conference paper
published journal article
Connected vehicles (CVs) and their supporting infrastructure are expected to play an important role in the management of traffic congestion. As highway expansion projects are becoming less common, deploying emerging technologies is essential to make the most of the current road infrastructure. Most published studies report that CVs improve traffic performance only marginally. Here, we propose that CVs drive cooperatively with cooperative adaptive cruise control (CACC)-enabled vehicles by designating a CACC lane for periods with high flows of slow-moving heavy-duty drayage trucks. To assess if this approach could help absorb year 2035 projected drayage traffic increases at the Ports of Los Angeles and Long Beach, which is the largest port complex in the U.S.A., we analyze three 2035 scenarios for I-710, a key freeway for freight transportation in Southern California: (1) CACC-enabled vehicles are deployed under mixed traffic conditions; (2) CACC-enabled vehicles are restricted to the first lane (left-most lane); (3) the first lane is reserved for CACC-enabled vehicles, and access is optional. Our results suggest that substantial speed improvements can be obtained, but only when the first lane is CACC reserved with optional access, because this approach creates more platooning opportunities and thus helps maximize the benefits of CACC.
conference paper
Traffic state estimation provides valuable information for travelers and decision makers. To implement an estimation method, one needs to predetermine the initial state and model parameters. This paper presents a new method to estimate model parameters and initial states for Newellâ??s simplified kinematic wave model based on heterogeneous data sources. Different from existing studies, the proposed method is a simultaneous framework which estimates both parameter and traffic state at the same step. The problem is formulated in a least square optimization framework which is solved using the Gauss-Newton method. The authors verified the estimation method using Next Generation Simulation (NGSIM) (USDOT, 2008) data and analyzed the impact of market penetration rate. The estimation result is consistent with observation.
published journal article
In recent empirical studies on values of time and reliability, many have suggested that travelers are interested not only in travel time saving but also in reduction in travel time variability. Variability introduces uncertainty for travelers such that they do not know exactly when they will arrive at their destination. Thus, it is considered as a risk (or an added cost) to a traveler making a trip. Continuing research is reported on route choice models and the effect on travel time reliability in an uncertain environment caused by demand and supply variations. The goal is to examine what the aggregate impact of changes in variability might be on network assignment and how travelers with different risk-taking behaviors respond to these changes.
published journal article
A current majority in some city, seeking to increase the probability that it will set policy in the following period, may initially adopt extremist policies that are particularly unattractive to the minority, leading some members of the minority to emigrate. This article develops a model to illustrate this idea, while providing examples that illustrate its relevance. (JEL H70, H41, D72)
conference paper
conference paper
This paper categorizes and solves a new class of problems called Real-Time Mass Transport Vehicle Routing Problems (MTVRP). The aim of these problems is to find a solution to optimally route vehicles in real time to pick up and deliver more passengers. This problem is described in the context of flexible large-scale mass transport options that use new technologies for communication among passengers and vehicles. The problem is very relevant to future transportation options involving large scale real-time routing of shared-ride fleet transit vehicles. However the global optimization of such a problem has not been studied in the past. Previous research by the authors (1) described MTVRP and proposed a three level hierarchical optimization process. The earlier work had shown the theoretical solutions for the first two levels giving globally optimal parameters. This paper implements the third step of the process, namely the Local Mass Transport Vehicle Routing Problem (LMTVRP) and demonstrates the efficacy of the scheme with simulation of LMTVRP scheme that uses globally optimal parameters. The paper also presents a classification of MTVRP among other Vehicle Routing Problems (VRPâ??s), and provides the simulation results from the application of MTVRP in a real urban network, namely, Barcelona, Spain.
published journal article
Intelligent transportation systems (ITS) hold great promise for public works professionals seeking to optimize those public investment strategies that deal with traffic congestion and other growth pressures. Advanced traffic and fleet management systems as well as traveler information and vehicle-based systems can take advantage of information technology advances and private market products to substantially improve the productivity, connectivity, and safety of transportation. And as the new federal transportation act further spurs deployment of these systems, ITS research programs will continue to play a vital role in supporting such deployment and the overall evolution of ITS. Such research includes developing technology tools, providing testing and evaluation environments, and helping advance the state of the practice.
published journal article
working paper
Probing a die-hard traffic congestion controversy, this paper scrutinizes two key variables, density and flow, under equilibrium versus optimal states. We find that optimization requires flow in equilibrium to decrease under mild congestion, but flow must increase under hyper-congestion. However, while under hyper-congestion flow should be increased by decreasing density, a mild congestion requires flow to be decreased by decreasing density. Thus, in flow of vehicles should always be discouraged to either increase or decrease flow of vehicles for economic efficiency. Moreover, even when optimal policy, given traffic demand, requires flow to increase, the optimal flow itself must decrease eventually as demand increases beyond a critical level.