Wilfred W. Recker

A model of complex travel behavior: Part I—Theoretical development

This paper presents a policy sensitive approach to modeling travel behavior based on activity pattern analysis. A theoretical model of complex travel behavior is formulated on a recognition of a wide range of interdependencies associated with an individuals travel decisions in a constrained environment. Travel is viewed as input to a more basic process involving activity decisions. A fundamental tenet of this approach is that travel decisions are driven by the collection of activities that form an agenda for participation; the utility of any specific travel decision can be determined only within the context of the entire agenda. Based on the theoretical model of complex travel behavior, an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns, and is presented in a companion paper (Recker et al, 1985).

ON OPTIMAL FREEWAY RAMP CONTROL POLICIES FOR CONGESTED TRAFFIC CORRIDORS

This paper examines the conditions for which ramp metering can be beneficial to the overall system in terms of travel time savings for a simple traffic corridor that consists of a freeway and a set of parallel arterials connected by entrance ramps. The focus is on analyzing state and control relationships to arrive at general analytical results regarding optimal metering policies, rather than on either developing specific control algorithms or solving a specific application. The analysis is concerned with the general behavior of the system under ramp control and traffic diversion. The analysis assumes that time-varying traffic demands that originate from various locations are destined for a single location and that the freeway is uniformly congested throughout the control period. Under these assumptions, some general results are obtained regarding the effectiveness of ramp metering for various traffic diversion propensities and differentials between freeway and arterial traffic conditions. It is shown that the optimal ramp control policies are determined by the magnitudes of two co-state vectors that depend on traffic conditions on the freeway and its alternative, and the drivers diversion propensity. The results of two limiting cases imply that when the freeway is uniformly congested ramp control is counter-productive unless diversion occurs, and where drivers have a high propensity to divert, the optimal policy is dependent on the travel speed on the freeway alternative and on the wave speed of backward propagating waves on the freeway.

A model of complex travel behavior: Part II—An operational model

Abstract Based on the theoretical model of complex travel behavior developed in a companion paper (Recker et al. , 1986), an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns. The system employs a simulation approach in combination with techniques of pattern recognition, multiobjective optimization and disaggregate choice models. Initial empirical verification of the system of models is presented based on results obtained from a sample data set.

An analysis of the severity and incident duration of truck-involved freeway accidents

Data associated with over 9000 accidents involving large trucks and combination vehicles during a two-year period on freeways in the greater Los Angeles area are analyzed relative to collision factors, accident severity, and incident duration and lane closures. Relationships between type of collision and accident characteristics are explored using log-linear models. The results point to significant differences in several immediate consequences of truck-related freeway accidents according to collision type. These differences are associated both with the severity of the accident, in terms of injuries and fatalities, as well as with the impact of the accident on system performance, in terms of incident duration and lane closures. Hit-object and broadside collisions were the most severe types in terms of fatalities and injuries, respectively, and single-vehicle accidents are relatively more severe than two-vehicle accidents. The durations of accident incidents were found to be log-normally distributed for homogeneous groups of truck accidents, categorized according to type of collision and, in some instances, severity. The longest durations are typically associated with overturns.

An analytical model of multihop connectivity of inter-vehicle communication systems

Taking advantage of the proliferation of wireless communication devices, we could well develop advanced transportation information systems based on inter-vehicle communication (IVC), in which drivers can have faster response to incidents and are able to communicate critical information in wake of disasters. Whether such IVC systems are feasible or not is highly related to the performance of multihop connectivity. Existing analytical studies of multihop connectivity, however, usually assume Poisson distribution of communication nodes or uniform distribution of vehicles on a road, and simulation-based studies are not suitable for real-time applications with computationally costly traffic simulators. In this paper, we present an analytical model for multihop connectivity of IVC in a traffic stream, in which positions of vehicles are all known through observations, traffic simulators, or traffic theories. After introducing most-forwarded-within-range communication chains and node- and hope-related events, we derive a recursive model of node and hop probabilities and further define a number of performance measures of multihop connectivity. We then apply the model to study multihop connectivity of IVC in both uniform and non-uniform traffic and obtain results consistent with those in literature. The new analytical model is efficient without repeating traffic simulations while capable of capturing the impact of arbitrary distribution patterns of vehicles. Thus it is suitable for evaluating connectivity of IVC for different traffic congestion patterns and extended for studies of other situations.

Some general results on the optimal ramp control problem

In an effort to relieve peak hour congestion on freeways, various ramp metering algorithms have been employed to regulate the inputs to freeways from entry ramps. In this paper, we consider a freeway system comprised of a freeway section and its entry/exit ramps, and formulate the ramp control problem as a dynamic optimal process to minimize the total time spent in this system. Within this framework, we are able to show when ramp metering is beneficial to the system in terms of total time savings, and when it is not, under the restriction that the controlled freeway has to serve all of its ramp demand, and the traffic flow process follows the rules prescribed by the LWR theory with a triangular flow-density relationship. We also provide solution techniques to the problem and present some preliminary numerical results and empirical validation.

A conflict model and interactive simulator (FASTCARS) for predicting enroute driver behavior in response to real-time traffic condition information

This paper proposes a theoretical methodology and practical data collection approach for modeling enroute driver behavioral choice under Advanced Traveler Information Systems (ATIS). The theoretical framework is based on conflict assessment and resolution theories popularized in psychology and applied to models of individual consumer behavior. It is posed that enroute assessment and adjustment is a reactionary process influenced by increased conflict arousal and motivation to change. When conflict rises to a level at which conflict exceeds a personal threshold of tolerance, drivers are likely to alter enroute behavior to alleviate conflict through either route diversion of goal revision. Assessment and response to conflict arousal directly relate to the drivers abilities to perceive and predict network conditions in conjunction with familiarity of network configurations and accessible alternate routes.Data collection is accomplished through FASTCARS (Freeway andArterialStreetTrafficConflictArousal andResolutionSimulator), in interactive microcomputer-based driving simulator. Limited real-world implementation of ATIS has made it difficult to study or predict individual driver reaction to these technologies. It is contended here that in-laboratory experimentation with interactive route choice simulators can substitute for the lack of real-world applications and provide an alternate approach to data collection and driver behavior analysis. This paper will explain how FASTCARS is useful for collecting data and testing theories of driver behavior.

Factors influencing destination choice for the urban grocery shopping trip

Destination choice for the urban grocery shopping trip is hypothesized to be determined by three factors: the individuals perception of the destination, the individuals accessibility to the destination and the relative number of opportunities to exercise any particular choice. Results of a multinomial logit model estimation support this hypothesis and provide useful information concerning the role of urban form in this destination choice situation. It is determined that accessibility is the primary aspect influencing destination choice and that its effect is nonlinear.

Travel/activity analysis: Pattern recognition, classification and interpretation

This paper presents a methodology for the analysis of travel/activity patterns based on a classification procedure in which the set of measurements that define human movement is represented by a pattern vector. Transformation techniques are then applied to the pattern vectors to develop a taxonomy for the pattern space. Subsequent inversion of the transformed patterns yields representative activity patterns that can be related to socioeconomic and urban form characteristics. Pattern recognition theory is demonstrated to be an effective means by which complex travel/activity patterns can be transformed into a structurally simpler space for purposes of planning and analysis.

A non-compensatory model of transportation behavior based on sequential consideration of attributes

The proposed model of travel choice behavior is based upon an assumption that individuals compare their choice alternatives on a series of attributes ordered in terms of importance; they eliminate from consideration those alternatives which do not meet their expectation on one or more of the characteristics. The process is repeated with adjusted levels of expectation until only one alternative remains. The model thus incorporates a number of psychological decision axioms which have seldom been applied in models aimed at providing transportation planners with useful information from consumer survey data. Estimates of parameters defining distributions of expectation levels in a population of travelers are generated using a nonlinear optimization technique. The technique is demonstrated to provide estimates which replicate well the choices of travelers in two different contexts: choice of hypothetical concepts of small urban vehicles and choice of destination for shopping trips within an urban area.