Xuesong Wang

Tongji University · College of Transportation Engineering

Car-following (CF) modeling, a fundamental component in microscopic traffic simulation, has attracted increasing interest of researchers in the past decades. In this study, we propose an adaptable personalized car-following framework -MetaFollower, by leveraging the power of meta-learning. Specifically, we first utilize Model-Agnostic Meta-Learning...

Truck crashes are generally more serious than passenger vehicle crashes, and they cause more deaths per crash worldwide per the U.S. Department of Transportation’s Fatality Analysis Reporting System. Risk assessment and factor analysis are the keys to preventing truck crashes, but research on commercial trucks has been limited. Currently, freight a...

Autonomous vehicles (AVs) have the potential to significantly revolutionize society by providing a secure and efficient mode of transportation. Recent years have witnessed notable advancements in autonomous driving perception and prediction, but the challenge of validating the performance of AVs remains largely unresolved. Data-driven microscopic t...

This study is about smallest acceptable sample size determination in experimental design studies involving a driving simulator. The smallest acceptable sample size should be specified so researchers can make accurate inferences about their studied populations. However, the number of samples typically collected is largely subject to the expense of d...

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style throug...

Prediction, decision-making, and motion planning are essential for autonomous driving. In most contemporary works, they are considered individual modules or combined into a multi-task learning paradigm. However, we argue that they should be integrated into a comprehensive framework. Although several recent approaches follow this scheme, they suffer...

Crashes caused by problems with bus drivers’ physical and mental health have increased in frequency in recent years. Insomnia, a common type of sleep problem, has significant positive relationships with both crash risk and mental health problems, especially anxiety and depression, which are themselves associated with driving behavior. However, few...

Car-following is a control process in which a following vehicle adjusts its acceleration to keep a safe distance from the lead vehicle. Recently, there has been a booming of data-driven models that enable more accurate modeling of car-following through real-world driving datasets. Although there are several public datasets available, their formats...

Exploring and analyzing safety influencing factors can guide targeted traffic safety management. Traditional traffic safety models are aimed at specific data problems and making adjustments to the model structure, which lack focus on predictive ability and have limited information on the analysis of influencing factors. In recent years, machine-lea...

Among traffic crashes, truck crashes are usually more severe and cause greater harm to other involved traffic participants, particularly vulnerable road users such as the drivers of two-wheelers. Automatic emergency braking (AEB), also known as autonomous emergency braking, has been demonstrated to be a safe, efficient, and high benefit–cost ratio...

The Manchester Driver Behavior Questionnaire (DBQ) is a widely used self-reported measure of aberrant driving behaviors. It provides a standardized way of evaluating drivers' safety awareness and motivation, but the effectiveness of the DBQ's application in different regions can be influenced by culture, social norms, and time period. Several studi...

Car-following models are calibrated to account for various driver behaviors such as speed and space headway. Because drivers do not all drive the same way, they are typically classified based on their level, or profile, of aggressiveness. This approach to model calibration assumes that a single set of car-following parameters applies to an individu...

The two-wheeler (TW) is a popular means of transportation in China, but TWs often suffer from serious traffic crashes because of their highly flexible trajectory and low detectability. Therefore, they present a challenge for the sensing and decision-making systems in autonomous vehicles (AVs). Collision avoidance systems, such as automatic emergenc...

The motion system is a major component of a driving simulator. It provides motion cues in various directions with different degrees of freedom (DOF). Different DOF could influence response variables widely used in highway design safety evaluation conducted in simulators. Few studies, though, have comprehensively explored the effect of driving simul...

Driving Simulator, a powerful simulation tool, has already been used in safety evaluation of roadway geometric design during the pre-construction design stage. Conventional ways of estimating proper sample size include the empirical method, the resource equation, power analysis, and the Bayesian method. However, significant boundaries and prior dis...

Learning-based approaches hold great potential for autonomous urban driving motion planning. Compared to traditional rule-based methods, they offer greater flexibility in planning safe and human-like trajectories based on human driver demonstration data and diverse traffic scenarios. Frenet planning is widely applied in autonomous driving motion pl...

In public road tests of autonomous vehicles in California, rear-end crashes have been the most common type of crash. Collision avoidance systems, such as autonomous emergency braking (AEB), have provided an effective way for autonomous vehicles to avoid collisions with the lead vehicle, but to avert false alarms, AEB tends to apply late and hard br...

Assuring the safety of all road users, including non-motorized vehicles, is important in the autonomous driving environment. Autonomous emergency braking (AEB) systems have provided an effective way for automated vehicles to avoid collisions with the less easily detectable non-motorized vehicles. Automatic preventive braking (APB) is a new method p...

Understanding crash causation to the extent needed for applying countermeasures has always been a focus as well as a difficulty in the field of traffic safety. Previous research has been limited by insufficient crash data and analysis methods more suitable to single crashes. The use of crashes and near crashes (CNCs) and naturalistic driving studie...

The Responsibility-Sensitive Safety (RSS) model was proposed by Mobileye as a mathematical model that defines the real-time safety distance that the automated vehicle (AV) needs to maintain from surrounding vehicles. However, RSS strategy tends to be overly conservative. This research made modifications to the RSS safe distance to reduce its conser...

Freeway crash prediction models are the basic of traffic safety research, yet crash occurrence and the influencing factors change over time. In order to make sure the implemented safety models fit the current traffic environment, this study conducts a comparative analysis of 2017 and 2020 datasets collected from freeways in Suzhou, China. Consideri...

In-Vehicle Information (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers. The interface design, especially the quantity of icons presented to the driver such as those for navigation, music, and phone calls, ha...

The safe operation of automated vehicles (AVs) is now on the research agenda, with attention to the AV’s operational design domain (ODD), which defines the conditions in which its driving automation system is designed to function. Due to the limited sight line on freeway entrance terminals, crashes involving AVs continue to occur during the merging...

Increasingly, drivers are choosing to buy usage-based automobile insurance (UBI). Manage-how-you-drive (MHYD) insurance, a new type of UBI, incorporates active safety management to monitor driver behavior and issue warnings as needed. While researchers have introduced telematics data into automobile insurance pricing, the specific effect of in-vehi...

On the evening of March 18, 2018, an automated vehicle (AV) struck and killed a 49-year-old pedestrian in Tempe, AZ, as she crossed the road. From about 2 weeks before the crash through April 30, 2018, an online survey, designed to address U.S. public perceptions of AVs among vulnerable road users, was distributed to adult U.S. residents. Survey re...

A driving strategy for autonomous vehicles (AVs) that is consistent with human behavior while demonstrating superior performance seems to have a good chance to be accepted by early AV users and be successful in the long run. Most of the past research focused on motion strategies affected by the presence of other vehicles. On the other hand, AV not...

Distracted driving such as phone use during driving is risky, as it increases the probability of severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in existing studies, and most of them used facial motions, which would be highly influenced by light conditions and algorithm effectiveness, still could not fully ind...

The departure sight triangle provides the view for the vehicle waiting to cross at the two-way stop-controlled intersection. The factors influencing the sight triangle for human drivers are considered in the 2018 AASHTO Green Book, but the Green Book lacks quantitative estimations for automated vehicles (AVs). Therefore, to guarantee the AV’s opera...

Car-following refers to a control process in which the following vehicle (FV) tries to keep a safe distance between itself and the lead vehicle (LV) by adjusting its acceleration in response to the actions of the vehicle ahead. The corresponding car-following models, which describe how one vehicle follows another vehicle in the traffic flow, form t...

The rear-end crash is one of the most common types of crashes, and key risk factors have been broadly identified in the car-following behaviors preceding a crash. However, the relationships between rear-end crash risk and daily car-following behaviors, or habits, have not been well examined. This study aims to identify the daily car-following behav...

Freeways in China have developed rapidly in recent years. The large traffic volumes and high travel speeds have created a serious safety problem that is of growing concern, however. Accurate identification of factors influencing crashes is a prerequisite for implementing countermeasures, but unobserved heterogeneity in crash data can lead to errone...

To ensure improvements are made in the parts of the city currently most prone to crashes, this study conducted a 2009-2016 longitudinal comparison of the traffic safety in Shanghai at the level of the traffic analysis zone (TAZ). The police-reported crashes occurring in 2009 and 2016 within the downtown areas of Shanghai were examined to acquire a...

Sight distance is an important indicator of vehicle safety at intersections. Traditional intersection design methods might be not suitable for the autonomous vehicle (AV) because its perception differs from that of the human driver, on which AASHTO Greenbook 2018 are based. Since, to guarantee future operational safety, intersection design needs to...

In recent years, the development and testing of autonomous driving technology have become widespread around the world. However, due to differences in perception abilities between autonomous vehicles and human drivers, the current geometric design controls for highway alignments, designed for the human driver, may not be applicable to the autonomous...

Micro-mobility vehicles such as electric bicycles, or e-bikes, are becoming one of the essential transportation modes in metropolitan areas, and most deliveries in large cities are dependent on them. Due to the e-bike’s popularity and vulnerability, e-bike crash occurrence has become a major traffic safety problem in many cities across the world; f...

Data-based research approaches to generate crash scenarios have mainly relied on conventional vehicle crashes and naturalistic driving data, and have not considered differences between the autonomous vehicle (AV) and conventional vehicle crashes. As the AV’s presence on roadways continues to grow, its crash scenarios take on new importance for traf...

Ranking sites with promise is an essential step for cost-effective engineering improvement on roadway traffic safety. This study proposes a Bayesian multivariate spatio-temporal interaction model based approach for ranking sites. The severity-weighted crash frequency and crash rate are used as the decision parameters. The posterior expected rank an...

Safety performance functions (SPFs) are indispensable analytical tools that usually play a crucial role in estimating crash frequencies, identifying hotspots, analyzing crash contributing factors, and assessing the effectiveness of safety countermeasures. Due to the limited availability of safety data, municipalities tended to adopt SPFs from Highw...

Although traffic crashes involving buses are less frequent than those involving other vehicle types, the consequences of bus crashes are high due to the potential for multiple injuries and casualties. As driver error is a primary factor affecting bus crashes, driver safety education is one of the main countermeasures used to mitigate crash risk. In...

Accurate identification of crash hotspots forms the foundation of roadway safety improvement. The Highway Safety Manual micro-level approach uses individual intersections and road segments as analysis units, and correspondingly identifies some isolated road entities as hotspots. However, because traffic police and administrative agencies routinely...

The ability of automated vehicles (AV) to avoid accidents in complex traffic environments is the focus of considerable public attention. Intel has proposed a mathematical model called Responsibility-Sensitive Safety (RSS) to ensure AVs maintain a safe distance from surrounding vehicles, but testing has, to date, been limited. This study calibrates...

Operating speed is often used to evaluate consistency in road geometric design. In the China, the Specifications for Highway Safety Audit includes a spot-based speed model that predicts operating speed by dividing the road into homogeneous segments and observing the speeds at sparsely spaced spots. This paper presents a continuous speed model as a...

Traffic crashes at signalized intersections are frequently linked to driver behavior at the onset of the circular yellow (CY) indication. To better understand behavioral factors that influence a driver’s decision to stop or go at an intersection, this study analyzed the behavior of the driver of a subject vehicle at the onset of the CY indication....

Safety guarantees are vital to the dependability of the automated vehicle (AV), so are of primary concern to the AV industry and regulatory bodies. Responsibility-Sensitive Safety (RSS), proposed by Mobileye, is a rigorous mathematical model that defines the real-time safety distance that the AV needs to maintain in relation to surrounding vehicles...

With a growing population, bus service is an efficient mode of transportation in cities. However, traffic crashes involving buses can bring more casualties and economic losses. Bus drivers, an integral part of this service, should be monitored closely. Job satisfaction, an overlooked criterion in the industry, is a crucial component that often lead...

To comprehensively identify the factors with significant impacts on freeway crash frequency, the crash, roadway, traffic and weather data from Kaiyang Freeway in Guangdong Province in 2014 were collected. The whole freeway was split into 154 segments on the basis of homogeneity in horizontal curvature and vertical grade. A spatio-temporal interacti...

Cell phone use while driving is becoming a key problem in traffic safety as it causes visual-manual distraction and has been linked to increases in crash rates. The use of hand-held phones has been banned in several countries, yet research comparing the safety of hands-free phone use with hand-held has produced inconsistent results. Analysis of spe...

Safer roads and police enforcement are closely associated since the latter directly encourages road users to improve their behavior by complying with basic traffic rules and laws. Understanding the relationships between police enforcement, driving behavior, and traffic safety is a prerequisite for optimizing enforcement strategies. However, there i...

Safety is an important challenge in the development of autonomous vehicles (AVs). To ensure the safety of AVs, Intel and Mobileye have proposed a model called Responsibility-Sensitive Safety (RSS). Previous studies have shown that RSS has the potential to improve the safety performance of AVs, especially for partial autonomous driving algorithms. H...

Road traffic accidents (RTA) are one of the major public health issues in Ethiopia and a big challenge for the government to tackle. This study aims to find out the spatiotemporal distribution of RTAs in the Dire Dawa city of Ethiopia and identify the major factors contributing to the RTAs. Locations of the black-spots are identified using the crit...

Operating speed profiles represent drivers’ responses to roadway geometry and are widely used to evaluate safety performance of roadway design. To predict operating speed profile, the majority of early research followed a two-step modeling procedure: (1) estimate speeds at start, middle, and end points of road segments, and (2) fill the profile bet...

A model used for velocity control during car following is proposed based on reinforcement learning (RL). To optimize driving performance, a reward function is developed by referencing human driving data and combining driving features related to safety, efficiency, and comfort. With the developed reward function, the RL agent learns to control vehic...

Given the potential difference in drivers’ route familiarity, this study aims to investigate the respective factors contributing to local-vehicle and non-local-vehicle crashes on freeway. Crash data from Kaiyang Freeway in Guangdong Province, China in 2014 are collected for the investigation, where the crashes with all involved vehicles registered...

Drowsy driving is one of the main causes of traffic crashes, a serious threat to road traffic safety. The effective early detection of a drowsiness state can help provide a timely warning for drivers, but previous studies have seldom considered the cumulative effect of drowsiness over time. The purpose of this study is therefore to establish a mode...

The crash prediction model is a useful tool for traffic administrators to identify significant risk factors, estimate crash frequency, and screen hazardous locations, but some jurisdictions interested in traffic safety analysis can collect only limited or low-quality data. Existing crash prediction models can be transferred if calibrated, but the c...

Safety performance function (SPF) has been a vital tool in traffic safety evaluation including finding contributing factors to crashes, identifying hotspots, and assessing safety effects of countermeasures. In the United States (U.S.), the Highway Safety Manual provides a number of SPFs for a variety of road facilities. Due to the limited availabil...

The urban expressway system serves as a key role in the roadway transportation system. It provides an efficient and comfortable approach for long-distance travel within the city. However, the safety status of the urban expressways is becoming a critical issue as the high-frequent traffic crashes have severely influenced the traffic operations. Amon...

Forward collision warning (FCW) systems function by alerting drivers to upcoming hazards ahead and have been shown to help drivers respond more quickly under emergency situations. As FCW directly affects how vehicles interact longitudinally with one another, it may also influence car-following behavior such as reaction time, which has been little r...

Single-vehicle (SV) and multi-vehicle (MV) crashes have been recognized as differing in spatial distribution and influencing factors, but little consideration has been given to these differences as related to hotspot identification. For the purpose of better hotspot identification, this study aims to analyze influencing factors of SV and MV crashes...

Car-following behavior is a basic micro-driving behavior. Previous researches have been devoted to modeling car-following behaviors in western countries, with few studies focused in China. Shanghai naturalistic driving study (SH-NDS) is China’s first naturalistic driving study, which provides high-precision microscopic driving behavior data. Based...

Longitudinal acceleration of a vehicle represents the change of driver’s speed, and the drastic change of speed indicates undesirable designs. However, for the adjacent combined sections, there is still no scientific and effective acceleration prediction method. To accommodate this limitation, a new modeling approach based on frequent and equidista...

The Manchester Driver Behavior Questionnaire (DBQ) identifies risky driving behaviors resulting from psychological mechanisms. Investigating the relationships between these behaviors and drivers’ crash risk can provide a better understanding of the personal factors contributing to the incidence of crashes, allowing the more effective development of...

Excessive longitudinal deceleration and acceleration reduce driving comfort and increase safety risk. There is a dearth of research, however, on how geometric design characteristics, especially complex alignments and their adjacent segments, affect deceleration and acceleration. The Tongji University driving simulator was used to collect vehicle op...

Analysis of lane change is important for microsimulation and safety improvement, and can also provide reference for advanced driver assistance systems (ADAS) and connected and autonomous vehicles (CAVs). Yet little research has comprehensively explored lane changing, particularly in China, a site of current CAV testing. This study developed an auto...

Safety performance functions (SPFs), or crash-prediction models, have played an important role in identifying the factors contributing to crashes, predicting crash counts and identifying hotspots. Since a great deal of time and effort is needed to estimate an SPF, previous studies have sought to determine the transferability of particular SPFs; tha...

Continuing rapid growth in Shanghai, China, requires traffic safety to be considered at the earliest possible stage of transport planning. Macro-level traffic safety studies have been carried out extensively in many countries, but to date, few have been conducted in China. This study developed a macro-level safety model for 263 traffic analysis zon...

To identify the timing of drowsiness driving warning is the key issue and a bottleneck of onboard drowsiness driving warning technology. Finding a rationale for warning timing using driver's driving behavior response feature is an innovation. Therefore, after conducting a driving simulator experiment under the influence of drowsiness alarming, eye...

A model used for velocity control during car following was proposed based on deep reinforcement learning (RL). To fulfil the multi-objectives of car following, a reward function reflecting driving safety, efficiency, and comfort was constructed. With the reward function, the RL agent learns to control vehicle speed in a fashion that maximizes cumul...

Cut-in maneuvers, when vehicles change lane and move closely in front of a vehicle in the adjacent lane, are very common but adversely affect roadway capacity and traffic safety. Yet little research has comprehensively explored cut-in behavior, particularly in China, which has a challenging driving environment and is often used for connected and au...

Cell phone use while driving is becoming a key problem for traffic safety. To identify the characteristics of driver’s phone use; analyze its influence on driving performance, and explore factors influencing drivers’ speed change during phone use, 52 drivers’ 1,244 phone use events from the first naturalistic driving data in China was used. Because...

This study proposes a framework for human-like autonomous car-following planning based on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation environment where an RL agent learns from trial and error interactions based on a reward function that signals how much the agent deviates from the empirical data. Through...

Real-time safety analysis has been widely adopted to reveal the relationship between real-time traffic characteristics and crash occurrence, and these results could be applied to improve active traffic management systems and enhance safety performance. Most of the previous studies have been applied to freeways and seldom to arterials. This study at...

With the development of society, the number of vehicles increases rapidly. The vehicle plays an important role in people's life, however the problem of traffic safety caused by vehicles has also become increasingly prominent. In China, the high crash rate and casualty rate on expressways have always troubled traffic management department. So crash...

Speed variation on urban expressways has been frequently noted as a key factor associated with high crash risk. However, it was often difficult to capture the safety impact of speed variance with spaced sensor measurements. As an alternative, this paper aims to leverage the use of the floating car data (FCD) to capture the speed variance in a morni...

Five car-following models were calibrated, validated and cross-compared. The intelligent driver model performed best among the evaluated models. Considerable behavioral differences between different drivers were found. Calibrated model parameters may not be numerically equivalent with observed ones.

Real-time crash risk evaluation is an emerging analysis topic which can identify crash-prone traffic conditions and further benefit the implementation of the active traffic safety management systems on urban expressways. Studies have been conducted to develop crash risk evaluation models with different modeling techniques. However, they were develo...