Abstract

It is increasingly recognized that travel time reliability is important to travellers and goods, and hence there is an increasing demand to include reliability in the evaluation and appraisal of transport projects and programs, as a separate factor in its own right. A number of the policy options already in use as congestion mitigation policies have also positive impacts on the travel time reliability. It is therefore important to evaluate impacts of any remedial action separately both for average travel time (congestion) and for variability of that travel time (reliability). The impacts are generally assessed with an observational before/after study. As many things, independent from the system to be assessed, change between the periods before and after the installation of the system, observational before/after studies take also into account a reference site, where the effect of these changes is identified. In a previous paper Bhouri and Aron, (2013) presented the reliability impacts of a managed lane case consisting in a Dynamic Hard Shoulder Running (HSR) during rush hours on a French urban motorway. The study was conducted by comparing reliability indicators based on data collected in 2002 before the implementation of the system and in 2006 after this implementation. Jacques Chirac, former president of France, launched in 2003 an important campaign for road safety and against speeding. This modified the travel time distribution, differently according to the lane. As reliability is based on the percentiles (and not only on averages), it was necessary, in order not to confound the effect of this campaign with the HSR effect, to develop the observational before/after study method for determining that time effect by level of travel time: to do this, the before and after travel time distributions of the reference site are established, then their difference is analyzed as a function of the travel time, taking into account the percentiles. This method and the results are presented in this paper. Document type: Conference object

Abstract

TRB 2014 - 93rd Transportation Research Board Annual Meeting, WASHINGTON DC, ETATS-UNIS, 12-/01/2014 - 16/01/2014; The travel time variability may significantly influence the driver's route choice. Estimating travel time reliability is thus really appealing to urban infrastructure managers. This could provide better information to drivers, encourage their reassignment on the network, and optimize its use. In this paper, we study any arterial in under-saturated conditions with known fixed-time traffic signals. The kinematic wave model is chosen to simply represent traffic dynamics. A semi-analytical (grid-free) method is applied to determine the separation between vehicle groups at each signal of the arterial. The main contribution of this paper is to present an aggregated diagram that describes the functioning of this arterial. It graphically provides the direct assessment of vehicle travel times with respect to their departure and the traffic flow. This tool only depends on signal settings and is cyclic and invariant for fixed-time signals. We show how to use this diagram to generate probabilistic travel time distributions when some input parameters are uncertain. Furthermore, this diagram appears insightful when the traffic flow is not accurately known.

Abstract

Managed lanes operations refer to multiple strategies for recurring congestion control by increasing the road capacity or adapting its configuration to the demand level. As a result, the evaluation of their impacts usually focuses on congestion or safety-related indicators. However, with the growing prosperity, consumers demand higher quality transport services, for which reliable transport networks are central. This paper is focused on the travel time reliability assessment of a managed lane experience from a French motorway. The paper shows results from the field test experience of the hard shoulder dynamic use on the A4-A86 motorway in the east of Paris. Further to the reliability assessment, the paper focuses on the reliability indicators. It particularly shows the weakness of the skew of the distribution of travel time indicator.; La gestion dynamique des voies fait appel à de multiples stratégies pour maîtriser les congestions récurrentes, ce en accroissant la capacité de la route ou en adaptant sa configuration à la demande. Ces stratégies sont donc logiquement généralement évaluées en termes d'impacts sur la fluidité ou la sécurité du trafic, impacts mesurés par des indicateurs. Cependant, avec la prospérité croissante, les consommateurs demandent une amélioration de la qualité de service pour laquelle la fiabilité des réseaux de transport est centrale. Cette communication porte sur l'évaluation de la fiabilité des temps de parcours résultant d'une expérimentation de gestion dynamique des voies sur une autoroute en France - le tronc commun A4-A86, à l'est de Paris. La bande d'arrêt d'urgence y a été ouverte à la circulation à certaines périodes de la journée. Les résultats de cette expérimentation sont donnés ici ; à la lumière de ces résultats notamment, les indicateurs de fiabilité sont ensuite discutés. On montre en particulier la faiblesse de certains indicateurs fondés sur la largeur ou la dissymétrie de la distribution des temps de parcours. Document type: Conference object

Abstract

ISTS 2014 - 4th International Symposium of Transport Simulation, Ajaccio, FRANCE, 01-/06/2014 - 04/06/2014; Buses on the same route tend to bunch when the system is uncontrolled. This lack of regularity leads to an increase in the average passenger waiting time, increases delays and makes travel times uncertain. A wide variety of solutions have been proposed to maintain accurate bus system performance. Unfortunately, if a strategy is applied permanently, it could detract from the entire transport system efficiency. That is why a transit operator needs an accurate forecast of the route in order to intervene before the bus route is too disrupted to be restored to regularity. This paper aims to predict critical situations in real-time forecasting of a bus route state. To accomplish this, we propose to take advantage of both theoretical and empirical information (model and data) using data assimilation (a particle filter). On one hand, a stochastic dynamic bus model forecasts future bus route states. On the other hand, archived data calibrates the model parameters while real-time data provides information about the actual route state. The methodology is applied to a real case study thanks to the quality data provided by TriMet (the Portland, Oregon transit district). Predictions are finally evaluated by an a posteriori comparison with real data. The results highlight that the method leads to a valid forecast of a bus route state with a 8 minutes time window. This duration is sufficient to predict critical situations, especially bus bunching. Further research would have to consider deterministic travel times from a traffic model instead of the distributions in order to maintain correlation between travel times on links. In that case, the assimilation process would focus on the surrounding traffic flow, also potentially available in the Portland data.

Abstract

Increasing mobility and congestion results in an increase in travel time variability and in a decrease in reliability. Reliability becomes an important performance measure for transportation facilities. A variety of performance measures have been proposed to quantify it. Many of these indicators are based on percentiles of travel time. The knowledge of the distribution of travel time is needed to properly estimate these values. Congestion distorts the distribution and particular statistical distributions are needed. Different distributions have been proposed in the literature. In a previous paper, we presented a comparison of six statistical distributions used to model travel time. These six distributions are the Lognormal, Gamma, Burr (extended by Singh-Maddala), Weibull, a mixture of two Normal distributions and a mixture of two Gamma distributions. In this paper a probabilistic modeling of travel time which takes into account the levels-of-service is given. Levels of service are identified, then travel time distributions are modeled by level of service. This results in a very good fit between the empirical and modeled distributions Moreover, the adjustment was improved, thanks to the calibration of “Bureau of Public Roads” functions, linking the travel time to the traffic flow by level of service. The superiority of the Singh-Maddala distribution appears in many cases. This has been validated, thanks to travel time data from the same site at another period. However the parameters of the distributions vary from one year to another, due to changes in infrastructure. The transferability of the approach, not performed, will be based on travel time data on another site. Document type: Conference object