Probe vehicle data sampled by time or space: Consistent travel time allocation and estimation

A characteristic of low frequency probe vehicle data is that vehicles traverse multiple network components (e.g., links) between consecutive position samplings, creating challenges for (i) the allocation of the measured travel time to the traversed components, and (ii) the consistent estimation of component travel time distribution parameters. This paper shows that the solution to these problems depends on whether sampling is based on time (e.g., one report every minute) or space (e.g., one every 500 m). For the special case of segments with uniform space-mean speeds, explicit formulae are derived under both sampling principles for the likelihood of the measurements and the allocation of travel time. It is shown that time-based sampling is biased towards measurements where a disproportionally long time is spent on the last segment. Numerical experiments show that an incorrect likelihood formulation can lead to significantly biased parameter estimates depending on the shapes of the travel time distributions. The analysis reveals that the sampling protocol needs to be considered in travel time estimation using probe vehicle data.     

Short‐term travel time forecasts for transport information system in hong kong

In this paper, a case study is carried out in Hong Kong for demonstration of the Transport Information System (TIS) prototype. A traffic flow simulator (TFS) is presented to forecast the short‐term travel times that can be served as a predicted travel time database for the TIS in Hong Kong. In the TFS, a stochastic deviation coefficient is incorporated to simulate the minute‐by‐minute fluctuation of traffic flows within the peak hour period. The purposes of the case study are: 1) to show the applicability of the TFS for larger‐scale road network; and 2) to illustrate the short‐term forecasting of path travel times in practice. The results of the case study show that the TFS can be applied to real network effectively. The predicted travel times are compared with the observed travel times on the selected paths for an OD pair. The results show that the observed path travel times fall in the 90% confidence interval of the predicted path travel times.     

A hybrid scheme for real‐time prediction of bus trajectories

The uncertainty associated with public transport services can be partially counteracted by developing real‐time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real‐time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances. Copyright © 2017 John Wiley & Sons, Ltd.     

A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial‐a‐ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time‐dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time‐dependent travel time matrices. The branch‐and‐price approach is introduced for the time‐dependent DARP and tested by examining the sub‐network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade‐off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd.     

Nature of influence of out‐of‐vehicle time‐related attributes on transit attractiveness: a random parameters logit model analysis

This paper describes the nature of the impacts of walking distances and waiting time on transit use. The relative trade‐offs of walking and transfer components with other transit service attributes are also discussed. A total of 449 completed stated‐preference interviews were collected; with six observations from each respondent, the total number of observations was 2694. This data set was used to estimate the coefficients in different utility functions using a random parameters logit model. The results demonstrated that walking distances to and from transit stops have important and significant nonlinear negative influences on the attractiveness of transit. Transfer waiting time was also shown to have a significant nonlinear negative impact on transit attractiveness. The random parameters logit model had a better model fit than the standard logit model. Some of the findings obtained here are novel, while others are consistent with previous works. These findings have implications for both theory and practice. Copyright © 2014 John Wiley & Sons, Ltd.     

The impacts of household structure on the individual stochastic travel and out‐of‐home activity time budgets

The amount of time individuals and households spend in travelling and in out‐of‐door activities can be seen as a result of complex daily interactions between household members, influenced by opportunities and constraints, which vary from day to day. Extending the deterministic concept of travel time budget to a stochastic term and applying a stochastic frontier model to a dataset from the 2004 UK National Travel Survey, this study examines the hidden stochastic limit and the variations of the individual and household travel time and out‐of‐home activity duration—concepts associated with travel time budget. The results show that most individuals may not have reached the limit of their ability to travel and may still be able to spend further time in travel activities. The analysis of the model outcomes and distribution tests show that among a range of employment statuses, only full‐time workers' out‐of‐home time expenditure has reached its limit. Also observed is the effect of having children in the household: Children reduce the flexibility of hidden constraints of adult household members' out‐of‐home time, thus reducing their ability to be further engaged with out‐of‐home activities. Even when out‐of‐home trips are taken into account in the analysis, the model shows that the dependent children's in‐home responsibility reduces the ability of an individual to travel to and to be engaged with out‐of‐home activities. This study also suggests that, compared with the individual travel time spent, the individual out‐of‐home time expenditure may perform as a better budget indicator in drawing the constraints of individual space–time prisms. Copyright © 2013 John Wiley & Sons, Ltd.     

The congestion multiplier: Variations in motorists’ valuations of travel time with traffic conditions

The value of travel time savings in part depends upon the disutility of the travel time that is saved and partly on the use to which the time saved is put. It has long been recognised that the disutility of the time spent travelling also depends upon a wide range of factors such as the journey length or the effort, comfort and safety associated with travelling.Hence we might expect the value of motorists’ travel time to vary with the traffic conditions as represented by the degree of congestion, in part to reflect the more difficult driving environment when there are more vehicles, but also a higher sense of frustration, similar to that associated with waiting time and contributing to its premium valuation.In this context, and despite the predominance of car travel in developed countries, the empirical evidence specifically relating to car values of travel time tends to fail to distinguish between different types of time according to the degree of congestion. Thus we are often left unclear as to precisely what type of time has been valued. Moreover, when a distinction is made, it tends to be into a simple dichotomy of congested and uncongested traffic.This paper provides new evidence on the variation in the valuation of motorists’ travel time savings across a finer gradation of types of time than has been hitherto attempted. This is obtained from the same Stated Choice exercise conducted in the United Kingdom and the United States. The paper also provides an extensive account of previous research into how congestion impacts on motorists’ values of time.     

Microscopic modeling of large‐scale pedestrian–vehicle conflicts in the city of Madinah,Saudi Arabia

This paper presents a micro‐simulation modeling framework for evaluating pedestrian–vehicle conflicts in crowded crossing areas. The framework adopts a simulation approach that models vehicles and pedestrians at the microscopic level while satisfying two sets of constraints: (1) flow constraints and (2) non‐collision constraints. Pedestrians move across two‐directional cells as opposed to one‐dimensional lanes as in the case of vehicles; therefore, extra caution is considered when modeling the shared space between vehicles and pedestrians. The framework is used to assess large‐scale pedestrian–vehicle conflicts in a highly congested ring road in the City of Madinah that carries 20 000 vehicles/hour and crossed by 140 000 pedestrians/hour after a major congregational prayer. The quantitative and visual results of the simulation exhibits serious conflicts between pedestrians and vehicles, resulting in considerable delays for pedestrians crossing the road (9 minutes average delay) and slow traffic conditions (average speed <10 km/hour). The model is then used to evaluate the following three mitigating strategies: (1) pedestrian‐only phase; (2) grade separation; and (3) pedestrian mall. A matrix of operational measures of effectiveness for network‐wide performance (e.g., average travel time, average speed) and for pedestrian‐specific performance (e.g., mean speed, mean density, mean delay, mean moving time) is used to assess the effectiveness of the proposed strategies. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling and simulation of vehicle projection arrival–discharge process in adaptive traffic signal controls

Real‐time signal control operates as a function of the vehicular arrival and discharge process to satisfy a pre‐specified operational performance. This process is often predicted based on loop detectors placed upstream of the signal. In our newly developed signal control for diamond interchanges, a microscopic model is proposed to estimate traffic flows at the stop‐line. The model considers the traffic dynamics of vehicular detection, arrivals, and departures, by taking into account varying speeds, length of queues, and signal control. As the signal control is optimized over a rolling horizon that is divided into intervals, the vehicular detection for and projection into the corresponding horizon intervals are also modeled. The signal control algorithm is based on dynamic programming and the optimization of signal policy is performed using a certain performance measure involving delays, queue lengths, and queue storage ratios. The arrival–discharge model is embedded in the optimization algorithm and both are programmed into AIMSUN, a microscopic stochastic simulation program. AIMSUN is then used to simulate the traffic flow and implement the optimal signal control by accessing internal data including detected traffic demand and vehicle speeds. Sensitivity analysis is conducted to study the effect of selecting different optimization criteria on the signal control performance. It is concluded that the queue length and queue storage ratio are the most appropriate performance measures in real‐time signal control of interchanges. Copyright © 2010 John Wiley & Sons, Ltd.