面向驾驶员特性的路径规划算法

合理的路径规划必须充分考虑驾驶员习惯和心理特征,交叉口延误和转弯类型(如左转、直行或右转)对驾驶员的心理感受有较大影响。为此,针对城市路网密度大、交叉口间距小的特点,对经典的A*算法进行两方面的改进：将交叉口延误引入代价函数中;引入交叉口转弯系数γ以表征驾驶员对转弯类型的心理感受,并将其加入代价函数中。算例结果表明,与原算法相比,改进后的A*算法在保证路径总时间最短的前提下能避开左转弯操作,与实际的驾驶员习惯更吻合。     

Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a ‘nanoscopic model’ of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a ‘driver-agent’, for recognising driver’s intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver’s intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver’s mood, have also been presented.     

遗传算法在路径规划上的应用

为了满足出行者能高效快捷地到达目的地, 需要找到一条综合权值最优的出行路径, 再在其上设置指路标志对目的地进行指引. 基于此, 本文首先根据路网的特点, 对交通路网模型进行表述; 接着阐述了遗传算法的基本概念和算法思想, 并以行驶路程和交叉口个数作为出行者路径选择的因素, 定义了行驶路程和交叉口个数综合指标最小的路径为最优路径; 最后, 以广州大学城中山大学为例, 在明确起终点的情况下, 利用遗传算法的方法找到了去往中山大学的最优路径, 验证了遗传算法在路径规划上的有效性.     

Stochastic User Equilibrium Traffic Assignment with Turn-delays in Intersections

Turn-delays in intersections contribute significantly to travel times and thus route choices in urban networks. However, turns are difficult to handle in traffic assignment models due to the asymmetric Jacobian in the cost functions. The paper describes a model where turn delays have been included in the solution algorithm of Stochastic User Equilibrium (SUE) traffic assignment. When the Jacobian is symmetric, SUE minimises the road users' 'perceived travel resistances'. This is a probit-model where the links cost-functions of the links are traffic dependent. Hereby, overlapping routes are handled in a consistent way. However, no theoretical proof of convergence has been given if the Jacobian is asymmetric, although convergence can be shown probable for model data representing realistic road-networks. However, according to the authors knowledge SUE with intersection delays have not been tested earlier on a full-scale network. Therefore, an essential part of the paper presents practical tests of convergence. Both geometric delays and delays caused by other turns are considered for each turn. Signalised and non-signalised intersections are handled in different ways, as are roundabouts. In signalised intersections a separate model handles queues longer than one green-period. Green-waves can also be taken into consideration. The model has been tested on a large-scale network for Copenhagen with good results. To make it possible to establish the comprehensive data, a GIS-based 'expert system' was implemented (see Nielsen, O.A., Frederiksen, R. D. and Simonsen, N. (1997). Using expert system rules to establish data on intersections and turns in road networks. International Transactions in Operational Research , 5 , 513–529.     

Analysis and Classification of Human Driving Behaviour in an Urban Environment*

Intelligent vehicle systems have introduced the need for designers to consider user preferences so as to make several kinds of driving features as driver friendly as possible. This requirement raises the problem of how to suitably analyse human performance so they can be implemented in automatic driving tasks. The framework of the present work is an adaptive cruise control with stop and go features for use in an urban setting. In such a context, one of the main requirements is to be able to tune the control strategy to the driver’s style. In order to do this, a number of different drivers were studied through the statistical analysis of their behaviour while driving. The aim of this analysis is to decide whether it is possible to determine a driver’s behaviour, what signals are suitable for this task and which parameters can be used to describe a driver’s style. An assignment procedure is then introduced in order to classify a driver’s behaviour within the stop and go task being considered. Finally, the findings were analysed subjectively and compared with a statistically objective one.     

Traffic congestion analysis at the turn level using Taxis' GPS trajectory data

Sensing turn-level or lane-level traffic conditions not only enables navigation systems to provide users with more detailed and finer-grained information, it can also improve the accuracy in the search for the fastest routes and in short-term predictions of traffic conditions. The widespread collection and application of taxis' GPS data enable us to sense urban traffic flow on a large scale. Since current GPS positional accuracy cannot reach the lane level, existing approaches using GPS trajectory data only analyze traffic conditions at the road level. Whereas some studies attempted to detect lane-level traffic conditions using lane-level data, the high cost of data collection considerably limits their practical application. To address this limitation, this article proposes an approach for detecting traffic congestion from taxis' GPS trajectories at the turn level. Based on analyzing features of GPS trajectories and identifying valid trajectory segments, the proposed approach detects congested trajectory segments of three different intensities. It then identifies congestion events in each turning direction through a clustering approach. Finally, congestion intensity, time of the day when congestion occurred and queue length in each turning direction at a road intersection in Wuhan, China are explored and analyzed. The results support the feasibility of this approach for detecting and analyzing traffic congestion at the turn level. Compared with other approaches that detect traffic congestion using GPS trajectory data, the proposed approach analyzes congestion at a finer-grained level (the turn level). Compared with other approaches that detect traffic congestion at the lane level, the proposed approach can sense traffic congestion over a larger area and at a lower cost.     

Towards load-balanced de-congested multi-robotic agent traffic control by coordinated control at intersections

This paper presents a methodology for the coordination of multiple robotic agents moving from one location to another in an environment embedded with a network of agents, placed at strategic locations such as intersections. These intersection agents, communicate with robotic agents and also with each other to route robots in a way as to minimize the congestion, thus resulting in the continuous flow of robot traffic. A robot’s path to its destination is computed by the network (in this paper, ‘Network’ refers to the collection of ‘Network agents’ operating at the intersections) in terms of the next waypoints to reach. The intersection agents are capable of identifying robots in their proximity based on signal strength. An intersection agent controls the flow of agent traffic around it with the help of the data it collects from the messages received from the robots and other surrounding intersection agents. The congestion of traffic is reduced using a two-layered hierarchical strategy. The primary layer operates at the intersection to reduce the time delay of robots crossing them. The secondary layer maintains coordination between intersection agents and routes traffic such that delay is reduced through effective load balancing. The objective at the primary level, to reduce congestion at the intersection, is achieved through assigning priorities to pathways leading to the intersection based on the robot traffic density. At the secondary level, the load balancing of robots over multiple intersections is achieved through coordination between intersection agents by communication of robot densities in different pathways. Extensive comparisons show the performance gain of the current method over existing ones. Theoretical analysis apart from simulation show the advantages of load-balanced traffic flow over uncoordinated allotment of robotic agents to pathways. Transferring the burden of coordination to the network releases more computational power for the robots to engage in critical assistive activities.     

基于等效网络的车辆导航系统路线规划算法

在实际交通行为中,不可避免地存在着交叉口时间延迟,而且交通管制信息如交叉口转向限制也普遍存在,这些交通特征使得常规的最短路算法难以满足车辆导航系统路线规划的要求。提出基于“节点-弧段-特征”的数据结构存储方案,能够完整描述路网的平面拓扑和交通特征属性;针对具有交叉口转向限制和交叉口延迟等特征的交通网络,首先采用对偶图方法构造等效网络,在等效网络中采用常规的最短路算法计算最优路线,然后将它转化为原道路网中的行车路线。试验证明这种方法能够有效解决包含交通特征的车辆导航系统路线规划问题.     

A real-time framework for eye detection and tracking

Epidemiological studies indicate that automobile drivers from varying demographics are confronted by difficult driving contexts such as negotiating intersections, yielding, merging and overtaking. We aim to detect and track the face and eyes of the driver during several driving scenarios, allowing for further understanding of a driver’s visual search pattern behavior. Traditionally, detection and tracking of objects in visual media has been performed using specific techniques. These techniques vary in terms of their robustness and computational cost. This research proposes a real-time framework that is built upon a foundation synonymous to boosting, which we extend from learners to trackers and demonstrate that the idea of an integrated framework employing multiple trackers is advantageous in forming a globally strong tracking methodology. In order to model the effectiveness of trackers, a confidence parameter is introduced to help minimize the errors produced by incorrect matches and allow more effective trackers with a higher confidence value to correct the perceived position of the target.     

基于实时车速的交通控制与诱导协同

为了减小路网的总行程时间和提高路网运行效率,提出一种基于实时车速的交通控制与诱导协同模型。利用惩罚函数将有约束遗传算法转化为无约束遗传算法对所建立的协同模型进行求解,得到最佳的控制方案和诱导方案。在Vissim微观交通仿真软件中建立包含4个交叉口的小型路网进行仿真实验,仿真结果表明,此方法能够有效地减少路网总行程时间,提高路网运行效率。      

Machine learning in road accident research: decision trees describing road accidents during cross-flow turns

In-depth studies of behavioural factors in road accidents using conventional methods are often inconclusive and costly. In a series of studies exploring alternative approaches, 200 cross-flow junction road accidents were sampled from the files of Nottinghamshire Constabulary, UK, coded for computer analysis using a specially devised ‘Traffic Related Action Analysis Language’, and then examined using different computational and statistical techniques. The present study employed an AI machine-learning method based on Quinlan's ‘ID3’ algorithm to create decision trees distinguishing the characteristics of accidents that resulted in injury or in damage only; accidents of young male drivers; and those of the relatively more and less dangerous situations. For example the severity of accidents involving turning onto a main road could be determined with 79% accuracy from the nature of the other vehicle, season, junction type, and whether the Turner failed to notice another road user. Accidents involving young male drivers could be identified with 77% accuracy by knowing if the junction was complex, and whether the Turner waited or slowed before turning.     

The relation between driving experience and recognition of road signs relative to their locations

OBJECTIVES: Examine how driving experience and expectations affect the ability of experienced drivers to identify traffic signs--specifically, no right turn (NRT) and no left turn (NLT) at intersections. BACKGROUND: Failure to heed signs is a frequent cause of accidents, and the authors focused on the contributions of experience and expectancy to sign identification. METHOD: Inexperienced and experienced drivers were connected to an eye tracker system and briefly exposed to various traffic scenes. Some of the pictures included an NRT sign at the expected location (on the right), and some included the same sign at an unexpected location (on the left). The same procedure was used with an NLT traffic sign. RESULTS: Experienced drivers identified traffic signs better than inexperienced drivers did when the signs were posted at the expected location but identified them worse than did inexperienced drivers when they were at unexpected locations. CONCLUSIONS: With experience, drivers' expectations regarding the expected location of traffic signs become so strong that violating these expectancies results in more identification errors among experienced drivers than among inexperienced drivers. To optimize experienced drivers' traffic sign identification, signs must be located in accordance with drivers' expectations--specifically, on the right side of the road. APPLICATIONS: When signs are misplaced, crashes can be caused by inappropriate placement rather than inappropriate driving. Highway designers should ensure that their design conforms to standards that shape experienced drivers' expectations.     

基于候客点规划的空闲出租车路线推荐算法

为空闲出租车司机推荐有效的闲逛路线在提高出租车司机工作效率、减少乘客等待时间以及缓解交通压力方面具有重要作用。现有的研究工作主要集中于为空闲司机推荐完整的驾驶路线,没有考虑到真实路网环境下某些路段的可等待因素,使得推荐的路线因载客概率较低、行驶距离较长而花费成本较高。提出一种基于候客点规划的路线推荐算法,对出租车轨迹数据进行处理,并设计路径匹配算法将每个轨迹点与真实路段一一匹配。通过统计每个路段历史接载信息,并利用一种改进的多层感知机建立可预测时序接载概率的模型,结合路段的可等待因素设计一种最小花费成本的路线推荐算法。在真实数据集上的实验结果表明,与MNP、InExperence、Random算法相比,所提算法花费成本、巡航时间以及巡航路程均明显减少。     

Path prediction and predictive range querying in road network databases

In automotive applications, movement-path prediction enables the delivery of predictive and relevant services to drivers, e.g., reporting traffic conditions and gas stations along the route ahead. Path prediction also enables better results of predictive range queries and reduces the location update frequency in vehicle tracking while preserving accuracy. Existing moving-object location prediction techniques in spatial-network settings largely target short-term prediction that does not extend beyond the next road junction. To go beyond short-term prediction, we formulate a network mobility model that offers a concise representation of mobility statistics extracted from massive collections of historical object trajectories. The model aims to capture the turning patterns at junctions and the travel speeds on road segments at the level of individual objects. Based on the mobility model, we present a maximum likelihood and a greedy algorithm for predicting the travel path of an object (for a time duration h into the future). We also present a novel and efficient server-side indexing scheme that supports predictive range queries on the mobility statistics of the objects. Empirical studies with real data suggest that our proposals are effective and efficient.     

An iterative/subdivision hybrid algorithm for?curve/curve?intersection

The problem of finding all intersections between two space curves is one of the fundamental problems in computer-aided geometric design and computational geometry. This article proposes a new iterative/subdivision hybrid algorithm for this problem. We use a test based on Kantorovich’s theorem to detect the starting point from which Newton’s method converges quadratically and a subdivision scheme to exclude certain regions that do not contain any intersections. Our algorithm is guaranteed to detect all intersections in the domain for nondegenerate and non-ill-posed cases.     

Using Expert System Rules to Establish Data for Intersections and Turns in Road Networks

Delays and restrictions in intersections contribute significantly to the overall travel times in urban traffic networks and therefore also affect route choices. In practice, however, it is quite unusual to include intersection delays in traffic models, logistic models and route guidance systems. Time consuming and tedious data preparation together with the complexity of network updating is the main reason for this, as most transportation software applications can do the necessary calculations. In this paper, we report on the development of a procedure that can automate the task of adding data for intersection delay modelling to an existing network. The method requires a GIS-based network with link attributes as input data. The method has developed as an extension tool applicable to existing networks and therefore supply of additional data is normally not required. By a set of 'expert system rules', the intersections are classified into a number of groups – such as prioritised and signalised intersections, wedges and Y-junctions – and the required input data for turn delay models is established. The method has been tested on large-scale networks with good results. Most of the required data was satisfactorily estimated, although some edits had to be made manually. This was mainly the case for roundabouts and for intersections with a very special geometry. In conclusion, the method greatly reduced the burden establishing data sets for intersection delay modelling in urban traffic networks.     

两相邻路口交通信号的协调控制

传统路口的控制算法大多研究单个路口的信号控制情况.该文根据路口之间的相互关 系,利用高阶广义神经网络及模糊推理提出了两个相邻交通路口的协调算法.利用此算法设计 的交通信号控制器,可以有效地协调两相邻路口的红绿灯信号,在一定程度上改善了交通路口 的交通状况.     

Older driver failures of attention at intersections: using change blindness methods to assess turn decision accuracy

A modified version of the flicker technique to induce change blindness was used to examine the effects of time constraints on decision-making accuracy at intersections on a total of 62 young (18-25 years), middle-aged (26-64 years), young-old (65-73 years), and old-old (74+ years) drivers. Thirty-six intersection photographs were manipulated so that one object (i.e., pedestrian, vehicle, sign, or traffic control device) in the scene would change when the images were alternated for either 5 or 8 s using the modified flicker method. Young and middle-aged drivers made significantly more correct decisions than did young-old and old-old drivers. Logistic regression analysis of the data indicated that age and/or time were significant predictors of decision performance in 14 of the 36 intersections. Actual or potential applications of this research include driving assessment and crash investigation.     

Computational modelling of switching behaviour in repeated gambles

We present a computational model which predicts people’s switching behaviour in repeated gambling scenarios such as the Iowa Gambling Task. This Utility-Caution model suggests that people’s tendency to switch away from an option is due to a utility factor which reflects the probability and the amount of losses experienced compared to gains, and a caution factor which describes the number of choices made consecutively in that option. Using a novel next-choice-prediction method, the Utility-Caution model was tested using two sets of data on the performance of participants in the Iowa Gambling Task. The model produced significantly more accurate predictions of people’s choices than the previous Bayesian expected-utility model and expectancy-valence model.     

Synchronization of traffic signals as a means of reducing red-light running

The goal of this study was to determine if traffic signals that are synchronized along a route are associated with fewer red-light violations than traffic signals that are not synchronized. A total 3600 cycles of traffic signals at 12 intersections along 2 major urban arteries were observed. Synchronized intersections were effective in reducing the likelihood of red-light running (RLR) by (a) providing fewer opportunities than nonsynchronized intersections for RLR and (b) having a lower rate of RLR relative to the number of opportunities. After adjustment for the number of opportunities, the odds of entering the intersections in red in synchronized intersections were nearly 1/7 the odds of RLR in nonsynchronized intersections. Congestion reduced the effectiveness of synchronized intersections relative to nonsynchronized intersections. Male drivers were slightly more likely to run red lights than female drivers, and the effects of synchronization were fairly constant across age, gender, and the presence or absence of passengers. Actual or potential applications of this research involve signal synchronization to reduce aggressive driving in general and RLR in particular.