Chenfeng Xiong | Villanova University (original) (raw)

Papers by Chenfeng Xiong

This paper presents a Bayesian approach for modeling and calibrating drivers' en route route chan... more This paper presents a Bayesian approach for modeling and calibrating drivers' en route route changing decision with behavior data collected from laboratory driving simulators and field Bluetooth detectors. The behavior models are not based on assumptions of perfect rationality. Instead, a novel descriptive approach based on naive Bayes' rules is proposed and demonstrated. The en route diversion model is first estimated with behavior data from a driving simulator. Subsequently, the model is recalibrated for Maryland, based on Bluetooth detector data, and applied to analyze two dynamic message sign scenarios on I-95 and I-895. This calibration method allows researchers and practitioners to transfer the en route diversion model to other regions based on local observations. Future research can integrate this en route diversion model with microscopic traffic simulators, dynamic traffic assignment models, and/or activity-based/agent-based travel demand models for various traffic operations and transportation planning applications.

Computer-Aided Civil and Infrastructure Engineering, 2014

This article adopts a family of surrogatebased optimization approaches to approximate the respons... more This article adopts a family of surrogatebased optimization approaches to approximate the response surface for the transportation simulation inputoutput mapping and search for the optimal toll charges in a transportation network. The computational effort can thus be significantly reduced for the expensive-toevaluate optimization problem. Meanwhile, the random noise that always occurs through simulations can be addressed by this family of approaches. Both one-stage and two-stage surrogate models are tested and compared. A suboptimal exploration strategy and a global exploration strategy are incorporated and validated. A simulationbased dynamic traffic assignment model DynusT (Dynamic Urban Systems in Transportation) is utilized to evaluate the system performance in response to different link-additive toll schemes implemented on a highway in a real road transportation network. With the objective of minimizing the network-wide average travel time, the simulation results show that implementing the optimal toll predicted by the surrogate model can benefit society in multiple ways. The travelers gain from the 2.5% reduction (0.45 minutes) of the average travel time.

Journal of Transportation Engineering, 2015

For determining highly disaggregate details about traffic dynamics, microscopic traffic simulatio... more For determining highly disaggregate details about traffic dynamics, microscopic traffic simulation 34 has long proven to be a valuable tool for the evaluation of development plans and operation/control 35 strategies. With recent advances in computing capabilities, research interest in large-scale 36 microscopic simulation has never been greater. This case study develops a 24-h large-scale 37 microscopic traffic simulation model for the Washington, DC, metropolitan area. The model 38 consists of over 7,000 links, 3,500 nodes, 400 signalized intersections, and over 40,000 origin-39 destination pairs. Various field measurements, such as time-dependent traffic counts and corridor 40 travel times, have been used for model calibration/validation. The EPA's Motor Vehicle Emission 41 Simulator is linked with the microscopic simulation model for the estimation of environmental 42 impacts. The calibrated model system has been used to comprehensively evaluate a newly built 43 toll road in Maryland, the Intercounty Connector. Various network-level and corridor-level 44 performance measures are quantified. The case study demonstrates the feasibility and capability 45 of large-scale microscopic simulation in transportation applications. It establishes an example for 46 modelers and practitioners who are interested in constructing a large-scale model system. The 47 developed 24-h simulation model system of traffic and emissions has the potential to serve as a 48 test bed for integration with other analysis tools, such as behavioral and optimization models.

The policy of flexible work schedule has been proposed for years in order to stimulate the redist... more The policy of flexible work schedule has been proposed for years in order to stimulate the redistribution of departure time among commuters. However, its potential influence on travelers' day-today traffic dynamics is infrequently seen in existing studies. This paper extends an agent-based positive departure time model to gain perspective on travelers' dynamic reaction towards the flexible work schedule policy. Unlike most rational behavior models, the positive model emphasizes the bounded rationality in people's actual behavior, and allows for heterogeneity among travelers. Dynamic traffic assignment (DTA) is integrated with this proposed model to build up the feedback loop between individual choice (demand side) and network performance (supply side). Scenarios of different percentages of population with flexible work schedule are analyzed. It is found that travelers with flexibility in work schedule tend to depart later to avoid peak periods in the morning. The average travel time in the network will decrease by at most 22%, when the policy of flexible work schedule is implemented.

Transportation Research Record: Journal of the Transportation Research Board, 2013

A novel positive model was developed for departure time choice under road pricing and uncertainty... more A novel positive model was developed for departure time choice under road pricing and uncertainty at individual levels, and the consequent system-level dynamic properties were also analyzed. The proposed modeling framework avoided assumptions of substantial rationality and focused on how individuals actually make decisions. Bayesian learning, knowledge updating, search, and decision making under uncertainty were modeled in the framework. Then time-dependent departure patterns along with other system performance were investigated in a series of agent-based simulation experiments. The way in which individuals actually chose departure time under various supply-and demand-side uncertainty scenarios was explored for the effect of the scenarios on system performance and its dynamic properties.

Transportmetrica B: Transport Dynamics, 2014

Measuring the transport network vulnerability has become an important research issue recently. Wi... more Measuring the transport network vulnerability has become an important research issue recently. With the increase on the road user's value of time, users are now not only concerned about taking the shortest route to save travel times, but also decrease the variances by choosing a route that is more reliable to arrive at the destination within acceptable time frame. Ensuring a reliable network and providing alternative options under network breakdowns are very important to reduce the network vulnerability. This paper proposed a computationally efficient approach to measure system-level network vulnerability through a game theory approach. The most vulnerable link is indicated by link failure probabilities and the overall vulnerability measure of the network is represented by the expected total travel time. The performances are compared and discussed through the numerical results from several reliability improvement strategies.

Journal of Urban Planning and Development, 2013

Application of microscopic traffic simulation beyond the corridor level analysis is not widely se... more Application of microscopic traffic simulation beyond the corridor level analysis is not widely seen in literature. This is partly because of the fact that a simulation model cannot capture behavior responses such as peak spreading. This study develops a framework that integrates agent-based travel behavior models with large-scale traffic simulation to capture the regional impacts of new development. The proposed model is then applied to the I-270/I-495/I-95 corridor in the north Washington, DC metropolitan area in a case study. Findings from this study reveal the potential of the proposed model to capture network dynamics and behavioral reactions. This framework also provides a valuable tool for the evaluation of new transportation infrastructure, such as the intercounty connector (ICC) corridor currently under construction, and its operation strategies.

Transportation Planning and Technology, 2013

ABSTRACT Many states in the USA have developed statewide travel demand models for transportation ... more ABSTRACT Many states in the USA have developed statewide travel demand models for transportation planning at the state level and along intercity corridors. Travel demand models at mega-region and provincial levels are also widely used in Europe and Asia. With modern transportation planning applications requiring enhanced model capabilities, many states are considering improving their four-step statewide demand models. This paper synthesizes representative statewide models developed with traditional four-step, advanced four-step, and integrated micro-simulation methods. The focus of this synthesis study is as much on model applications and data requirements as on modeling methods. An incremental model improvement approach toward advanced statewide models is recommended. Review findings also suggest model improvement activities should be justified by planning application needs. For statewide model improvement plans to be successful and financially sustainable, the return on model improvement investment needs to be demonstrated by timely applications that rely on improved model capabilities.

Journal of Transportation Engineering, 2014

This paper presents a departure time choice analysis, based on the notion of a latent carpooling ... more This paper presents a departure time choice analysis, based on the notion of a latent carpooling preference. The study is based on combined revealed preference and stated preference survey data collected on the Maryland side of the Capital Beltway (I-495). A conditional logit model is first estimated to identify drivers' choice of departure time when tolls and congestion management strategies, including high-occupancy vehicle (HOV) lanes and high-occupancy toll (HOT) lanes, are implemented. Then a latent class model accounting for heterogeneity across categories of drivers is proposed to examine difference in behavioral preferences across classes. The latent class model result reveals significant heterogeneity in drivers' latent preference toward ride-sharing, which can potentially support ranges of transportation policy and incentive design related to congestion management strategies such as HOV/HOT lane usage.

Transport Reviews, 2012

Since the passage of the Intermodal Surface Transportation Efficiency Act in 1991, a significant ... more Since the passage of the Intermodal Surface Transportation Efficiency Act in 1991, a significant number of state highway agencies have started to develop and implement statewide travel demand models to meet policy and legislative development needs. Currently, however, a lack of up-to-date multimodal and inter-regional passenger travel data hampers analysts' ability to conduct quantitative assessments of long-distance travel infrastructure investment needs, at both the national and statewide levels. Despite these data limitations, but also largely shaped by them, long-distance travel modelling has become an increasingly popular topic in recent years. This paper reviews several methodologies for multimodal inter-regional travel demand estimation, drawing examples from both state-specific modelling within the USA and from fully national models being developed and applied in other parts of the world, notably in Europe.

IET Intelligent Transport Systems, 2014

A significant portion of the observed variability in roadway performance can be due to the differ... more A significant portion of the observed variability in roadway performance can be due to the difference and innate heterogeneity in drivers' behaviour. Analytical models, stated preference data collection and studies, and laboratory-based simulator experiments are developed to understand the driver behaviour for years. However, little has been done to fill the important gap between the survey/laboratory observed behaviour and the field observed behaviour. This study investigates drivers' actual behaviour by conducting real-world field experiments in Beijing's roadway system. In the experiment platform developed, instrumented vehicles are employed for the advanced data collection and analysis in order to understand the impact of roadway category on drivers' longitudinal behaviour, i.e. car-following and car-approaching. These behaviour dimensions are identified in this study and quantified by parameters including relative speed, leading vehicle speed, accelerator release, braking activation, distance headway, time headway, and time-to-collision. The analysis suggests that the drivers' behaviour variation heavily depends on roadway characteristics, which supplements further theoretical and survey-based behavioural research. The research findings provide insight for theoretical advances, evaluating driving assistance systems (DAS), and roadway-specific incentive designs for traffic harmonization, speed reduction, collision warning/avoidance, safety enhancement, and energy consumption savings.