New developments in transportation systems and the increasing complexities of urban living are creating challenges and opportunities to comprehensively address transportation problems. The key to exploiting new opportunities lies in understanding how travelers would respond to changes in the transportation system. This study aims to understand traveler behavior under normal and unexpected travel conditions in real-life situations. The results of a comprehensive behavioral survey conducted in Brussels are reported. Commuters' mode, departure time and route selection decisions, and the factors that influence them, including travel conditions, personal and household characteristics, and situational constraints, are explored. The paper develops a deeper understanding of automobile commuters' response to adverse weather. Automobile commuters constitute more than 50% of the total sample (N = 1218). They were asked about adverse weather impacts on their mode, route and departure time changes. Among those who changed their travel decisions in adverse weather (about 50%), more than one-quarter reported that adverse weather was either very important or important in changing their mode; and 60% changed their departure time due to adverse weather whereas 35% diverted to alternate routes. Furthermore, close to 75% kept themselves informed about weather through secondary information sources such as radio and television. To analyze relationships empirically, ordered probit models of mode and departure time were estimated. The models show that commuters change their travel patterns in systematic ways when adverse weather occurs. Finally, the implications of the survey results for dealing with adverse weather problems are discussed.

The impact of adverse weather conditions on the propensity to change travel decisions: A survey of Brussels commuters

In this paper, we present the results of an extended traveler behavior survey conducted in Geneva (Switzerland) in March 1994. In this survey, commuters were asked about the impact of various factors, related to individual or household characteristics and situational, contextual and environmental constraints on their basic travel decisions. In particular, the issues of mode, route and departure time choice were investigated, together with the diversion from normal patterns in response to adverse weather conditions. Some cross cultural comparisons are discussed with respect to the results of a similar survey conducted in Brussels (Belgium) in 1992 (Khattak & de Palma 1995, 1997).

Understanding individual travel decisions: results from a commuters survey in Geneva

Fuzzy Power Heronian function based CoCoSo method for the advantage prioritization of autonomous vehicles in real-time traffic management

System dynamics and feedback control problem formulations for real time dynamic traffic routing

In this paper, the Dynamic Traffic Routing problem is defined as the real-time point diversion of traffic during non-recurrent congestion. This dynamic traffic routing problem is then formulated as a feedback control problem that determines the time-dependent split parameters at the diversion point for routing the incoming traffic flow onto the alternate routes in order to achieve a user-equilibrium traffic pattern. Feedback linearization technique is used to solve this specific user-equilibrium formulation of the Dynamic Traffic Routing problem. The control input is the traffic split factor at the diversion point. By transforming the dynamics of the system into canonical form, a control law is obtained which cancels the nonlinearities of the system. Simulation results show that the performance of this controller on a test network is quite promising.

Solution to the user equilibrium dynamic traffic routing problem using feedback linearization

The development of a real-time traffic diversion control system for integrated freeway and arterial networks, as part of the most currently envisioned Intelligent Vehicle/Highway System (IVHS) is the topic of this paper. The objective of the traffic control system referred to as 'Smartnet' is to use real-time data to divert traffic from freeway to arterial networks so as to reduce congestion and improve drivers' travel time. The freeway network chosen for this work is the l-395 freeway corridor area in Northern Virginia, between the Capital Beltway and the District of Columbia. The arterials designated as alternative routes for diversion were primarily chosen to comply to network conditions and to conform with expected driver behavior in route selection. In addition, the route capacity, its associated ramps, and the normal flow volume were also considered in this selection process. The diversion strategies under this approach are based on the highway system performance. The aim is to optimize the system's performance as a whole.

A. G. Hobeika

Papers

A Real-Time Traffic Diversion Model: A Conceptual Approach