A utility-theory analysis of automobile speed under uncertainty of enforcement

Highway automobile speed and uncertain enforcement of the speed limit are introduced into a standard household utility model having time and income constraints. Due to uncertainty, expected utility is maximized to obtain the optimal speed (in excess of the speed limit). The optimal amounts of all other commodities and travel are also obtained. The key feature of the model is the risk attitude of the driver and the effect on optimal speed of such attitude. A related feature is the effect of risk attitude on the amount of speed self-insurance. An important finding is that the risk avert (seeking, neutral) driver charges himself an insurance premium that is larger than (smaller than, equal to) what is actuarially sufficient. The relationship between speed, risk attitude, and efficient cost of automobile travel is developed and implications are explored. A parametric analysis is conducted to establish the effect on optimal speed (and other variables) of changes in such policy instruments as the price of gasoline, the probability of being caught exceeding the speed limit, the unit speed fine, and the speed limit. Policy implications of the theoretical results are part of the conclusions.     

Non-linear utility functions in models of travel choice behavior

Models of individual choice behavior have been extensively developed and used in travel prediction during the last ten years. These models are generally formulated with utility functions that are linear in parameters. Theories of economics and psychology suggest that the true relationship between service variables and utility is non-linear. In this paper we demonstrate that non-linear transformations of time and cost variables produce statistically significant improvements in the model estimated, have a theoretically appealing interpretation, and lead to managerially important differences in policy evaluations. These results support the need to refine the specification of choice utility functions based on theoretical considerations and empirical research.     

Tackling traffic congestion in Accra,Ghana: A road user's perspective

A fast emerging component of the urban transportation problem in cities of the Third World is the problem of traffic congestion. Rapid increases in car ownership coupled with poor land use planning, inadequate road space, lack of regulated parking systems, uneducated use of the road by pedestrians, and bad driving behavior of motorists have all combined to produce congestions comparable to those experienced in cities in the advanced parts of the world. Traffic management measures have been tried in some of the major cities such as road expansion and redistribution of land uses in city centers, but most have produced minimal results. It is recommended in this paper that city authorities adopt an integrated approach to congestion with emphasis on influencing the behavior of the road users.     

Application of Inverse Models to Vehicle Optimization Problems

This paper presents a nonlinear inverse model of a road vehicle which simulates combined steering and braking/driving. The inputs to the model are the lateral and longitudinal acceleration of the vehicle's sprung mass center. The simulation returns the steering wheel angle and brake/drive torques required to obtain the desired accelerations. An example is presented which demonstrates the utility of inverse models for optimization purposes.     

Development of Vehicle-following Behavior for Automated Vehicle Systems

Automation of vehicular traffic in different forms has been considered by many people. It offers many advantages. Vehicular traffic dynamics for automated vehicle systems are developed here using calculus of variations and optimal control theory. Using such an optimization approach, the relationship of the traffic dynamics developed here and the traffic dynamics which have been used extensively before for non-automated systems is also shown. Such an approach considers multiple objective functions for the system.     

A model of stoppings on urban bus routes

The amount of time required to pick up and discharge passengers is an important issue in the planning and modeling of urban bus systems. Several past studies have employed models of this component of bus travel time which are based, in part, on a model of the number of stoppings the bus makes to pick up or discharge passengers. Most past versions of this model have assumed that expected demand does not vary from stop to stop or from trip to trip, but that the number of passengers demanding service at any given stop during any given trip follows a Poisson distribution. An alternative model is derived, based on the assumption that expected demand varies among stops and times of day but is fixed from day to day at any given stop and time of day. Boarding and alighting survey data are used to verify that the “average-demand” Poisson model consistently overestimates the number of stoppings and to calibrate an approximate version of the alternative model. A stop-spacing optimization model previously developed by Kikuchi and Vuchic is reevaluated using the alternative stopping model in place of the average demand model used in the original version. The results are found to be considerably different, thus indicating that transit route optimization models are sensitive to the way in which stopping processes are modeled.