Showing papers in "Transportation Research Record in 2020"
TL;DR: In this paper, a growing number of industrial wastes and recycled materials have been utilized in the pavement industry to preserve natural resources, and the concept of sustainable pavement gains prominence, and a number of projects have been proposed.
Abstract: As the concept of sustainable pavement gains prominence, a growing number of industrial wastes and recycled materials have been utilized in the pavement industry to preserve natural resources. This...
122 citations
TL;DR: This study takes advantage of publicly available but not readily accessible e-scooter share data in Washington, D.C. for an initial view of the travel patterns and behaviors related to this new mode, and adopts an innovative approach to scrape and process general bikeshare feed specification data in real time for e- scooter share.
Abstract: The proliferation of micromobility, evolving from station-based to dockless bikeshare programs, has dramatically accelerated since 2017 with an influx of investment from the private sector to a new...
78 citations
TL;DR: An experimental campaign with five vehicles equipped with ACC was conducted at the proving ground of AstaZero in Sweden to improve understanding on the properties of ACC systems and their functionality under real driving conditions, with main parameters under investigation are the response time of controllers, the available time headway settings, and the stability of the car-platoon.
Abstract: Adaptive cruise control (ACC) systems are standard equipment in many commercially available vehicles. They are considered the first step of automation, and their market penetration rate is expected...
69 citations
TL;DR: In this article, an automated pavement distresses detection using road images remains a challenging topic in the computer vision research community, and recent developments in deep learning have led to considerable researches.
Abstract: Automated pavement distresses detection using road images remains a challenging topic in the computer vision research community. Recent developments in deep learning have led to considerable resear...
68 citations
TL;DR: An end-to-end machine learning model for predicting lane-change maneuvers from unlabeled data using a limited number of features is developed and presented and results show that lane changes can efficiently be predicted in real-time, with an average detection time of at least 3 s with a small percentage of false alarms.
Abstract: Highway safety has attracted significant research interest in recent years, especially as innovative technologies such as connected and autonomous vehicles (CAVs) are fast becoming a reality. Ident...
60 citations
TL;DR: A two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact is proposed and a new loss function that considers the volume impact in speed prediction is developed.
Abstract: Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing ...
54 citations
TL;DR: Results show that adopting the CACC system in a five-vehicle platoon substantially reduces the driving volatility and reduces the risk of rear-end collision which consequently improves safety and decreases fuel consumption and emissions compared with the ACC system and manually-driven vehicles.
Abstract: Connected and automated vehicle technologies have the potential to significantly improve transportation system performance. In particular, advanced driver-assistance systems, such as adaptive cruis...
52 citations
TL;DR: A long short-term memory neural network is established and trained to predict pedestrians’ red-light crossing intentions and has an accuracy rate of 91.6% based on internal testing at one signalized crosswalk.
Abstract: Traffic violations of pedestrians at intersections are major causes of road crashes involving pedestrians, especially red-light crossing behaviors. To predict the pedestrians’ red-light crossing in...
52 citations
TL;DR: In this paper, traffic patterns have complex spatial and temporal dependencies that make accurate forecasting on large-scale data sets difficult to be achieved on large datasets, which makes it critical to developing adaptive strategies for mobility.
Abstract: Traffic forecasting approaches are critical to developing adaptive strategies for mobility. Traffic patterns have complex spatial and temporal dependencies that make accurate forecasting on large h...
37 citations
TL;DR: The road transport sector in India is on the cusp of a transition to battery electric vehicles (BEVs) from internal combustion engines (ICEs), and the Government of India (GoI) has announced several policy changes as discussed by the authors.
Abstract: The road transport sector in India is on the cusp of a transition to battery electric vehicles (BEVs) from internal combustion engines (ICEs). Government of India (GoI) has announced several policy...
34 citations
TL;DR: A Bayesian optimization framework for the high-dimensional calibration problem of transportation simulation models, which shows a better convergence and a higher computational efficiency than SPSA.
Abstract: The parameters of a transportation simulation model need to pass through a careful calibration process to ensure that the model’s output is as close as possible to the actual system. Owing to the c...
TL;DR: Rubber swelling in bitumen, which is a diffusion-induced volume expansion process, plays a dominant role in the design of crumb rubber modified bitumen binders and their properties development as discussed by the authors.
Abstract: Rubber swelling in bitumen, which is a diffusion-induced volume expansion process, plays a dominant role in the design of crumb rubber modified bitumen binders and their properties development. Thi...
TL;DR: An improved multi-scale and multi-feature tracking algorithm based on a kernel correlation filter (KCF) algorithm is proposed to avoid the KCF extracting single features and single-scale defects and obtains accurate vehicle counting results which can meet real-time processing requirements.
Abstract: Using deep learning technology and multi-object tracking method to count vehicles accurately in different traffic conditions is a hot research topic in the field of intelligent transportation. In t...
TL;DR: Both theoretical analysis and simulation results show that the delay-compensating CACC has better string stability and traffic flow stability than the widely-used CACC system and shows the potential for improving traffic throughput and fuel efficiency.
Abstract: Communication delay is detrimental to the performance of cooperative adaptive cruise control (CACC) systems. In this paper, we incorporate communication delay explicitly into control design and pro...
TL;DR: In this paper, a micro-modeling TNC operation is essential for large-scale transportation network companies (TNCs) in metropolitan areas across the world, and it is shown that such a system can increase the share of total trips in cities across the globe.
Abstract: Transportation Network Companies (TNCs) have been steadily increasing the share of total trips in metropolitan areas across the world. Micro-modeling TNC operation is essential for large-scale tran...
TL;DR: In the past decade, transportation network companies (TNCs) such as Uber, Lyft, and Via have established themselves as a viable transportation alternative to other modes as mentioned in this paper, however, the popularity of TNCs has waned.
Abstract: In the past decade, transportation network companies (TNCs) such as Uber, Lyft, and Via have established themselves as a viable transportation alternative to other modes. However, the popularity of...
TL;DR: A Bayesian simulation-based optimization method for calibrating the effective train capacity is introduced, which explicitly recognizes that capacity may be different at different stations depending on congestion levels.
Abstract: This paper proposes a general network performance model (NPM) for monitoring the performance of urban rail systems using smart card data. NPM is a schedule-based network loading model with strict c...
TL;DR: In this article, a modal change can be achieved by either introducing restrictions on the use of private vehicles (PVs) or using public transport (PT) to draw travelers away from private vehicles over to public transport.
Abstract: Urban traffic levels can be reduced by drawing travelers away from private vehicles (PV) over to using public transport (PT). This modal change can be achieved by either introducing restrictions on...
TL;DR: A support vector machine (SVM) model is employed to explore the non-linear relationship between flight delay outcomes and reveals that factors such as pushback delay, taxi-out delay, ground delay program, and demand-capacity imbalance are significantly associated with flight departure delay.
Abstract: The expected growth in air travel demand and the positive correlation with the economic factors highlight the significant contribution of the aviation community to the US economy On‐time operati
TL;DR: This study developed a model that simultaneously uses objective and subjective variables to estimate the pedestrian perception of sidewalks’ QoS in Bogota, Colombia and proposed guidelines that provide decision makers with the tools to identify which sidewalk attributes actually influence pedestrians’ perception of QoS.
Abstract: A variety of different pedestrian performance or service indicators (PPSI), such as the pedestrian level of service (PLOS), or quality of service (QoS), have been developed to evaluate pedestrian i...
TL;DR: In this article, the authors examined the factors that influence travelers' mode choice between transit and ridesourcing, for two distinct market segments, i.e., transit users in a regu...
Abstract: This paper presents the results of a study that examines the factors that influence travelers’ mode choice between transit and ridesourcing, for two distinct market segments—transit users in a regu...
TL;DR: This paper proposes a methodology to map potholes along the road surface using ultra-high accuracy LiDAR units onboard a wheel-based mobile mapping system and it is observed to accurately detect pothole with varying severity and different causes.
Abstract: Pavement distress or pothole mapping is important to public agencies responsible for maintaining roadways. The efficient capture of 3D point cloud data using mapping systems equipped with LiDAR eli...
TL;DR: In this paper, the authors proposed that road freight transport is believed to be the first transport domain in which driverless (DL) vehicles will have a significant impact, but almost no attention has been paid to it.
Abstract: Road freight transport is believed by many to be the first transport domain in which driverless (DL) vehicles will have a significant impact. However, in current literature almost no attention has ...
TL;DR: Public transit disruption is becoming more common across different transit services, and can have a destructive influence on the resiliency of the transportation system as mentioned in this paper, even though transit agencie...
Abstract: Public transit disruption is becoming more common across different transit services, and can have a destructive influence on the resiliency of the transportation system. Even though transit agencie...
TL;DR: In this paper, the increase in the axle loads and frequency of operations of over-weight (OW) torsion vehicles was studied in the energy sector across the United States.
Abstract: Recent traffic trends and permit issuance show significant mobility demands in the energy sectors across the nation. The increase in the axle loads and frequency of operations of over-weight (OW) t...
TL;DR: In this paper, the authors analyzed the performance of light detection and ranging (Lidar) sensor performance on detecting pedestrians under different weather conditions and found that Lidar sensor is the key sensor in autonomous vehicles.
Abstract: This paper intends to analyze the Light Detection and Ranging (Lidar) sensor performance on detecting pedestrians under different weather conditions. Lidar sensor is the key sensor in autonomous ve...
TL;DR: A smooth-switching control-based CACC scheme with IFT optimization (CACC-SOIFT) by implementing a bi-layer optimization model and a Kalman predictor that can guarantee string stability and riding comfort in the environment of dynamic IFT.
Abstract: Vehicle-to-vehicle communications can be unreliable because of interference and information congestion, which leads to the dynamic information flow topology (IFT) in a platoon of connected and auto...
TL;DR: Road networks are critical to a community's ability to recover from a disaster and the ability to move goods and people efficiently is dramatically affected by disruptions to vulnerable components of the road network.
Abstract: Road networks are critical to a community’s ability to recover from a disaster. The ability to move goods and people efficiently is dramatically affected by disruptions to vulnerable components of ...
TL;DR: The results from the MARS model revealed that different factors including relative speed between lane-changing vehicle (LCV) and lead vehicle (LV)/following vehicle (FV), traffic conditions, acceleration of LCV and FV, and roadway geometric characteristics have significant effects on gap acceptance behavior.
Abstract: Gap acceptance is one of the crucial components of lane-changing analysis and an important parameter in microsimulation modeling. Drivers’ poor gap judgment, and failure to accept a necessary safet...
TL;DR: In this paper, the main challenge of prediction of dynamic demand in intelligent transportation systems is addressed, where real-time dynamic demand prediction is essential for planning and operations, and the main challenges of predicting dynamic or...
Abstract: Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic or...