urban transportation networks. Lack of collaboration, however, exacerbates congestion due mainly to frequent stops at signalized intersections. It is beneficial to develop a control logic that collects basic safety message from approaching connected and autonomous vehicles and guarantees efficient intersection operations with safe and incident free vehicle maneuvers. In this paper, a signal-head-free intersection control logic is formulated into a dynamic programming model that aims to maximize the intersection throughput. A stochastic look-ahead technique is proposed based on Monte Carlo tree search algorithm to determine the near-optimal actions (i.e., acceleration rates) over time to prevent movement conflicts. Our numerical results confirm that the proposed technique can solve the problem efficiently and addresses the consequences of existing traffic signals. The proposed approach, while completely avoids incidents at intersections, significantly reduces travel time (ranging between 59.4% and 83.7% when compared to fixed-time and fully-actuated control strategies) at intersections under various demand patterns.     

A simple reservation and allocation model of shared parking lots

With increasing auto demands, efficient parking management is by no means less important than road traffic congestion control. This is due to shortages of parking spaces within the limited land areas of the city centers in many metropolises. The parking problem becomes an integrated part of traffic planning and management. On the other hand, it is a fact that many private parking spots are available during daytime in nearby residential compound because those residents drive their cars out to work. These temporarily vacant parking lots can be efficiently utilized to meet the parking demand of other drivers who are working at nearby locations or drivers who come for shopping or other activities. This paper proposes a framework and a simple model for embracing shared use of residential parking spaces between residents and public users. The proposed shared use is a winning strategy because it maximizes the use of private resources to benefit the community as a whole. It also creates a new business model enabled by the fast-growing mobile apps in our daily lives.     

Electric vehicle tour planning

This study extends the orienteering problem with time windows by considering electric vehicles (EV) with limited range. The model can simulate the change in the battery’s state of charge at each point along the routes, and thus can be used to solve the problem of EV tourist trip design with time windows. A land-sea integrated network for Penghu low-carbon islands was tested, and then the optimal green trip designs are obtained using a heuristic method. Some unique properties of the model are also discussed, as well as a number of management or planning implications.     

Coordinated platooning with multiple speeds

In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on the time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.