An estimation of total vehicle travel reduction in the case of telecommuting. Detailed analysis using an activity-based modeling approach

peer reviewedransportation Demand Management (TDM) is often referred to as a strategy adopted by transport planners with the goal to increase transport system efficiency. One of the possible measures that can be adopted in TDM is the implementation of telecommuting. A significant number of studies have been conducted in the past to evaluate the effect of telecommuting on peak-period trips. However it is less studied whether telecommuting also effectively and significantly reduces total vehicle travel. For this reason, a conventional modeling approach was adopted in this paper to calculate total kilometers of travel saved in the case telecommuting would materialize in the Flanders area. In a second part, the paper also introduces the use of an activity-based modeling approach to evaluate the effect of telecommuting. By doing so, an operational activity-based framework is externally validated by means of another completely different model, both calibrated for the same application and study area

Surveying activity-travel behavior in Flanders: Assessing the impact of the survey design

peer reviewedEver since car ownership and car use started to increase in Western Europe and the USA, transportation planners attempted to model people’s travel behavior. In the context of the Feathers project a dynamic activity-based travel demand framework is developed for Flanders. In this paper, the complete survey design of the data collection effort required for such dynamic activity-based model is discussed. A mixed survey design of using a PDA application on the one hand, and using traditional paper and pencil diaries on the other hand, turns out to be a very suitable way of collecting detailed information about planned and executed activity-travel behavior of households. The results show that no attrition effects are present, not on the number of out-of-home activities reported, nor on the number of trips reported. Moreover the survey mode (PDA versus paper and pencil) has no direct impact on the quantities investigated. Notwithstanding, it is essential for further analysis on the Feathers data to explicitly take into account mode effects because of two reasons. First, the effect of explanatory variables can be influenced by the survey mode. Second, the variance in the estimation of the quantity investigated can differ significantly. Heteroscedatisc linear regression models provide the required framework to explicitly take into account these mode effects

Uncertainty in forecasts of complex rule-based systems of travel demand: Comparative analysis of the Albatross/Feathers model system

peer reviewedThis paper documents the results of a comparative analysis of model uncertainty of the Albatross/Feathers model system for respectively the Rotterdam region, The Netherlands and Antwerp region, Belgium. The assessment concerned the calculation of the coefficient of variation for the daily distance travelled per person. The calculations are performed both at the aggregated level and the disaggregated level (e.g. disaggregation by certain socio-demographics). Results indicate that model uncertainty differs by socio-demographic groups. Results of a regression analysis also indicate that in both regions uncertainty in daily distance travelled per person is strongly correlated with the inverse square root of the relevant socio-demographic population and the complexity of the classification, measured in terms of the number of possible classes

Uncertainty in forecasts of complex rule-based systems of travel demand: Comparative analysis of the Albatross/Feathers model system

peer reviewedThis paper documents the results of a comparative analysis of model uncertainty of the Albatross/Feathers model system for respectively the Rotterdam region, The Netherlands and Antwerp region, Belgium. The assessment concerned the calculation of the coefficient of variation for the daily distance travelled per person. The calculations are performed both at the aggregated level and the disaggregated level (e.g. disaggregation by certain socio-demographics). Results indicate that model uncertainty differs by socio-demographic groups. Results of a regression analysis also indicate that in both regions uncertainty in daily distance travelled per person is strongly correlated with the inverse square root of the relevant socio-demographic population and the complexity of the classification, measured in terms of the number of possible classes

Agent-based Simulation Model for Long-term Carpooling: Effect of Activity Planning Constraints

AbstractIn order to commute by carpooling, individuals need to communicate, negotiate and coordinate, and in most cases adapt their daily schedule to enable cooperation. Through negotiation, agents (individuals) can reach complex agreements in an iterative way, which meets the criteria for the successful negotiation. The procedure of negotiation and trip execution in the long-term carpooling consists of a number of steps namely; (i) decision to carpool, (ii) exploration and communication, (iii) negotiation, (iv) coordination and schedule adaptation, (v) long term trip execution (carpooling), (vi) negotiation during carpooling and (vii) carpool termination and exploration for new carpool. This paper presents a conceptual design of an agent-based model (ABM) of a set of candidate carpoolers. A proof of concept implementation is presented. The proposed model is used for simulating the interactions between autonomous agents. The model enables communication to trigger the negotiation process; it measures the effect of pick-drop and shopping activities on the carpooling trips. Carpooling for commuting is simulated: we consider a set of two intermediate trips (home-to-work and work-to-home) for the long-term carpooling. Schedule adaptation during negotiation depends on personal preferences. Trip timing and duration are crucial factors. We carried out a validation study of our results with real data (partial) collected in Flanders, Belgium. Simulation results show the effect of constraining activities on the carpooling trips. The future research will mainly focus on enhancing the mechanisms for communication and negotiation between agents

Analysis of In-Vehicle Black Carbon Exposure and Trip Characteristics Using GPS Logs and Diaries

Poster SP-26 presented at ISEE 2012 Seattle, USA. Title: Analysis of In-vehicle Black Carbon Exposure and Trip Characteristics Using GPS Logs and Diaries Abstract: Background: Global Positioning Systems (GPS) are being used more frequently in health research. To limit respondent burden, and because of technical problems with the development of miniaturized air quality sensors; exposure is determined afterwards by linking GPS traces with air pollution models or nearby monitoring stations. In-vehicle exposure may however be not only related to yearly averaged outdoor concentrations. Objectives: To investigate whether the levels of in-vehicle Black Carbon (BC) concentrations are influenced by trip duration, hour of the day, traffic intensities, and spatial parameters like degree of urbanization or road type. Methods: Personal exposure measurements were done using µ-aethalometers, trip diaries and GPS devices. More than 1000 car-trips were evaluated in Flanders, Belgium. GPS coordinates were assigned to road segments to allow BC concentrations to be linked with trip and road characteristics. Results: Due to loss of signal, technical issues or participant’s error, 30% of all car trips had no GPS coordinates. If the distance between a GPS point and the closest road with known traffic intensities was larger than 30m, the observation was omitted (23% of all recorded coordinates). Average BC concentrations on highways are comparable to concentrations on urban roads (8.3 µg/m3), but almost double the concentrations on rural roads (4.7 µg/m3). BC concentrations are elevated at lower speeds (<30 km/h) and at speeds above 80 km/h. Driving on roads with low instantaneous traffic intensities resulted in lower exposures than driving on roads with higher traffic intensities. Concentrations on traffic peak hours are higher compared to off-peak hours. We found no evidence of a buildup of BC particles inside a vehicle; but there is a link between trip length and use of certain road types. Conclusions: We found evidence that BC concentrations in vehicles depend on speed, timing of the trip, degree of urbanization, and traffic intensities

Estimating Scalability Issues While Finding an Optimal Assignment for Carpooling

AbstractAn automatic service to match commuting trips has been designed. Candidate carpoolers register their personal profile and a set of periodically recurring trips. The Global CarPooling Matching Service (GCPMS) shall advise registered candidates on how to combine their commuting trips by carpooling. Planned periodic trips correspond to nodes in a graph; the edges are labeled with the probability for negotiation success while trying to merge planned trips by carpooling. The probability values are calculated by a learning mechanism using on one hand the registered person and trip characteristics and on the other hand the negotiation feedback. The GCPMS provides advice by maximizing the expected value for negotiation success. This paper describes possible ways to determine the optimal advice and estimates computational scalability using real data for Flanders

Analysis of the Co-routing Problem in Agent-based Carpooling Simulation

AbstractCarpooling can cut costs and help to solve congestion problems but does not seem to be popular. Behavioral models allow to study the incentives and inhibitors for carpooling and the aggregated effect on the transportation system. In activity based modeling used for travel forecasting, cooperation between actors is important both for schedule planning and revision. Carpooling requires cooperation while commuting which in turn involves co-scheduling and co-routing. The latter requires combinatorial optimization. Agent-based systems used for activity based modeling, contain large amounts of agents. The agent model requires helper algorithms that deliver high quality solutions to embedded optimisation problems using a small amount of resources. Those algorithms are invoked thousands of times during agent society evolution and schedule execution simulation. Solution quality shall be sufficient in order to guarantee realistic agent behavior. This paper focuses on the co-routing problem

INTEGRATING CONSOLIDATION OPTIONS IN A NEW CONCEPTUAL FREIGHT TRANSPORTATION FRAMEWORK

ABSTRACT In a growing globalised context and consumption economy freight transport is of crucial importance. Being able to understand the drivers of freight flows makes it possible to forecast freight flows in the future and to calculate the impact of different policies on freight traffic. This will put policymakers in the position to get a better insight in the way the transport of goods comes about. Still, freight demand modelling is lacking behind on the efforts made in passenger transport models. For this the development of a comprehensive and reliable freight transport model is essential. In this paper a conceptual freight transportation framework is proposed. Special attention is paid to the different consolidation options of a forwarder