Jan-Dirk Schmöcker

Estimating Trip Generation of Elderly and Disabled People: Analysis of London Data

The aging of populations has implications for trip-making behavior and the demand for special transport services. The London Area Travel Survey 2001 is analyzed to establish the trip-making characteristics of elderly and disabled people. Ordinal probit models are fitted for all trips and for trips by four purposes (work, shopping, personal business, and recreational), with daily trip frequency as the latent variable. A log-linear model is used to analyze trip length. A distinction must be made between young disabled, younger elderly, and older elderly people. Retired people initially tend to make more trips, but as they become older and disabilities intervene, trip making tails off. Household structure, income, car ownership, possession of a drivers license, difficulty walking, and other disabilities are found to affect trip frequency and length to a greater or lesser extent.

Capacity Constrained Transit Assignment with Common Lines

This paper proposes the use of absorbing Markov chains to solve the capacity constrained transit network loading problem taking common lines into account. The approach handles congested transit networks, where some passengers will not be able to board because of the absence of sufficient space. The model also handles the common lines problem, where choice of route depends on frequency of arrivals. The mathematical formulation of the problem is presented together with a numerical example.

Attacker–defender models and road network vulnerability

The reliability of road networks depends directly on their vulnerability to disruptive incidents, ranging in severity from minor disruptions to terrorist attacks. This paper presents a game theoretic approach to the analysis of road network vulnerability. The approach posits predefined disruption, attack or failure scenarios and then considers how to use the road network so as to minimize the maximum expected loss in the event of one of these scenarios coming to fruition. A mixed route strategy is adopted, meaning that the use of the road network is determined by the worst scenario probabilities. This is equivalent to risk-averse route choice. A solution algorithm suitable for use with standard traffic assignment software is presented, thereby enabling the use of electronic road navigation networks. A variant of this algorithm suitable for risk-averse assignment is developed. A numerical example relating to the central London road network is presented. The results highlight points of vulnerability in the road network. Applications of this form of network vulnerability analysis together with improved solution methods are discussed.

A Game Theoretic Approach to the Determination of Hyperpaths in Transportation Networks

In transit assignment, the common lines problem leads to the notion of a hyperpath, which is a set of paths that when used according to the “take whichever attractive line arrives next” strategy minimises the expected travel time. Similarly, the game theoretic approach to risk-averse traffic assignment leads to the generation of a set of paths which minimises expected travel time when a pessimistic assumption is made about on-trip events. The equivalence between the hyperpath of transit assignment and the set of paths generated by a multi-agent, zero sum game is shown in this paper. In particular, game theory is used to show that the path split probabilities proposed by Spiess and Florian (1989) are optimal for the risk-averse traveller who needs to make an on-the-spot decision between alternative routes. An alternative two-agent (single demon), zero-sum game is considered. The results of the multiple- and two-agent games are compared on a small example network, showing that the single demon game can lead to denser hyperpaths.

Metro Service Delay Recovery: Comparison of Strategies and Constraints Across Systems

This study was conducted to identify the strategies used by operators to provide a high level of service. The research distinguishes between punctuality and regularity of service and proposes that metro passengers primarily value regularity. The focus of this research is not on incident prevention, but on strategies that can be implemented after an incident to restore service swiftly and to minimize delay. The research identifies the recovery strategies used by six metros and summarizes advantages and disadvantages of these strategies. The influence of the type of delay on the choice of strategy is described. Similarly, the impact of constraints such as line length, service frequency, and passenger crowding on the effectiveness of each strategy is also discussed. It was found that it was generally sufficient to distinguish minor incidents, slow-moving delays, and major incidents. A case study shows that those metros with higher inbuilt flexibility can return more easily to normal service. This finding will have implications for metro management. The research has been carried out by the Railway Technology Strategy Centre at Imperial College London in collaboration with the Community of Metros benchmarking group. The performances and service qualities of six metros (three European, two American, and one Asian) have been analyzed and compared. The study consists of a quantitative analysis of the performance of two lines from each metro, together with a more qualitative assessment of the strategies used to optimize performance, through structured interviews with key operational and managerial staff.

Mass effects and mobility decisions

Abstract This paper presents a review of the literature on mass effects and their importance in choice behavior, i.e. how individual behavior is influenced by the behavior of others, with the goal of extracting lessons for transportation policy. An overview of psychological theories explaining the process underlying mass effects and conformity behavior is given. This is followed by a presentation of evidence of mass effects on choice behavior both outside and within transportation planning, covering contexts ranging from long term choices such as residential location to short term decisions such as driving behavior. Based on this review, modeling approaches for studying mass effects and their data requirements are then synthesized, highlighting the advantages and limitations of each. The paper concludes with a discussion of the importance of leveraging the power of mass effects for designing transportation policies aimed at promoting sustainable and safe mobility, and of challenges for future work in this area.

Comparative Analysis of Proximal and Distal Determinants for the Acceptance of Coercive Charging Policies in the UK and Japan

ABSTRACT Coercive policies, such as road pricing or environmental taxation, are policies of an authority that charges or restricts its subjects in order to protect or restore common goods. Studies have shown it is important to understand the acceptability of such policies to the general public to guarantee long-term success. Our analysis, based on a limited survey of British and Japanese students, investigates well-established psychological factors that determine acceptability of road pricing directly or indirectly, such as perceived effectiveness, fairness, or problem awareness, as well as the role of a general trust in the government and a belief in “absolute values.”

Effects of Transit Real-Time Information Usage Strategies

Real-time information (RTI) is becoming increasingly available to transit travelers. This paper discusses the effects of RTI access available before the start of a journey in relation to line loads as well as passenger benefits. That RTI access can affect the choice of departure time and stop as well as the route choice is considered. Two types of travelers with access to RTI are distinguished: travelers who want to arrive at their destinations as soon as possible and passengers who prefer to stay slightly longer at their current locations if doing so can reduce their travel time. For illustration, a network with irregular service arrivals is used and the optimal strategy approach of Spiess and Florian is used as a benchmark for passengers without RTI access. As expected, results showed that travelers without RTI access travel longer but also that particular combinations of traveler strategy and RTI provision lead to counterintuitive effects. Results further illustrated that the two RTI access strategies that travelers use can lead to significant differences in loads. Implications for demand management are discussed.

Special Issue on Improving Network Reliability Through ITS Technologies

Network Reliability is an increasingly important topic in transportation planning and engineering. A recent trend in congested urban areas is to make infrastructure investments to achieve more reliable travel times that are resilient to minor or major disruptions. In achieving this, Intelligent Transportation Systems (ITS) plays a key role. Advanced traveller information systems for passengers and timely en-route information for car drivers are one of the best ways to avoid unnecessary delays. Effective data collection techniques are needed in order to understand and predict the network condition. Furthermore, effective network control strategies, including demand management measures such as road tolls and access control, will be needed. These are just some examples of opportunities where new ITS developments will be required to improve network reliability. The initial idea for this special issue originated at the 3rd International Symposium on Transportation Network Reliability (INSTR) held in Delft in July 2007. Compared to previous INSTR conferences, the number of papers discussing ITS issues had largely increased. Further, a large number of papers presented at the 14th ITS world congress in Beijing in October 2007 concerned network reliability issues. This special issue provides four articles that were selected following a general call for papers (and a rigorous review process), focusing on the topic of improving network reliability through innovative ITS technologies. The articles provide four different examples of areas where ITS technologies can be used to improve network reliability. The first two study the feasibility of using bus probes and taxi data, respectively, to improve estimates of inner-urban travel times. Taxi data become an increasingly popular source of real-time traffic data to provide the general public with travel time estimates. Bus data are an alternative source that provide potentially more regular information but are limited to specific routes. Inherent problems of bus data are thought to be uncertain dwell times at stops and lower traffic speeds than cars. The first article, by Uno and colleagues, describes an approach as to how these problems might be overcome. The focus of the second article, by Liu and colleagues, is on the reliability of taxi data to provide travel time information; in particular, how the reliability increases when digital rather than analog wireless technologies are used. Link travel times obtained by taxis might be used directly by the taxi dispatcher to optimize the fleet distribution as well as by traffic managers to better predict travel times for all road users. The third and fourth articles in this special issue illustrate that better information provision might influence travel behavior on a broader scale, for example, departure time choices in journey planning through a metropolitan area as well as route choice or even choices of using or avoiding particular junctions according to their reliability. The third article, by Higatani and colleagues, gives an example of how data collected on one of the technologically most advanced urban motorway system in the world, the Hanshin Expressway around Osaka, can be used to provide users with different measures of network reliability such as standard deviation in journey times that will help them better plan their journeys. The final article by Viti and van Zuylen studies the queue formation at junctions with fixed-time and vehicle actuated controls. A better understanding of this complex dynamic process will help improve control strategies that aim at minimising the variation of delays around junctions.

Demand adaptation towards new transport modes: the case of high-speed rail in Taiwan

This study aims to explain the factors affecting ridership changes on the relatively new Taiwan high-speed rail system (THSR). The analysis is based on monthly ridership data from January 2007 to December 2013. We also discuss the impact of THSR on competing modes such as air demand. Econometric time-series models are used for ridership estimation. First, a seasonal autoregressive integrated moving average model was applied; showing that the ridership thrives and that the trend prediction fairly well performed if applied to data after 2012. Second, to specify the impact of explanatory variables, a first-order moving average model was fitted. Results show that ridership, population and fuel price have a positive effect, while unemployment and car ownership tend to reduce the THSR ridership. We include as a separate factor ‘months since operation start’, showing that this factor is significant and discuss its relation to demand adaptation. Implications for general equilibrium modelling for new transport systems are discussed. Moreover, ridership data from two specific stations are used to test the importance of predominant trip purposes for demand estimation.