Evaluating gravel transport sustainability: A case study of Taiwan’s northeast corridor

We use social-eco-efficient analysis in the form of SEEbalance to evaluate gravel transport sustainability for trucking and two kinds of intermodal transportation. Results show that switching from trucks to intermodal transportation can improve the sustainability of gravel transportation in the northeast corridor of Taiwan. Sensitivity analysis shows that rail combined with truck intermodal transportation has competitive advantage despite the terminal’s location factor.     

Modelling the provision of transport with planned or market‐determined public transport services

Implications of the difference between planned and market‐determined public transport services for the modelling of the transport system and its use are examined. In the former case, the task for government seeking to optimise performance of the transport system has a standard bi‐level form, but in the latter case, the lower‐level problem in the bi‐level formulation is to determine mutually consistent solutions to a pair of optimisation problems. The relevance of the mutually consistent solution in this context is contrasted with its sometimes misleading role in the context of optimisation of urban traffic signal control.     

Education of truck drivers using the assist driver support system ‐a pilot survey‐

We have developed a driver support system, ASSIST, to decrease automobile driving accidents. Most traffic accidents involve collisions of two objects. A collision occurs when a vehicle's headway is shorter than the stopping distance. Therefore, we plan to warn the driver when the vehicle's headway is shorter than the estimated stopping distance. This driver support system performs exactly that task. Results of experiments verify that this system increases that distance gap by warning the driver to increase the headway.     

The importance of new‐generation freight terminals for intermodal transport

Manufacturers have been promoting new terminal concepts for several years. They claim more efficient operations, shorter handling times and lower costs compared to conventional operations. However, so far no new‐generation terminals have been implemented, nor is there any intention yet to implement them. This is regrettable, because if new‐generation terminal concepts can achieve what their designers claim, these terminals could significantly improve the competitiveness of intermodal transport. It is expected that new‐generation terminals will perform particularly well in complex bundling networks such as hub and spoke, collection‐distribution and line networks. A static‐process analysis is used to evaluate the claimed terminal performances. The method incorporates the terminal function and the type of bundling network. Specific network situations have been defined for each type of bundling network. This study shows that the new concepts perform better than the reference terminal and shunting in complex bundling operations.     

Manual vs. adaptive cruise control – Can driver’s expectation be matched?

The role of the driver in the longitudinal car following control task will change from operator to supervisor with most of manual control replaced by automation as adaptive cruise control (ACC) technologies become commonplace. The extent to which manual control can be replaced by ACC will be determined by many factors. An important issue is the compatibility between ACC performance and the driver’s expectations.This paper describes the results of a simulation study of the performance of ACC relative to driver expectation. Driver’s expectation is quantitatively defined as the expected deceleration rate for several time-to-collision (TTC) levels, and an absolute minimum TTC that drivers tried to avoid in all cases. A two-level ACC algorithm was used to simulate the performance of an ACC equipped vehicle in various scenarios, and the result was compared to the driver’s expectations. The investigation has focused on scenarios which ACC is able to manage technically, but where driver expectations might be breached.By systematically changing variables such as the parameters of the ACC algorithms, traffic scenarios and time-headway settings, a large number of situations have been tested. The results have revealed that whilst appropriate ACC settings can be found which will meet the driver’s expectations, the ACC settings that are most capable in a range of traffic conditions are not necessarily the most user-friendly. A discussion on the implications of the findings is also presented.     

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.     

The multi‐actor,multi‐criteria analysis methodology (MAMCA) for the evaluation of transport projects: Theory and practice

In this paper the multi‐actor multi‐criteria analysis (MAMCA) method to evaluate transport projects is presented. This evaluation method specifically focuses on the inclusion of qualitative as well as quantitative criteria with their relative importance, defined by the multiple stakeholders, into one comprehensive evaluation process in order to facilitate the decision making process by the different stakeholders. The MAMCA methodology is introduced by an overview of other evaluation methods for transport projects in the past and is illustrated by means of two practical cases. The introduction will lead us to the theoretical conception of the MAMCA method where we draw the attention to the proven usefulness of the MAMCA for the evaluation of transport projects and the inclusion of different kinds of stakeholders, individuals as well as groups, into the evaluation process.     

A schedule‐based dynamic transit network model — Recent advances and prospective future research

Using the schedule‐based approach, in which scheduled timetables are used to describe the movement of vehicles, a dynamic transit assignment model is formulated. Passengers are assumed to travel on a path with minimum generalized cost that consists of four components: in‐vehicle time; waiting time; walking time; and a time penalty for each line change. A specially developed branch and bound algorithm is used to generate the time‐dependent minimum path. The assignment procedure is conducted over a period in which both passenger demand and train headway are varying. This paper presents an overview of the research that has been carried out by the authors to develop the schedule‐based transit assignment model, and offers perspectives for future research.     

Improved modeling of park‐and‐ride transfer time: Capturing the within‐day dynamics

An important factor that affects park‐and‐ride demand is transfer time. However, conventional park‐and‐ride demand models treat transfer time as a single value, without considering the time‐of‐day effect. Since early comers usually occupy spots closer to the entrance, their transfer times are shorter. Hence, there is a relationship between arrival time and transfer time. To analyze this relationship, a micro‐simulation model is developed. The model simulates the queuing system at the entrance and the pattern that parking spots are occupied in the parking lot over time. As expected, the model output illustrates an increasing relationship between arrival time and transfer time. This relationship has significant implication in mode choice models because it means that the attractiveness of park‐and‐ride depends on the time of arrival at the park‐and‐ride lot. This model of park‐and‐ride transfer time can potentially improve travel demand forecasting, as well as facilitate the operation and design of park‐and‐ride facilities.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.     

Macroscopic modeling of lane‐changing for two‐lane traffic flow

We propose a macroscopic model of lane‐changing that is consistent with car‐following behavior on a two‐lane highway. Using linear stability theory, we find that lane‐changing affects the stable region and the propagation speeds of the first‐order and second‐order waves. In analyzing a small disturbance, our model effectively reproduces certain non‐equilibrium traffic‐flow phenomena—small disturbance instability, stop‐and‐go waves, and local clusters that are affected by lane‐changing. The model also gives the flow‐density relationships in terms of the actual flow rate, the lane‐changing rate, and the difference between the potential flow rate (the flow rate that would have occurred without lane‐changing) and the actual flow rate. The relationships between the actual flow rate and traffic density and between the lane‐changing rate and traffic density follow a reverse‐lambda shape, which is largely consistent with observed traffic phenomena.     

X vs. Y: an analysis of intergenerational differences in transport mode use among young adults

Transportation - Recent research has contrasted the travel patterns of young adults of Generation Y (or, synonymously, the Millennial Generation) with the travel patterns of earlier generations of...     

Estimation of a time‐dependent origin‐destination matrix for congested highway networks

This paper presents a time‐dependent origin‐destination (O‐D) matrix estimation procedure embedded with a dynamic traffic assignment model, in which the predictive dynamic user optimal conditions in congested networks are maintained. Two solution algorithms are proposed, namely: an iterative (ITR) scheme and a method of successive averages (MSA) scheme. It is found that the MSA scheme outperforms the ITR scheme. As a prior O‐D matrix is an important input for the problem, its quality is essential for the reliability of the matrix estimation procedure. Empirical constraints are set in relation to the quality of the prior O‐D matrix for the estimation procedure. Numerical examples are used to demonstrate the effectiveness of the proposed methodology.     

Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world’s railways through NDEA analysis

This paper presents an approach to include both the unstorable feature of transportation service and the technological differences within railway companies in efficiency and effectiveness measurements. We explore efficiency and effectiveness for a group of 40 global railways in the year 2002, using traditional data development analysis (TDEA) and network data development analysis (NDEA). Comparing the results obtained from the NDEA model with those from the TDEA indicate that performance measures are quite different in terms of the magnitude, and even using different DEA type models to evaluate railway system performance does not distort the ranking of their performance. We also analyze the inter-related effects among three performance measures, finding that transportation service characteristics have positive effects on the evaluation of performance. Generally speaking, the NDEA model provides deeper insight regarding the sources of inefficiency and process-specific guidance to railway managers so as to help them improve their railway’s performance.     

Modelling rain effects on risk‐taking behaviours of multi‐user classes in road networks with uncertainty

This paper proposes a new travel time reliability‐based traffic assignment model to investigate the rain effects on risk‐taking behaviours of different road users in networks with day‐to‐day demand fluctuations and variations in travel time. A generalized link travel time function is used to capture the rain effects on vehicle travel times and road conditions. This function is further incorporated into daily demand variations to investigate those travel time variations arising from demand uncertainty and rain condition. In view of these rain effects, road users' perception errors on travel times and risk‐taking behaviours on path choices are incorporated in the proposed model with the use of a logit‐based stochastic user equilibrium framework. This new model is formulated as a variational inequality problem in terms of path flows. A numerical example is used to illustrate the application of the proposed model for assessment of the rain effects on road networks with uncertainty.     

Validation of a schedule‐based capacity restraint transit assignment model for a large‐scale network

This paper describes the application of a capacity restraint trip assignment algorithm to a real, large‐scale transit network and the validation of the results. Unlike the conventional frequency‐based approach, the network formulation of the proposed model is dynamic and schedule‐based. Transit vehicles are assumed to operate to a set of pre‐determined schedules. Passengers are assumed to select paths based on a generalized cost function including in‐vehicle and out‐of‐vehicle time and line change penalty. The time‐varying passenger demand is loaded onto the network by a time increment simulation method, which ensures that the capacity restraint of each vehicle during passenger boarding is strictly observed. The optimal‐path and path‐loading algorithms are applied iteratively by the method of successive averages until the network converges to the predictive dynamic user equilibrium. The Hong Kong Mass Transit Railway network is used to validate the model results. The potential applications of the model are also discussed.     

Evaluating critical lines and stations considering the impact of the consequence using transit assignment model ‐case study of London's underground network

As the problem of full transit vehicles is encountered daily by passengers in most of the big cities, previous research evaluated the consequence of overcrowding in terms of on‐board crowding and passengers not being able to board with full vehicles. The impact of overcrowding in the real world is, however, not necessarily proportional to these numbers. This paper attempts to specify the critical lines and stations of a network by considering the number of passengers failing to board and attempting to evaluate its impact on service quality and safety risks. The hypothesis is that larger stations with wider platforms can often cope better with overcrowding than smaller stations. Therefore a station size dependent satisfaction function is proposed, which takes values from 0 to 1. The method is applied to London's underground network with a number of scenarios which show critical stations in the network if delays occur.     

Development of a probabilistic model to optimize disseminated real‐time bus arrival information for pre‐trip passengers

In the advent of Advanced Traveler Information Systems (ATIS), the total wait time of passengers for buses may be reduced by disseminating real‐time bus arrival times for the next or series of buses to pre‐trip passengers through various media (e.g., internet, mobile phones, and personal digital assistants). A probabilistic model is desirable and developed in this study, while realistic distributions of bus and passenger arrivals are considered. The disseminated bus arrival time is optimized by minimizing the total wait time incurred by pre‐trip passengers, and its impact to the total wait time under both late and early bus arrival conditions is studied. Relations between the optimal disseminated bus arrival time and major model parameters, such as the mean and standard deviation of arrival times for buses and pre‐trip passengers, are investigated. Analytical results are presented based on Normal and Lognormal distributions of bus arrivals and Gumbel distribution of pre‐trip passenger arrivals at a designated stop. The developed methodology can be practically applied to any arrival distributions of buses and passengers.