Liang Zheng

Liang Zheng
Central South University | CSU · School of Traffic and Transportation Engineering

Doctor of Philosophy

About

54
Publications
11,972
Reads
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966
Citations
Introduction
Liang Zheng currently works at the School of Traffic and Transportation Engineering, Central South University. Liang does research in Macro- and Micro- traffic flow modeling and simulation; Big data-driven traffic prediction; Simulation-based traffic management & control optimization.

Publications

Publications (54)
Article
Accurate short-term passenger demand origin-destination (OD) matrix prediction contributes to the coordination of traffic supply and demand. This study proposes a novel generative adversarial network (GAN) named Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (CWGAN-GP) to predict the network-wide ride-sourcing passenge...
Article
This paper proposes an arterial signal control stochastic simulation-based optimization model with traffic safety and efficiency as bi-objectives and solves it by a bi-objective surrogate-based promising area search (BOSPAS) method. In this model, traffic safety and efficiency are indexed by the average potential collision energy (APCE) and the veh...
Article
Online ride-hailing plays an important role in modern urban transportation systems, and accurate short-term passenger demand prediction contributes to improving ride-hailing services. Many existing studies have made great achievements in zone-based demand prediction. However, origin–destination (OD)-based demand prediction has attracted little atte...
Article
This study develops a Surrogate-based Optimization algorithm with Dynamic Adaptation of perturbation search of All Dimensions (SODA-AD) to address high-dimensional mixed-integer optimization problems with a black-box objective function (HMIO-B). SODA-AD improves dynamic coordinate search (DCS) in two ways, i.e., with a new way of sampling candidate...
Article
Despite the advancements in the technologies of autonomous driving, it is still challenging to study the safety of a self-driving vehicle. Trajectory prediction is one core function of an auton-omous vehicle. This study proposes an Attention-based Interac-tion-aware Trajectory Prediction (AI-TP) for traffic agents around the autonomous vehicle. Wit...
Article
We propose a biobjective robust simulation-based optimization (BORSO) method to solve unconstrained problems involving implementation errors and parameter perturbations. We adopt the notion that a solution is robust efficient (RE) if the region that dominates its worst-case realizations of the biobjectives under uncertainty does not contain (all) t...
Article
The development and application of autonomous vehicles bring great changes to urban traffic management and control. As one of the bottlenecks to improve transportation efficiency, intersection management plays an important role in the urban city. When the dynamic control method in different cases is determined, the key of autonomous intersection ma...
Article
This study proposes a stochastic simulation-based network-wide signal timing optimization model with the balance consideration of traffic safety and efficiency, and solves it with a Bi-objective Stochastic Simulation-based Optimization (BOSSO) algorithm. During numerical experiments, an urban road network with 15 signalized and 5 non-signalized int...
Article
Full-text available
With Connected Vehicle Technologies being popular, drivers not only perceive downstream traffic information but also get upstream information by routinely checking backward traffic conditions, and the backward-looking frequency or probability is usually affected by prevailing traffic conditions. Meanwhile, the bi-directional perception range of dri...
Article
Knowledge of travel times serves as an important role in traffic control and management. As an increasingly popular data source, vehicle trajectories can provide large-scale travel time information. However, real-world travel time information extracted from sparse or low-resolution trajectory data often contains missing data that need to be imputed...
Article
Full-text available
Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions, which can minimize the wait time for passengers and drivers. With the consideration of spatiotemporal dependences, this study proposes a multi-task deep learning (MTDL) model to predict short-term taxi demand...
Article
This study proposes a tensor-based K-Nearest Neighbors (K-NN) method, in which traffic patterns involve multi-dimensional temporal information and bi-directional spatial information. Such multi-temporal information can not only capture the instantaneous fluctuation of short-term traffic but keep the general trend of long-term traffic. In numerical...
Article
Knowledge of trip travel times serves an important role in transportation management and control. Existing travel time estimation approaches generally cover empirical ones, statistical ones and hybrid ones. Despite strong tractability, the empirical approaches cannot sufficiently capture diverse travel time distributions (TTDs) and often encounter...
Conference Paper
Simulation plays a fundamental role in evaluating traffic operations and transportation planning strategies. A reliable simulator can provide effective analysis of a given traffic network if the simulation model parameters are accurately calibrated to local conditions. To solve the calibration problem under changes in traffic demand, this paper con...
Article
Accurate short-term passenger demand prediction contributes to the coordination of traffic supply and demand. This study proposes an end-to-end multi-task learning temporal convolutional neural network (MTL-TCNN) to predict the short-term passenger demand in a multi-zone level. Along with one feature selector named spatiotemporal dynamic time warpi...
Article
This paper proposes a deep learning based multitask learning (MTL) model to predict network-wide traffic speed, and two methods to improve its prediction performance. The nonlinear Granger causality analysis detects the spatiotemporal causal relationships among various links to select the most informative features for the MTL model. Bayesian optimi...
Article
The equity of right-of-way is an important topic in traffic management and control. With the balance consideration of traffic equity and efficiency, which are respectively evaluated by the Atkinson index and average travel time, this study proposes a bi-objective signal timing simulation-based optimization (SO) model under uncertainties, and solve...
Article
This study addresses a network-wide signal timing optimization problem with environmental concerns by a bi-objective stochastic simulation-based optimization (BOSSO) method. In this method, the global samples evaluated by costly simulation are used to build a type of surrogate model named the regressing Kriging model, which are then employed to pre...
Article
Full-text available
Vehicle to anything (V2X), especially vehicle-to-vehicle (V2V) technology, is regarded as a promising technology to improve traffic efficiency and safety. Under V2V environment, drivers can communicate with each other, and obtain the real-time information of followers, besides of that from the preceding vehicle. According to the condition of sendin...
Article
This paper employs Next Generation Simulation (NGSIM) trajectory data to empirically validate the vehicle type-dependent car-following heterogeneity from both micro- and macro-aspects, and to address the contradictory findings about this type of heterogeneity in previous studies. Regarding the micro-viewpoint, traffic conflict analysis techniques a...
Article
Transportation corridors have backwash-spread effects to its surrounding areas on diverse resources, which is the main factor of regions' generation and expansion. This paper defines corridor field potential energy based on the gravitational field theory to evaluate the backwash-spread effects of major transportation corridors, so as to quantify th...
Article
Full-text available
This study proposes a feature selection based approach to identify reasonable spatial-temporal traffic patterns related to the target link, in order to improve the online-prediction performance. The prediction task is composed of two steps: one hybrid intelligent algorithm based feature selector is proposed to optimize original state vectors, which...
Article
Full-text available
To mitigate traffic oscillations that usually sustainably propagate upstream, this paper proposes a jam-absorption driving (JAD) strategy in the framework of Newell's car-following theory. The basic idea of the JAD strategy is to guide a vehicle to move slowly before being captured by an oscillation, and terminate the slow movement when the vehicle...
Article
Full-text available
In the era of big data, mining data instead of collecting data is a new challenge for researchers and engineers. In the field of transportation, extracting traffic dynamics from widely existing probe vehicle data is meaningful both in theory and practice. Therefore, this paper proposes a simple mapping-to-cells method to construct a spatiotemporal...
Article
The well-known spatiotemporal traffic diagram is a popular and powerful tool in the field of transportation research and practice. It is an important basis of analyzing traffic conditions, identifying bottlenecks, and controlling and routing traffic. Traditionally, the spatio-temporal diagram is constructed by using stationary detector data, and li...
Article
Anisotropy is the property that macroscopic traffic flows essentially preserve. Therefore, an anisotropic higher-order continuum model is derived from a simplified Helly’s model with only the forward-looking traffic information. Its admissibility of a wide cluster solution is then analyzed in detail by an analytical technique based on the nonlinear...
Article
Full-text available
Under the traffic environment of the Internet of Vehicles, especially with the development of vehicle-to-vehicle technologies (i.e., V2V), drivers not only frequently perceive the vehicle information for preceding vehicles but can also actively check the real-time information of following vehicles with the assistance of V2V technologies. However, t...
Article
Optimal sensor placement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate sensor failure into the optimal sensor placement model. In this article, a two-stage stochastic model is proposed for the purpose of trave...
Article
Full-text available
Variable message signs that provide various types of route guidance information have been widely deployed in large cities. To release proper information only using easily collected data, a simple traffic-condition-based (TCB) route guidance strategy was recently proposed. The strategy works based on the estimation of free-flow and congested traffic...
Article
Full-text available
Car-following models are always of great interest of traffic engineers and researchers. In the age of mass data, this paper proposes a nonparametric car-following model driven by field data. Different from most of the existing car-following models, neither driver's behaviour parameters nor fundamental diagrams are assumed in the data-driven model....
Article
Full-text available
The paper proposes a car following model from the perspective of visual imaging (VIM), where the visual imaging size of the preceding vehicle on a driver's retina is considered as the stimuli and determines the driving behaviors. NGSIM trajectory data are applied to calibrate and validate the VIM under two scenarios, i.e. following the car and foll...
Article
Full-text available
Heterogeneity is an essential characteristic in car-following behaviours, which can be defined as the differences between the car-following behaviours of driver/vehicle combination under comparable conditions. This paper proposes a visual imaging model (VIM) with relaxed assumption on (1) a driver's perfect perception for the states of the neighbou...
Article
Full-text available
The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, t...
Article
Various studies have been conducted concerning vehicles’ crashworthiness and crash aggressivity. This paper aims to propose a crash-level approach to combine motor vehicles’ crashworthiness and crash aggressivity into an integrated index, which is expressed as the total secondary safety index (TSSI). A Bayesian ordered logit model was proposed to e...
Article
Mixed traffic without signal control is complicated. This paper proposes a pedestrian–vehicle cellular automata (CA) model to study the characteristics of the mixed traffic. The model includes two sub models. One is the pedestrian model, in which the heterogeneity is taken into consideration. The other is the vehicle model, in which a safely runnin...
Article
The safety level of signalized intersection depends greatly on drivers' decision-making behaviors, which are significantly influenced by the time-reminder strategy before amber of the signal device. However, previous related studies are mainly based on the statistical results from the field data rather than explore the influence mechanism of the si...
Article
Full-text available
As traffic phenomena can be explained by physical method, this interdisciplinary domain has attracted many physicists to explore. The primary object of this research is to reveal the physical characteristics of heterogeneous nonmotorized vehicle traffic composing of conventional bicycles and electric bicycles. Cellular automaton (CA) model is an ef...
Article
This paper explores the "lane-changing preparation process," defined as the synchronization process, from a new, integrated perspective. A comprehensive study was conducted to analyze the behavioral characteristics of the speed synchronization process of merging vehicles from entrance ramps by tracking their trajectories in the merge lanes. On the...
Article
The paper proposes an improved monkey optimization algorithm with dynamic adaptation. In the algorithm, the chaotic search method instead of random process is employed to generate random numbers in initialization process, climb process and watch-jump process so as to avoid repeating search in the same neighborhood. Moreover, two parameters (the evo...
Article
The traditional cellular automaton (CA) model assumes that drivers only receive information from the preceding vehicles, e.g. the brake light information. However, in reality, drivers not only perceive information from downstream but can also get upstream information, e.g. the honk stimulation. The CA model involving traffic information from downst...
Article
Due to the poor road markings and irregular driving behaviors, not every vehicle is positioned in the center of the lane. The deviation from the center can cause discomfort to drivers in the neighboring lane, which is referred to as lateral discomfort (or lateral friction). Such lateral discomfort can be incorporated into the driver stimulus–respon...
Article
Full-text available
This paper focuses mainly on the stability analysis of two-lane traffic flow with lateral friction, which may be caused by irregular driving behavior or poorly visible road markings, and also attempts to reveal the formation mechanism of traffic jams. Firstly, a two-lane optimal velocity (OV) model without control signals is proposed and its stabil...
Article
This paper deals mainly with the influence of lane changing behaviours on the stability of two-lane traffic flow under a periodic boundary condition. Following the description of an optimal velocity model for two vehicle groups and the derivation of their stability conditions, the feedback signals, which involve information about vehicles from both...
Article
Full-text available
The paper mainly studies the following vehicle’s honk effect on the driver of its predecessors in the single-lane cellular automaton model (CA model); besides, the determined condition of honk’s state is investigated in detail, which has seldom been studied before. Then, the influence of honk sensitivity threshold and slow-to-start sensitivity thre...
Article
On the basis of the research of driving behavior, by analyzing the mechanism of driving behavior and using the cellular automaton (CA) model, we introduce the mechanism of driving behavior, which is associated with the vehicle's own speed, the relative speed, the vehicle spacing, and the safety vehicle spacing, into the CA model (ACA). We observe t...

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Projects

Projects (2)
Project
Towards predicting or estimating traffic states with classical and newly-emerging methods, which play an important role in ITS or Smart Transportation.
Project
Intelligent Vehicles & Future Transportation