Development of a microscopic activity-based framework for analyzing the potential impacts of transportation control measures on vehicle emissions

Abstract

The 1990 Clean Air Act Amendments (CAAA) and the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) have defined a set of transportation control measures to counter the increase in the vehicle emissions and energy consumption due to increased travel. The value of these TCM strategies is unknown as there is limited data available to measure the travel effects of individual TCM strategies and the models are inadequate in forecasting changes in travel behavior resulting from these strategies. The work described in this paper begins to provide an operational methodology to overcome these difficulties so that the impacts of the policy mandates of both CAAA and ISTEA can be assessed. Although the framework, as currently developed, falls well short of actually forecasting changes in traveler behavior relative to policy options designed to encourage emissions reduction, the approach can be useful in estimating upper bounds of certain policy alternatives in reducing vehicle emissions. Subject to this important limitation, the potential of transportation policy options to alleviate vehicle emissions is examined in a comprehensive activity-based approach. Conclusions are drawn relative to the potential emissions savings that can be expected from efficient trip chaining behavior, ride-sharing among household members, as well as from technological advances in vehicle emissions control devices represented by replacing all of the vehicles in the fleet by vehicles conforming to present-day emissions technology.2

Activity-based Market Equilibrium for Capacitated Multimodal Transport Systems

“…Spatial-temporal constraints can be defined in terms of dual prices due to the linear programming structure, which provides a very powerful sensitivity analysis tool for analyzing spatial-temporal scenarios. For example, Recker and Parimi (1999) quantified the reductions in emissions due to households switching from no ride sharing behavior to ride sharing. Kang and Recker (2014) measured the effects of alternative fuel vehicle adoption under limited refueling infrastructure on households in Southern California using calibrated HAPP models.…”

A multi-day activity-based inventory routing model with space–time–needs constraints

“…Nevertheless, the ability to capture space-time constraints has many applications. Recker and Parimi (1999) quantified the costs of emissions by considering individuals' activity patterns. Using an ARP, they could evaluate the effects on emissions if households switch from no ride sharing behaviour to ride sharing.…”

A bridge between travel demand modeling and activity-based travel analysis

“…The solution patterns reveal personal travel behavior and activity participation within a 20 household context, while preserving the concept that the need for travel originates from participation in activities, that travel constitutes the linkage between activities, and in which all of the required components are contained in the activity scheduling problem. An application of the methodology in the estimation of the upper bounds of certain policy alternatives in reducing vehicle emissions can be found in Recker and Parimi (1999).…”

“…Experience using generic solvers for solution of a set of examples that in the realm of activity-based research have been perceived to be at least practically intractable, demonstrates that such frameworks are not prohibitively computationally intensive (Recker, 1995;Recker and Parimi, 1999;Recker et al 2000); and, undoubtedly, the application of algorithms specifically tailored to the model formulation would be substantially more efficient.…”