published journal article
research report
working paper
The fundamental diagram is an important element in a variety of transportation studies. While various shapes of the fundamental diagram have been proposed and numerous debates on the best-fit fundamental diagram haven been made, why the fundamental diagram has many different shapes has not been well explained. This study introduces time gap as a key parameter to understand drivers’ behavioral differences at different locations and traffic conditions, then relate it to the shape of the fundamental diagram. From I-80 freeway event detector data, it is shown that time gap follows a certain probabilistic distribution and its mean value varies along locations. When downstream congestion is expected, drivers tend to take larger time gap than otherwise. It also turns out that divers take different time gaps for different travel speeds. Three different types of time gap-speed diagrams are identified and matched to Greenberg, reversed-lambda, and inverted-V types of fundamental diagrams, respectively.
published journal article
Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99–1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95–1.32), fine particulate matter with aerodynamic diameter <2.5 μm (HR, 1.20 per 10 μg/m3; 95% CI, 1.01–1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99–1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02–1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.
research report
This report summarizes research work conducted under TO4304 at the University of California, Irvine. Under this task order, the research team provided Caltrans with on-call direct support, technical guidance, and research related support. A series of Paramics plug-ins were developed and have been released to Caltrans. These plug-ins include actuated signal, multiple actuated signal timing plan, actuated signal coordination, detector data aggregator, ramp metering control, on-ramp queue override control, ALINEA ramp metering control, BOTTLENECK ramp metering control, SWARM Ramp metering control, and Freeway MOE. They complement the current Paramics simulation model and enhance its functionalities. This report describes how we developed these plug-ins and the step-by-step procedure to use them. It can be used as user manuals.
Phd Dissertation
The purpose of this study is to propose control theoretic approaches for high-occupancy toll (HOT) lanes operation. This dissertation considers different operation objectives, and provides pricing schemes for HOT lanes accordingly.To improve the system performance, the study first proposes a simultaneous estimation and control method for the same system as that in (Yin and Lou, 2009). An integral controller is applied to estimate the average value of time (VOT) of SOVs, and the dynamic prices are calculated based on the logit model. The closed-loop system is proved to be stable and guaranteed to converge to the optimal state both analytically and numerically. Two convergence patterns, Gaussian or exponential, are revealed. The effect of the scale parameter in the logit model is also examined.Then, a new lane choice model, i.e., the vehicle-based user equilibrium principle, is proposed to capture the lane choice of SOVs. A general lane choice model is derived based on the characteristics of the logit and the vehicle-based UE model. An insight regarding the dynamic price is obtained by analytically solving the optimal dynamic prices with constant demands of HOVs and SOVs, and then a feedback controller is designed to determine the dynamic prices without knowing SOVs’ lane choice models, but to satisfy the two control objectives: maximizing the flow-rate but not forming a queue on the HOT lanes. If the type of the lane choice model is given, the distribution of VOTs of the SOVs can be estimated.Next, an optimal control problem is proposed to examine the statement that revenue maximization should generally coincide with the optimization of freeway performances, such as maximizing overall travel-time savings or throughput. Results show that operators need to make different strategies based on the traffic demand. In order to maximize the revenue, operators should set a higher price to make the HOT lanes underutilized if the demand of HOVs is low. However, if the demand of HOVs is high, operators need to set a lower price to attract more SOVs to create congestion on the HOT lanes.It has long been known that drivers’ departure time choice behavior is one fundamental cause of congestion. In the last part of this dissertation, pricing schemes are proposed to consider both lane choice and departure time choice. In the study period, the demands for the HOT and GP lanes are higher than their capacities, which means the whole freeway is congested. However, the congestion period on the HOT lanes is short than that on the GP lanes. So, the HOT lanes are “underutilized”. It turns out that flat (instead of dynamic) pricing schemes are able to meet the following two constraints: (1) the total travel time and scheduling cost is minimized; and (2) the costs for each non-switching and switching SOV are the same. We show that different revenue and tolling constrains for certain type of vehicles lead to different pricing schemes.
published journal article
conference paper
Traffic operations field computational resources as well as the bandwidth of field communication links are often quite limited. Accordingly, for on-line implementation of Advanced Transportation Management and Information Systems (ATMIS) strategies, such as vehicle reidentification, there is strong interest in development of fieldâ??based techniques and models that can perform satisfactorily while minimizing field computational and communication requirements. A new vehicle reidentification algorithm (REID-2) developed previously by the authors (1) was oriented toward algorithm simplification, but also demonstrated the added benefits of improved performance and much broader potential applicability (to both round and square single inductive loops) compared with earlier methods. However, the basis of REID-2 is directly matching inductive vehicle signatures, which typically consist of 200~1,200 data points (stored as integers, and obtained from IST-222 detector cards) per signature. The purpose of this research was to investigate if a relatively simple data compression and transformation technique could be applied successfully to the raw inductive signatures for each vehicle, and then use the resulting transformed vehicle signatures as inputs to vehicle reidentification. A Piecewise Slope Rate (PSR) approach was used to compress and transform the raw vehicle signatures. The results of this investigation, including sensitivity analyses, vehicle reidentification performance, and the accuracy of section travel time measurement, are very promising and suggest that the reduction in both computational effort and computer memory needed to store individual signatures with this approach could potentially benefit both the field computational and communication requirements needed for real-time implementation of this modified vehicle reidentification technique.
working paper
A panel data set is analysed with the goal of identifying patterns of change in the use of various modes of transport. The data set, which represents a national sample of the Netherlands, is comprised of over 2000 individuals surveyed in three waves six months apart in 1984 and 1985. The data were processed in the form of categorical variables depicting use or non-use of each mode at each wave and were analysed using log-linear models. Results indicated that there were significant patterns of change for all of the modes studied. Some of these patterns were interpreted as representing seasonality, while others were interpreted as representing more fundamental adjustments in travel behavior.
conference paper