Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.     

A multiple discrete-continuous model for independent- and joint-discretionary-activity participation decisions

This paper presents a multiple discrete-continuous econometric structure to model the daily time-investment decisions of couples in solo- and joint-discretionary activities incorporating intra-personal and inter-personal inter-dependencies. The empirical model was estimated using data from the 2000 Bay Area Travel Survey. The results indicate evidence of the positive impact of vehicle availability on independent activity participation and the negative impacts of the presence of children and mandatory time investments on the joint discretionary-activity engagement of the spouses. In addition, we also find the mandatory- and maintenance-activity-participation characteristics of the spouse to influence the discretionary activity choices of individuals. Finally, the analysis also indicates a strong impact of common unobserved factors on the decisions of couples. From a policy analysis perspective, these results imply that demand-management actions directly impacting one adult could also result in changes to the activity patterns of his/her spouse and to changes in joint activity participation characteristics. Dr. Sivaramakrishnan Srinivasan is an Assistant Professor in the Department of Civil and Coastal Engineering at the University of Florida. His research interests include travel-behavior analysis, activity-based travel-demand modeling, and the application of advanced econometric methods for transportation problems. Dr. Chandra R. Bhat has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE).     

Modeling children’s school travel mode and parental escort decisions

Understanding of the activity-travel patterns of children is becoming increasingly important to various policy makers. Further, there is also a growing recognition that intra-household interactions need to be explicitly accommodated in travel models for realistic forecasts and policy evaluation. In the light of these issues, this paper contributes towards an overall understanding of the school-travel behavior of children and the related interdependencies among the travel patterns of parents and children. An econometric model is formulated to simultaneously determine the choice of mode and the escorting person for children’s travel to and from school. The 2000 San Francisco Bay Area Travel Survey (BATS) data are used in the model estimation process. Empirical results indicate that the characteristics of child like age, gender, and ethnicity, and employment and work flexibility characteristics of the parents have strong impacts on the mode choice decisions. In addition, the impacts of some of these attributes on the choice of mode to school are different from the corresponding impacts on the choice of mode from school. The distance between home and school is found to strongly and negatively impact the choice of walking to and from school, with the impact being stronger for walking to school. Several land-use and built-environment variables were explored, but were found not to be statistically significant predictors.

An exploratory analysis of joint-activity participation characteristics using the American time use survey

This paper presents a detailed exploratory analysis of joint activity participation characteristics using the American Time Use Survey (ATUS). As a very large nationwide survey that explicitly elicited information on both household and non-household companions for each activity episode, the ATUS is ideally suited for this analysis. Several intuitive and interesting results are obtained. Joint episodes are found to be of longer durations, significantly likely to take place at the residence of other people, and often confined to certain time periods of the weekday. In addition, important differences in these characteristics are also observed based on activity purpose, companion type, and the day of the week. These findings are intended to provide the basis for the justification of detailed collection of joint activity–travel participation information in household activity–travel surveys, and also as a stimulant for further empirical analysis and modeling of joint activity participation behavior.

Influence of turpentine addition in Jatropha biodiesel on CI engine performance,combustion and exhaust emissions

The prospect of using turpentine oil as an additive for Jatropha biodiesel and using it as an alternative fuel for diesel in CI engines has been experimented in this work. Tests were carried out in a single cylinder, air cooled, constant speed, direct injection diesel engine. The results display that the performance of Jatropha-Mineral Turpentine (JMT) and Jatropha- Wood Turpentine (JWT) blends were found close to diesel, emission features were enhanced and combustion parameters were noticed to be comparable with diesel. Brake thermal efficiency of JMT20 blend found closer to diesel at 75 % load. BSFC increases for JMT and JWT blends at part load and maintains at full load. CO, HC and Smoke emissions were reduced with JMT and JWT blends at 75 % load. NOx emissions were on the raise. Furthermore, JMT and JWT blends offered comparable performance and combustion parameters, reduced emissions and both can substitute standard diesel in CI engines.     

离岸浮力腿存储和再气化平台结构健康监测的试验研究（英文）

Offshore platforms are of high strategic importance, whose preventive maintenance is on top priority. Buoyant Leg Storage and Regasification Platforms(BLSRP) are special of its kind as they handle LNG storage and processing, which are highly hazardous. Implementation of structural health monitoring(SHM) to offshore platforms ensures safe operability and structural integrity.Prospective damages on the offshore platforms under rare events can be readily identified by deploying dense array of sensors. A novel scheme of deploying wireless sensor network is experimentally investigated on an offshore BLSRP, including postulated failure modes that arise from tether failure. Response of the scaled model under wave loads is acquired by both wired and wireless sensors to validate the proposed scheme. Proposed wireless sensor network is used to trigger alert monitoring to communicate the unwarranted response of the deck and buoyant legs under the postulated failure modes. SHM triggers the alert mechanisms on exceedance of the measured data with that of the preset threshold values; alert mechanisms used in the present study include email alert and message pop-up to the validated user accounts. Presented study is a prima facie of SHM application to offshore platforms, successfully demonstrated in lab scale.     

The relative importance of price and driving range on electric vehicle adoption: Los Angeles case study

Electric vehicles (EVs) are still a maturing technology. Barriers to their adoption include price and range anxiety. EV batteries are significant in determining both EV prices and costs. In this work, we focus on the impact of a high-capacity battery and EV rebates on an EV ecosystem. Using survey data from Los Angeles, California, we simulate different cases of battery costs and prices by means of an agent-based EV ecosystem model. We find that even in Los Angeles, a geographically spread out city, the price of EVs is a more significant barrier to adoption than EV range. In fact, even a quintupling of battery size at no additional costs improves EV adoption by only 5 %. Therefore, policy makers should focus more on affordability than range in promoting EV adoption.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

Structural Health Monitoring of Offshore Buoyant Leg Storage and Regasification Platform: Experimental Investigations

Offshore platforms are of high strategic importance, whose preventive maintenance is on top priority. Buoyant Leg Storage and Regasification Platforms (BLSRP) are special of its kind as they handle LNG storage and processing, which are highly hazardous. Implementation of structural health monitoring (SHM) to offshore platforms ensures safe operability and structural integrity. Prospective damages on the offshore platforms under rare events can be readily identified by deploying dense array of sensors. A novel scheme of deploying wireless sensor network is experimentally investigated on an offshore BLSRP, including postulated failure modes that arise from tether failure. Response of the scaled model under wave loads is acquired by both wired and wireless sensors to validate the proposed scheme. Proposed wireless sensor network is used to trigger alert monitoring to communicate the unwarranted response of the deck and buoyant legs under the postulated failure modes. SHM triggers the alert mechanisms on exceedance of the measured data with that of the preset threshold values; alert mechanisms used in the present study include email alert and message pop-up to the validated user accounts. Presented study is a prima facie of SHM application to offshore platforms, successfully demonstrated in lab scale.