Danya Yao

A Survey of Traffic Control With Vehicular Communications

During the last 60 years, incessant efforts have been made to improve the efficiency of traffic control systems to meet ever-increasing traffic demands. Some recent works attempt to enhance traffic efficiency via vehicle-to-vehicle communications. In this paper, we aim to give a survey of some research frontiers in this trend, identifying early-stage key technologies and discussing potential benefits that will be gained. Our survey focuses on the control side and aims to highlight that the design philosophy for traffic control systems is undergoing a transition from feedback character to feedforward character. Moreover, we discuss some contrasting preferences in the design of traffic control systems and their relations to vehicular communications. The first pair of contrasting preferences are model-based predictive control versus simulation-based predictive control. The second pair are global planning-based control versus local self-organization-based control. The third pair are control using rich information that may be highly redundant versus control using concise information that is necessary. Both the potentials and drawbacks of these control strategies are explained. We hope these comparisons can shed some interesting light on future traffic control studies.

Headway distribution modeling with regard to traffic status

Knowledge of vehicle headway distribution is very important for intelligent transportation and intelligent vehicle simulations. Various headway distribution models have been proposed, but most of them only fit for a certain traffic situation. To solve this problem, we study the dependence of headway distributions on traffic status in this paper. Results show that the log-normal distribution model is adequate in fitting headway data when the traffic is in free flow status; while the log-logistic distribution model is more suitable in fitting headway data when the traffic is in congestion status. This conclusion is useful in the traffic signal optimization algorithm, since it indicates that we should apply different delay estimation models during different traffic status so as to design optimal timing plan.

A Comparison of Phase Transitions Produced by PARAMICS, TransModeler, and VISSIM

Increasing efforts are devoted to test and improve the performance of commercial traffic simulation software now. However, most previous approaches emphasized microscopic car-following and lane-changing features but neglect the macroscopic traffic dynamics. In this paper, we compare the traffic flow phase transition behaviors of three popular simulation software: PARAMICS 6.5, TransModeler 2.0 and VISSIM 5.1 on a single yet typical scenario. Our testing re-sults show that their slight differences in microscopic models can be appropriately magnified and intuitively displayed in the phase diagram.

Behavior modeling and simulation for conflicts in vehicles-bicycles mixed flow

Great changes are taking place in Chinese economic and societal life during the last decade, which brings significantly increasing pressure to the transportation systems of most Chinese cities. For example, in Beijing, vehicles are now fiercely competing for the right of roads with the existing large amount of bicycles. Because many streets in Beijing are not fully channelized to separate vehicles and bicycles, such competition leads to notable growth of traffic accidents and decline of traffic efficiency. This important matter has attracted growing research interests recently. In this paper, a behavior modelling and simulation for conflicts in vehicles-bycicles mixed flow is proposed. The first part is driving-riding behaviors in vehicles-bicycles laminar flow, second part is a cellular automata model for vehicle-bycicle laminar flow, the third part is the simulation results and discussions, and the last part talks about the potential application.

Pedestrian Safety Analysis in Mixed Traffic Conditions Using Video Data

With the dramatic development of image processing technology, a growing number of traffic flow detection and analyses have been conducted by using video data. Time to collision (TTC) and postencroachment time (PET) are two major parameters used to indicate the severity of a potential collision and to capture an imminent vehicular accident. However, microlevel pedestrian-involved collisions are less studied because they are hard to observe or record. This paper tries to extract the traffic object locations from video data, to define the time difference to collision (TDTC) parameter as a variation from TTC and PET to fit the pedestrian-involved potential collisions/conflicts, analyze the interaction behavior between pedestrian and vehicles, and validate the TDTC parameter in indicating pedestrian safety performance by using 100 groups of interaction data. The results show that the interaction cases with larger TDTC values are safer, whereas the cases with continuously closer to zero TDTC values are more dangerous. About 80% of the cases classified by the TDTC parameter have the same result with the independent observation; if TDTC is combined with vehicle speed, the classification result can be improved. More mixed traffic scenes will be conducted based on this research in the future.

A review of game theory applications in transportation analysis

Game theory has been widely used in various fields since its birth. Particularly, it plays an important role in transportation analysis and provides powerful tools to solve many difficult problems. This paper provides an overview of the numerous applications of game theory in transportation analysis and classifies these applications into two types. We aim to provide a clear framework of these applications and also a feasible solving process of problems. At last, we point out some drawbacks of game theory based applications and discuss how to adjust game theory method to deal with complex situations in future practice.

Pattern Discovering of Regional Traffic Status with Self-Organizing Maps

It is believed that the evolution of traffic status follows certain temporal-spatial rules and patterns, and the challenge is to extract such patterns from mass traffic data. In this paper, the traffic status of multiple links in a certain region is considered. Self-organizing maps (SOMs) are applied to organize flow data of links into physically relevant clusters, with each cluster representing one pattern. The clustering results are then interpreted using several exploratory methods which utilize the SOMs advantages of topological preservation and easy visualization. Case studies on real-world data reveal some meaningful phenomena and rules of regional traffic status, which prove the effectiveness of our approaches

Dynamic vehicle routing problem using hybrid ant system

The dynamic vehicle routing problem, DVRP, consists in optimally routing a fleet occur at random. The optimization consists in finding the solution that minimizes the total length of tours and satisfying the customer delivery time window. In this paper, we present a hybrid ant system to handle the dynamism by means of modifying the pheromone matrix and candidate sets strategy. In addition, we make further improvements on vehicle routes with the local search heuristics. The results show that the hybrid ant system works effectively to find competitive solutions.

A novel curve lane detection based on Improved River Flow and RANSA

Accurate and robust lane detection, especially the curve lane detection, is the premise of Lane Departure Warning System (LDWS) and Forward Collision Warning System (FCWS). Lane detection on the structural roads under challenging scenarios such as the dashed lane markings and vehicle occlusion is a difficult task because of unreliable lane feature point. In this paper, a robust curve lane detection method based on Improved River Flow (IRF) and RANSAC method is proposed to detect curve lane under challenging conditions. The lane markings are grouped into a near vision field of straight line and a far vision field of curve line. The curve lanes are based on Hyperbola-pair model. To determine the coefficient of curvature, a novel method is proposed based on Improved River Flow method and RANSAC method. In the new method, Improved River Flow method is employed to search feature points in the far vision field guided by the results of detected straight lines in near vision field or the curve lines from last frame, which can connect dashed lane markings or obscured lane markings. So, it is robust on dashed lane markings and vehicle occlusion. Then, RANSAC is utilized to calculate the curvature, which can eliminate noisy feature points obtained from Improved River Flow. The experimental results show that the proposed method can robustly and accurately detect some challenging markings, such as the dashed lane markings and vehicle occlusion.

Delay estimates of mixed traffic flow at signalized intersections in China

Two characteristics of Chinese mixed traffic invalidate the conventional queuing delay estimates for western countries. First, the driving characteristics of Chinese drivers lead to different delays even though the other conditions are the same. Second, urban traffic flow in China is often hindered by pedestrians at intersections, such that imported intelligent traffic control systems do not work appropriately. Typical delay estimates for Chinese conditions were obtained from data for over 500 vehicle queues in Beijing collected using charge coupled device (CCD) cameras. The results show that the delays mainly depend on the proportion and positions of heavy vehicles in the queue, as well as the start-up situations (with or without interference). A simplified delay estimation model considers vehicle types and positions that compares well with the observed traffic delays.