Abstract In nowadays transportation networks, many multimodal itineraries are possible when traveling from an origin to a destination. Due to the plurality of alternatives, the choice of an option is difficult for the user. In this paper, we propose a novel decision support system to help users in that task. Our method ranks itineraries according to users’ preferences and trip profile based on a fuzzy

Abstract Real-time traffic movements at intersections is vital for transportation and traffic engineering. It helps in providing intersection traffic data and optimizing signal control plans. This study attempts to extend the data coverage by developing algorithms to estimate through and left-turn movements in real-time at signalized intersections. This study is the first attempt to estimate short-term

Abstract Developing appropriate modeling and simulation tools with the capability of analyzing traffic patterns, travel demand, and traveling/driving behavior responses at the regional level is important for the evaluation of active traffic management (ATM) and real-time transportation systems management and operations (TSM&O). In this paper, an integrated travel behavior and dynamic traffic assignment

(2021). Safety impacts and benefits of connected and automated vehicles: How real are they? Journal of Intelligent Transportation Systems: Vol. 25, No. 2, pp. 135-138.

Abstract Travel time distribution estimation is fundamentally important for the evaluation of travel time variability and reliability. For urban roads, signal delays are key components of travel time. They are stochastic and differ for vehicular movements due to different signal timings for through, left-turning, and right-turning vehicles. To better assist travelers in making trip decisions under

Abstract Traffic demands at intersections vary across various periods of a day and from day to day. Generally, fixed time traffic signals are designed considering the average traffic flows across multiple days over a predetermined time interval. This approach overlooks the day to day variability in traffic demand, leading to inefficient and unreliable signal control performance. A signal plan should

(2021). Correction. Journal of Intelligent Transportation Systems. Ahead of Print.

Abstract To alleviate parking problem and offer convenient and efficient service for drivers in parking selection, a smartphone-based parking guidance algorithm and system implementation architecture are proposed. The algorithm describes parking selection as multi-criteria decision making. Dijkstra algorithm is used to suggest the shortest path for the candidate parking lots. Travel cost criteria for

Abstract Nowadays, public transport is considered as an alternative to private vehicles to reduce environmental and social problems in developing countries. Hence, assuring a high passenger satisfaction level in the public transport system is an important task for municipalities and governments. However, passenger satisfaction evaluation of public transport is difficult as the opinions of passengers

Abstract Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using

Abstract It is of practical importance for individual vehicles to automatically identify traffic signal light status to facilitate their decision makings for traffic safety performance enhancement and operation efficiency maximization when they are approaching intersections, especially in near-future fully-or semi-autonomous vehicle-penetrated traffic systems. Traditional methods aim to directly extract

Abstract Reactionary delays that propagate from a primary source throughout train journeys are an immediate concern for British railway systems. Complex non-linear interactions between various spatiotemporal variables govern the propagation of these delays which can avalanche throughout railway network causing further severe disruptions. This paper introduces several machine learning (ML) techniques

Abstract To demonstrate the expected performance of an advanced driver assistance system (ADAS) in an intelligent or a highly automated vehicle test approaches should include a combination of simulations, track tests, and road tests. The main objective of our work was to propose a new evaluation approach conducted by an external entity where the vehicle is treated as a black box. This approach allowed

Abstract In this paper, we focus on a bi-objective school bus scheduling optimization problem, which is a subset of vehicle fleet scheduling problems to transport students distributed across a designated area to the relevant schools. The problem being proven as NP-hard in the literature, we propose an algorithm that seamlessly integrates a reinforcement learning approach with a genetic algorithm. Our

Abstract This paper presents a cost-effective strategy to reduce train delays by controlling passenger flow at the station entry. When a scheduled dwell time delay is likely to occur, the strategy reduces the number of passengers entering the platform by slowing down the opening speed of the automated fare collection (AFC) gates. The dwell time of the next train is predicted to enable proactive passenger

Abstract It’s often hard for existing mathematical models to unify and optimize all control variables including phase time, signal phase sequence, offset and signal cycle at the same time. An optimization model for regional green wave coordinated control based on Ring-and-Barrier structure under unsaturated signalized network is proposed in this study. The constraints of signal timing parameters, such

Abstract Given the aging infrastructure and the anticipated growing number of highway work zones in the United States, it is important to investigate methods to improve work zone mobility and safety. Data suggests that inappropriate merge maneuvers are a major contributing factor to highway work zone crashes that often lead to severe congestion and delay. This research proposes a New England Merge

Abstract Real-time queue length estimation and prediction provides useful information for proactively managing transportation networks. Queue spillback from off-ramps onto main lanes of freeways is one of the traffic issues caused by vehicular queues that can be efficiently managed using dynamic queue information. In this paper, a case-based reasoning algorithm combined with a Kalman filter is developed

Abstract Risky driving behaviors can cause accidents, which may result in major material and moral damages. Due to the increase in road accidents, it has become an important issue to identify risky driving behaviors and reward people who drive safely. With the development of technology, it is now possible to model driving behavior through advanced sensors integrated into embedded systems. In this study

Abstract Mobile devices and Internet-based applications are producing a significant volume of data that may be used to, at least partially, replace some of the hardware necessary to sense traffic systems. However, there are several issues related to such an agenda: data are heterogeneous, unstructured, may appear in natural language, are normally not geolocated, and there are balancing issues related

Abstract This study presents a multi-objective optimization model for the urban electric transit network problem with the aim of simultaneously designing the layout of bus routes, the frequency and the location and size of charging stations by making a tradeoff between two inconsistent objectives from the perspectives of passengers and operators. A Pareto artificial fish swarm algorithm (PAFSA) embedded

Abstract Travel time is one of the most important traffic parameters for travelers, traffic managers, planners, and operators alike. Travel time estimation is a significant component of any intelligent transportation systems (ITS) operations. In countries like India, which are at a nascent stage of ITS deployment, one of the main hurdles is the lack of accurate and automated systems for travel time

Abstract We conduct an examination of the preferences of drivers and passengers alike for in-vehicle interactions with a multistudy approach consisting of (1) a targeted literature survey of applications and user interfaces designed to support interactions with in-vehicle controls and systems based on gesture and voice input; (2) a large-scale survey (N = 160 participants) to understand drivers and

Abstract Automated vehicles (AVs, level 4) are coming on the market in forthcoming years, but it is unsure what is the operational capability of these vehicles in the first place. Especially in four-season countries, winter conditions, such as snowfall and minor amount of daylight hours, increase the operational requirements of AVs. In this study, the potential impacts of AVs on pedestrian safety are

(2020). Traffic and granular flow: the role of data and technology in the understanding of particle dynamics. Journal of Intelligent Transportation Systems: Vol. 24, Traffic and Granular Flow, pp. 535-538.

Abstract Connected and Automated Vehicles (CAVs) can potentially improve the performance of the transportation system by reducing human errors. This paper investigates the safety impact of CAVs in a mixed traffic with conventional vehicles at intersections. Analyzing real-world AV crashes in California revealed that rear-end crashes at intersections are the dominant crash type. Therefore, to enhance

Abstract This research investigated the impact of sensor camera misalignment on the quality of the lane keeping assistance, end user experience and driving performance. Testing was performed with 16 participants, both males and females, with an age range from 25 to 35. The Lane Keeping Assist System (LKAS) errors in lateral offset ranged from −0.66 m to 0.66 m and testing was performed on two roads

A cooperative lane-changing (CLC) motion planning algorithm for partially connected and automated environment is proposed in this study. Unlike conventional motion planner whose goal is merely enabling driving maneuver, this proposed algorithm takes one step further in terms of reducing oscillation and shockwave caused by lane change, hence improves transport mobility. The proposed motion planner is

Abstract This research, funded by the United States Department of Transportation Federal Highway Administration, is one of the early initiatives to investigate the potential of advanced technologies to improve pedestrian safety through vehicle automation and user notification. The research identified the need to develop standardized strategies with which to investigate the effectiveness and applicability

In transportation, LiDAR sensors have been primarily used in surveying and autonomous driving as a major onboard sensing device to detect field objects. Recently, with reduced price and increased demand from real-time and trajectory-level traffic detection, LiDAR technology sees great potential for becoming a mainstream means of infrastructure-based traffic detection other than only being used onboard

(2020). Correction. Journal of Intelligent Transportation Systems. Ahead of Print.

Motivated by military applications, this work considers connected platoons of ground vehicles of potentially different sizes and presents a model-free approach for optimizing the speed of the platoon to adjust the tradeoff between fuel economy and mobility as measured by travel speed. The motivation to seek a model-free solution is twofold: (1) vehicle models that are typically assumed to be available

The lane closures caused by the work zone at the approaches create a negative impact on the operational effectiveness of the signalized intersections. This paper presents an innovative design for intersections with work zones to improve the intersection’s practical capacity. In this design, the lanes in the leg with work zone can be used dynamically as approach and exit lanes during different periods

The growth of electronic commerce generates significant demand for the delivery of personal goods. Crowdsourcing applications have the potential to create more flexible alternatives to existing package-delivery services. However, the success of these applications is strongly related to the strategies of the crowd couriers, which are not well-understood in the current literature. In this paper, we analyzed

Ramp metering is a major measure to reduce traffic congestion and prevent traffic breakdown at on-ramp bottlenecks. However, its efficiency is often limited by the excessive traffic demands on either the mainline or the on-ramp. Meanwhile, unequal lane-setting, in which the number of mainline lanes is more than on-ramp, is a common infrastructure setup in urban expressway system. In this paper, a novel

Abstract The rapid advancements in sensor technologies has resulted in the increased use of Automatic Vehicle Location (AVL) systems for traffic data collection. Global Position System (GPS) sensors are the most commonly used AVL system, majorly because of it being a time-tested technology and being relatively cheap. Also, many of the transportation agencies have their vehicles equipped with GPS sensors

This study develops a feedback perimeter control strategy to maximize the throughput of an incident-affected network. The proposed perimeter control strategy is innovative in two aspects. First, the control variables, i.e., the inflow rates to the controlled subnetwork within the incident-affected network, are adjusted based on the online estimation of maximum network throughput that is updated dynamically

Most traditional metrics compare origin-destination (OD) matrices based on the deviations of individual OD flows and often neglect OD matrix structural information within their formulations. Limited metrics exist in literature for the structural comparison of OD matrices. One such metric is mean structural similarity index (MSSIM) that computes statistics on groups of OD pairs defined by local sliding

Traffic congestion induces significant economic loss each year, and identifying traffic congestion patterns is necessary for better traffic control and management. Floating car data (FCD) provides a cost-effective alternative for assessing traffic status and detecting congestion on a large scale. Recently, a new speed performance index (SPI) has been proposed to evaluate traffic status considering

Abstract Whereas the development of ADAS seeks to improve driver’s overall performance with a particular focus on traffic safety improvement; with it comes the requirement and opportunity to objectively evaluate the effectiveness of the technology in improving safety and overall road traffic efficiency. This study evaluates the effectiveness of ADAS in improving driver’s risk perception in near-crash

Road surface friction significantly impacts traffic safety and mobility. A precise road surface friction prediction model can help to alleviate the influence of inclement road conditions on traffic safety, Level of Service, traffic mobility, fuel efficiency, and sustained economic productivity. Laboratory-based methods were used in most previous studies related to road surface friction prediction model

Abstract The objective of this study is to model the complex behavior of non-lane based heterogeneous traffic which is predominantly occupied by vehicles with varying physical and dynamical characteristics and their staggered car following behavior. This study proposes a new continuum model by considering the properties of two-sided lateral gap in a non-lane based heterogeneous traffic stream. The

The objective of this study is to model the complex behavior of non-lane based heterogeneous traffic which is predominantly occupied by vehicles with varying physical and dynamical characteristics and their staggered car following behavior. This study proposes a new continuum model by considering the properties of two-sided lateral gap in a non-lane based heterogeneous traffic stream. The model is

Abstract Connected automation systems coordinate vehicle communications and automated vehicle control to improve transportation system mobility, safety, and sustainability. Real-world deployment of connected automated vehicle (CAV) applications and related traffic management technologies will require automation of all vehicle and traffic movements, including platooning, lane change, and merge maneuvers

Abstract In this paper, two new adaptive traffic signal control algorithms are proposed based on data from probe vehicles to realize the coordinated signal control of arterial roads. One is an iterative signal control algorithm, and the other is an optimized signal control algorithm. The proportion of vehicles in the nonstop group is selected as the indicator of the traffic state. The value for this

(2020). Special issue on dense surveillance systems for urban traffic. Journal of Intelligent Transportation Systems: Vol. 24, Dense Surveillance Systems for Urban Traffic, pp. 217-220.

Truck weight data is needed for a wide range of applications including but not limited to pavement design, weight enforcement, traffic monitoring, and freight transportation planning. Unfortunately, the low spatial resolution of weight sensors along the transportation network can limit these and other potential applications. The main contribution of this paper is a methodology to estimate gross vehicle

In a connected vehicle environment, vehicle location, speed, and other traffic information are readily available; hence, such environments provide new data sources for traffic signal control optimization. Existing adaptive signal control systems based on fixed detectors cannot directly obtain vehicle location and speed information, and thus, cannot provide accurate information about real-time traffic

In the past decades, Vehicular Ad hoc Networks (VANETs) have been increasingly developed. Providing secure and efficient communication is essential in VANETs. One of most important challenges in the secure and efficient communications is proposing an appropriate authentication scheme. In this paper, we suggest an efficient and novel authentication scheme for VANETs. In the proposed scheme, vehicles

This evaluation ascertained the operational impacts of the SUTRAC (Scalable Urban Traffic Control) Adaptive Signal Control Technology (ASCT) in an urban corridor consisting of 23 intersections in Pittsburgh, Pennsylvania. A combination of real-world GPS floating car runs and private sector probe data from INRIX was used to assess the impact of the ASCT. Data were collected with the ASCT active and

The rapid development of sensing, computing, and wireless communication techniques has given rise to an increasing number and increasing availability of high-resolution data that record real-time traffic information. In this study, radio frequency identification (RFID) data collected in Nanjing (a major city in southern China) were used to estimate dynamic travel demands and develop an RFID data-based

Short-term traffic speed forecasting is an important component of Intelligent Transportation Systems (ITS). Multi-step-ahead prediction can provide more information and predict the longer trend of traffic speed than single-step-ahead prediction. This paper presents a multi-step-ahead traffic speed prediction approach by improving the gradient boosting regression tree (GBRT). The traditional multiple

Reliable long-term travel time prediction would be effective support to traffic management, for example, traffic flow control or the pricing of tolls. Gradient boosting (GB) has been suggested as an excellent tool for short-term travel time prediction problems. This paper shows that GB with modifications can also work for long-term prediction. We introduce key variables, regarded as multiple factors

Traffic congestion has become a significant issue in urban road networks. There have been massive works about traffic signal optimization to improve the efficiency of traffic flow operation, and the so-called back-pressure control policy has proven to be excellent for oversaturated conditions. Most of the existing works with back-pressure are based on an adaptive phase sequence, and research with cyclic

Multi-view video surveillance is a highly valuable tool to ensure the safety of the crowd in large public space. By utilizing complementary information captured by multiple cameras, the issue of limited views and occlusion in single views can be addressed to gain better insight into the whole monitored space. However, multi-view surveillance has been widely applied to microscopic crowd analysis, for

We investigates the performance of deep Convolutional Neural Network (CNN) for recognizing highway traffic congestion state in surveillance camera images. Different from the usual images in ImageNet, images generated by highway surveillance cameras usually have much more extensive range of perspective and thus larger area of background. Therefore the objective road and vehicles are not as prominent

Self-driving cars are on the horizon, making it necessary to consider safety assurance and homologation of these autonomously operating vehicles. In this study, we systematically review literature that proposes new methods for these areas. The available methods were categorized into a novel taxonomy, dividing them into the strategies of combinatorial testing, robustness testing and search-based testing

Abstract User-related assessment of a level 3 automated driving system, providing functions such as lane- and distance-keeping, stop & go driving, lane change and overtaking, was carried out on a motorway in Germany with the aim to assess user-related issues of automated driving, i.e., behavior when driving with automation on motorways, user experiences, reactions and acceptance. Twenty-one persons

Classification of vehicles into distinct groups is critical for a number of applications including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The main goal of this paper is to demonstrate how data from Light Detection and Ranging (LiDAR) sensors could be leveraged to distinguish between specific types

Filtering of motorized two-wheelers (MTWs) is a common practice in dense urban heterogeneous traffic environments where they often tend to navigate through the available lateral spaces (commonly termed as ‘pore’ in the literature) described by the vehicles in-front. Considering the increased vulnerability of MTW riders in dense urban systems, proper evaluation and modeling of pore acceptance/rejection