A G/G(n)/C/C state‐dependent simulation model for metro station corridor width design

Metro station corridor and passengers are described as a G/G(n)/C/C state‐dependent queuing system with a general random arrival interval G and a general random and state‐dependent service time G(n) to offset the shortcomings in existing design methods. The corresponding G/G(n)/C/C state‐dependent discrete event simulation model is developed, and its high‐fidelity is tested. Then the optimization algorithm based on the simulation model is designed to determine corridor width. The proposed simulation optimization method and the existing analytical optimization methods, based on M/G(n)/C/C and D/D/1/C queuing models, are applied to design corridor width in a numerical example of 48 combinations of passenger flow rates and level of service (LOS). The designed corridor widths are tested in a micro‐simulation model, and the performance measure is compared. The result shows that the corridor widths obtained by the new method are 0.357 m (7.4%) larger than that of the other two methods on average; the area per passenger of the new method increases 10.53% and 11.63%, respectively, compared with that of the other two methods; the widths designed by the new method satisfy the requirement of LOS under various passenger flows, whereas 93% of the corridor widths obtained by the other two methods fail to meet the requirement of LOS, and the corridor widths designed by the new method have high elasticity coefficients of LOS‐width. Copyright © 2015 John Wiley & Sons, Ltd.     

A planning methodology for intelligent urban transportation systems

Recent developments in intelligent transportation systems pose new challenges and opportunities for urban transportation planning. To meet these challenges and to exploit these opportunities, a framework for a new transportation planning methodology has been developed. The methodology operates in a computer environment, called PLANiTS (Planning and Analysis Integration for Intelligent Transportation Systems), designed to facilitate the entire planning process form problem identification, through idea generation and analysis, on to prioritization and programming. To assist in problem identification, PLANiTS provides graphic representation of current conditions, including traffic, air pollution, accidents, and projections of future conditions. A computerized knowledge base, containing information about possible strategies and their effects, and a model base, containing transportation and other analysis models, are used to guide the user in identifying potentially effective strategies and performing the appropriate analysis. To facilitate the use of these tools, PLANiTS provides computer support of group processes such as brainstorming, deliberation, and consensus seeking. PLANiTS is designed for use in urban transportation planning at the local, regional, and state levels; it is intended to support a variety of participants in the planning process including transportation professionals, decision makers in transportation agencies (often local elected officials), citizens, and interest groups. Recognizing that transportation planning is essentially a deliberative, political process, PLANiTS is designed to inform and facilitate, but not replace, the political decision-making process.     

Effect of traffic information on commuters' propensity to change route and departure time

Considerable public and private resources are devoted to the collection and dissemination of real-time traffic information in the Chicago area. Such information is intended to help individuals make more informed travel decisions, yet its effect on behavior remains largely unexplored. This study evaluates the effect of traffic information on travelers' route and departure time changes and provides a stronger basis for developing advanced information systems. Downtown Chicago automobile commuters were surveyed during the AM peak period. The results indicate that a majority of the respondents access, use and respond to information. For example, individuals use travel information to reduce their anxiety—even if they do not change travel decisions; this indicates that information may have “intrinsic” value. That is, simply knowing traffic conditions is valued by travelers. More than 60% of the respondents had used traffic information to modify their travel decisions. Multivariate analysis using the ordered probit model showed that individuals were more likely to use traffic reports for their route changes if they perceived traffic reports to be accurate and timely, and frequently listened to traffic reports. Respondents were more likely to change their departure times if they perceived traffic reports to be accurate and relevant, and frequently listened to traffic reports. The implication for Advanced Traveler Information Systems are that they may be designed to support both enroute and pre-trip decisions. ATIS performance, measured in terms of accuracy, relevance and timeliness would be critical in the success of such systems. Further, near-term prediction of traffic conditions on congested and unreliable routes (where conditions change rapidly) and incident durations is desirable.     

Effect of parking information on travelers' knowledge and behavior

In many urban centers the demand for parking increases sharply before Christmas mainly due to shopping activity — causing parking congestion. One way to ameliorate such congestion is by disseminating parking information. Informed drivers may divert to relatively under-utilized parking facilities relieving the pressure on congested facilities. The City of Nottingham in England tested a real-time parking information system designed to alleviate congestion in the City Center parking facilities. Real-time information was disseminated through the radio, while historical information regarding parking locations was disseminated through newspaper advertisements and leaflets. The objective of this study is to assess impacts of the parking information system on travelers' knowledge and decisions.Survey research was used to understand traveler response. Respondents' levels of knowledge regarding car parks were analyzed by developing Poisson regression models. Drivers were more likely to have greater knowledge of city center car parks if they used several information sources (radio broadcasts, newspaper advertisements or leaflets and word-of-mouth), were active seekers of parking information, and searched for parking rather than going directly to a parking facility. In addition, the study of behavior showed that drivers were more inclined to use the relatively under-utilized Park-and-Ride facilities instead of the city center car parks if they received parking information from Newspaper advertisements/leaflets. Overall, the parking information service in Nottingham was effective; it seems reasonable to establish such information dissemination and monitoring systems at parking facilities in other urban areas. Furthermore, to support informed travel and activity participation decisions, parking information should be integrated with traffic and transit information.     

Heterogeneous platoon flow dispersion model based on truncated mixed simplified phase‐type distribution of travel speed

Existing research on platoon dispersion models either describe homogeneous traffic flow feature, or are in lack of analytical solutions. By analyzing the field data, the truncated mixed simplified phase‐type distribution is proved to be capable of capturing the characteristics of heterogeneous traffic flow with an excellent fitting result. In light of this, we derive a generic heterogeneous platoon dispersion model with truncated mixed simplified phase‐type of speed in the forms of integrable functions. Numerical case studies are conducted to compare the performance of the proposed model and the conventional models (i.e., the Robertson model and truncated mixed Gaussian model). The results show that the proposed model not only better captures the platoon dispersion laws of heterogeneous traffic flow, but also presents higher computational efficiency, which provides practical implications on traffic signal control. Copyright © 2017 John Wiley & Sons, Ltd.     

Stated preferences for investigating commuters' diversion propensity

A reasonable response to increasing traffic congestion may come from the rapidly developing traveler information systems. Such systems may be successful if they effectively influence drivers' enroute decisions; in this regard, a critical factor may be commuters' willingness to divert from their regular route in response to information about traffic congestion. This study evaluates the effects of real-time traffic information along with driver attributes, roadway characteristics and situational factors on drivers' willingness to divert.The empirical portion of this study is based on a survey of downtown Chicago automobile commuters. The stated preference approach was used to study commuters' diversion propensity. Drivers expressed a higher willingness to divert if expected delays on their usual route increased, if the congestion was incident-induced as opposed to recurring, if delay information was received from radio traffic reports compared with observing congestion, and if trip direction was home-to-work rather than work-to-home. Respondents were less willing to divert if their alternate route was unfamiliar, unsafe or had several traffic stops. Socioeconomic characteristics were also significant in predicting willingness to divert.