Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Induced traffic and economic appraisal

Economic appraisal of major roads in the UK is based on a set of standard procedures and conventions. A central assumption has been that the volume and pattern of traffic in any given year is independent of the quality of service offered by the network — the fixed trip matrix assumption. Failing to consider induced traffic can have serious consequences for the accuracy and robustness of the measured traffic benefits from road improvements. Assessment of the wider economic benefits of roads, which is an important political imperative for road investment, is also made more difficult. Two conclusions are reached. Variable trip matrix methods need to be introduced for the appraisal of major road schemes, and scheme appraisal needs to be complemented by a more strategic area-wide approach to evaluation. In responding to its advisory committee (SACTRA), the UK Department of Transport has accepted the first of these conclusions and is cautiously favourable to the second.     

Computational experience with an application of a simultaneous transportation equilibrium model to urban travel in Austin,Texas

Safwat and Magnanti (1988) have developed a combined trip generation, trip distribution, modal split, and traffic assignment model that can predict demand and performance levels on large-scale transportation networks simultaneously, i.e. a simultaneous transportation equilibrium model (STEM). The major objective of this paper is to assess the computational efficiency of the STEM approach when applied to an urban large-scale network, namely the urban transportation system of Austin, Texas. The Austin network consisted of 520 zones, 19,214 origin-destination (O-D) pairs, 7,096 links and 2,137 nodes. The Central Processing Unit (CPU) time on an IBM 4381 mainframe computer was 430 seconds for a typical iteration and about 4,734 seconds, less than 79 minutes, to arrive at a reasonably accurate solution in no more than 10 iterations. The computational time at any given iteration is comparable to that of the standard fixed demand traffic assignment procedure. These results encourage further applications of the STEM model to large urban areas.     

An equivalent optimization problem for combined multiclass distribution,assignment and modal split which obviates symmetry restrictions

This paper presents a model for combined multiclass trip distribution, trip assignment and modal split. Although this model is based on an equivalent optimization problem, it avoids the symmetry restrictions heretofore always associated with such approaches to multiclass trip assignment. This is accomplished by expressing Wardrop's first principle as a set of nonlinear constraints in standard mathematical programming form. An algorithm is proposed, each iteration of which requires solving a nonlinear program with linear constraints.     

Learning-based framework for transit assignment modeling under information provision

The modeling of service dynamics has been the focus of recent developments in the field of transit assignment modeling. The emerging focus on dynamic service modeling requires a corresponding shift in transit demand modeling to represent appropriately the dynamic behaviour of passengers and their responses to Intelligent Transportation Systems technologies. This paper presents the theoretical development of a departure time and transit path choice model based on the Markovian Decision Process. This model is the core of the MIcrosimulation Learning-based Approach to TRansit Assignment. Passengers, while traveling, move to different locations in the transit network at different points in time (e.g. at stop, on board), representing a stochastic process. This stochastic process is partly dependent on the transit service performance and partly controlled by the transit rider’s trip choices. This can be analyzed as a Markovian Decision Process, in which actions are rewarded and hence passengers’ optimal policies for maximizing the trip utility can be estimated. The proposed model is classified as a bounded rational model, with a constant utility term and a stochastic choice rule. The model is appropriate for modeling information provision since it distinguishes between individual’s experience with the service performance and information provided about system dynamics.     

Mode choice analysis with imprecise location information

Several large-scale person trip surveys include the information of the origin and destination of the trip only at the TAZ (traffic analysis zone) level, so the accuracy of location information is not enough to examine the effect of access and egress conditions on mode choice. Two approaches are applied in this study to complement the imprecise information; one for access to public transit from home, and the other for egress from public transit to destination. Home-based trip data with the destinations as university, governmental office, and hospitals are used in this study. About the information of the egress, the precise location of the destination are identified within TAZ from GIS database using the purpose of the trip and the type of the destination reported by the respondent, and the distance from the nearest train station and bus stop are calculated. About the access to the public transit form home, the distance from home to the public transit is treated as a probabilistic variable in estimating the mode choice model in this study. The model has the same structure as the latent class model. Census data which contain the population distribution within TAZ at city block level is used for the distribution of origin. The results of empirical analysis show that the proposed model has a better log-likelihood at convergence than those with TAZ centroids as the ends of the trip. The results suggest that the proposed model has the same effect as obtaining the precise location information, and that it enables to better represent mode choice behavior than using TAZ centroid. The results also suggest that imprecise location information provides smaller coefficient estimates for the effect of access and egress conditions, resulting the underestimate on the elasticity of the access and egress conditions for promoting public transit.     

Traffic assignment by trip type using volume restraint and link restraint for application in small urban areas

This research involved the development of a new traffic assignment model consisting of a set of procedures for an urbanized area with a population of 172,000. Historical, social, and economic data were used as input to conventional trip generation and trip distribution models to produce a trip table for network assignment. This fixed table was divided into three trip types: external-external trips, external-internal trips, and internal-internal trips. The methodology used to develop the new traffic assignment model assigned each of the trip types by varying the diversion of trips from the minimum path. External-external trips were assigned on a minimum path routing and external-internal trips were assigned with a slight diversion from the minimum path. Internal-internal trips were assigned with more diversion than external-internal trips and adjusted by utilizing iterative volume restraint and incremental link restraint. A statistical analysis indicated that assigning trips by trip types using trip diversion and volume and link restraint produces a significant improvement in the accuracy of the assigned traffic volumes.     

Long-term planning for ring-radial urban rail transit networks

Extensive work exists on regular rail network planning. However, few studies exist on the planning and design of ring-radial rail transit systems. With more ring transit lines being planned and built in Asia, Europe and the America's, a detailed study on ring transit lines is timely. An analytical model to find the optimal number of radial lines in a city for any demand distribution is first introduced. Secondly, passenger route choice for different rail networks is analyzed, for a many-to-many Origin-Destination (OD) demand distribution, based on a total travel time cost per passenger basis. The routes considered are: (1) radial lines only; (2) ring line only or radial lines and ring line combined; or (3) direct access to a destination without using the rail system. Mathematica and Matlab are used to code the route choice model. A cost-benefit optimization model to identify the feasibility and optimality of a ring line is proposed. Unlike simulations and agent-based models, this model is shown to be easily transferable to many ring-radial transit networks. The City of Calgary is used as an example to illustrate the applicability of each model. The existing urban rail network and trip distribution are major influencing factors in judging the feasibility and optimal location of the ring line. This study shows the potential net benefit of introducing a ring line by assessing changes in passengers’ costs. The changes in passenger cost parameters, such as ride cost and access cost, are shown to greatly influence the feasibility of a ring line.     

Optimal cordon pricing in a non-monocentric city

This paper examines the effect of cordon pricing based on an urban spatial model of a non-monocentric city where trips may occur between any pair of locations in the city. The model describes the spatial distribution of trip demand and traffic congestion under alternative pricing schemes. We evaluate the efficiency of resource allocation by comparing three schemes: no-toll equilibrium, first-best optimum, and optimal cordon pricing. Optimal cordon pricing is defined as a combination of cordon location and toll level that maximizes the social surplus in a city. Simulations show that cordon pricing is not always effective for congestion management: cordon pricing tends to be effective as the urban structure is more monocentric.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

Spatial allocation on a network with congestion

This article formalizes the land use design problem as a discrete-convex programming problem integrating within a quadratic assignment framework a realistic representation of transportation behavior (automobile congestion and variable demand for travel) as modelled by a combined trip distribution trip assignment model. Hill-climbing algorithms are proposed to solve the resulting optimization problem. Their performance is compared and evaluated on a set of test problems.     

The benefits of improving public transport: a myth or reality?

As part of a research project completed some four years ago at Imperial College, London, a number of case studies were undertaken to examine the impacts that major improvements to the public transport system have on parallel road traffic. The three studies of major improvements to the public transport systems in three U.K. and German cities were: the Victoria Line in London; the extension of the U‐Bahn system in West Berlin (at the time of the study); and the S‐Bahn extension in Stuttgart. Each scheme is reviewed, with particular reference to the degree in which they have relieved congestion on the roads in the same corridor. This was examined simply to see whether or not public transport improvements are the only answer to traffic congestion, as is sometimes suggested. In the event, every scheme was a unique example in itself. The different conditions in each situation are presented and the actual impacts of the schemes assessed, based on the available information. The findings were rather different from the expectations. Only marginal relief from road traffic was recorded, with a substantial shift from buses to the improved rapid rail system. In the case of Stuttgart, for example, traffic growth on parallel roads was actually higher than the average growth on all city roads, though for other reasons.     

An impact analysis of traffic image information system on driver travel choice

A driver is one of the main components in a transportation system that influences the effectiveness of any active demand management (ADM) strategies. As such, the understanding on driver behavior and their travel choice is crucial to ensure the successful implementation of ADM strategies in alleviating traffic congestion, especially in city centres. This study aims to investigate the impact of traffic information dissemination via traffic images on driver travel choice and decision. A relationship of driver travel choice with respect to their perceived congestion level is developed by an integrated framework of genetic algorithm–fuzzy logic, being a new attempt in driver behavior modeling. Results show that drivers consider changing their travel choice when the perceived congestion level is medium, in which changing departure time and diverting to alternative roads are two popular choices. If traffic congestion escalates further, drivers are likely to cancel their trip. Shifting to public transport system is the least likely choice for drivers in an auto-dependent city. These findings are important and useful to engineers as they are required to fully understand driver (user) sensitivity to traffic conditions so that relevant active travel demand management strategies could be implemented successfully. In addition, engineers could use the relationships established in this study to predict drivers’ response under various traffic conditions when carrying out modeling and impact studies.     

Activity–travel behaviour of non-workers from Bangalore City in India

This paper presents exploratory and statistical analyses of the activity–travel behaviour of non-workers in Bangalore city in India. The study summarises the socio-demographic characteristics as well as the activity–travel behaviour of non-workers using a primary activity–travel survey data collected by the authors. Where possible, the research also compares the analysis findings with the case studies on activity–travel behaviour of non-workers, carried out in developed and developing countries. This gives an opportunity to understand the differences/similarities in the activity–travel behaviour of non-workers across diverse socio-cultural settings. The preliminary exploratory analysis shed light on the differences in activity participation, trip chaining, time-of-day preference for trip departure, and mode use behaviour of non-workers in Bangalore city. Statistical models were developed for investigating the effects of individual and household socio-demographics, land use parameters, and travel context attributes on activity participation, trip chaining, time-of-day choice, and mode choice decisions of non-workers. A few important results of the analysis are the influence of viewing television at home on out-of-home activity participation and trip-chaining behaviour, and the impact of in-home maintenance activity duration on time-of-day choice. Further, based on the findings of the initial analyses, an attempt has been made in this study to develop an integrated model that links time allocation, time-of-day choice, and trip chaining behaviour of non-workers. The study also discusses the implications of the research findings for transportation planning and policy for Bangalore city.     

True Walking Distance to Transit

Abstract

People riding transit in the city of Detroit walk on average 0.8 miles (1.3 km) per round trip. The straight-line walking distance was found by buffering the bus stop locations and comparing them to the weighted US Census blocks. However, the true walking path follows the street pattern. Rather than undertaking network analysis, which would require connecting all addresses in the city with all bus stops, a Monte Carlo simulation was performed in geographic information system with random addresses. The simulation was performed over several addresses until convergence was achieved. The distances were converted to walking times and compared to the US National Household Transportation Survey.     

A branch-and-price approach for solving the train unit scheduling problem

We propose a branch-and-price approach for solving the integer multicommodity flow model for the network-level train unit scheduling problem (TUSP). Given a train operator’s fixed timetable and a fleet of train units of different types, the TUSP aims at determining an assignment plan such that each train trip in the timetable is appropriately covered by a single or coupled train units. The TUSP is challenging due to its complex nature. Our branch-and-price approach includes a branching system with multiple branching rules for satisfying real-world requirements that are difficult to realize by linear constraints, such as unit type coupling compatibility relations and locations banned for coupling/decoupling. The approach also benefits from an adaptive node selection method, a column inheritance strategy and a feature of estimated upper bounds with node reservation functions. The branch-and-price solver designed for TUSP is capable of handling instances of up to about 500 train trips. Computational experiments were conducted based on real-world problem instances from First ScotRail. The results are satisfied by rail practitioners and are generally competitive or better than the manual ones.     

Gender differentials in travel pattern – The case of a mid-sized city,Rajkot, India

This paper is at the conjunction of arguments for gender equity in transport services on one hand and need to move towards low carbon transport on the other in a developing country city. The case study city, Rajkot, a mid-sized Indian city with mixed land use and limited public transport at the time of this study, has short trip lengths and low trip rates. But, even in this city there is gender disparity in travel pattern. Thus, trip rates and trip lengths of women in the city in each of the income group are lower than that of their male counter parts. With the increase in income, both, the trip rates and lengths increase, but, the increase is higher for men than for women. While the large proportions of women in each income group walk, that among the lowest income group walking is the predominant mode, as they are ‘no-choice’ or ‘forced’ walkers. With the increase in household income, women tend to shift to para-transit and men to personal motorized transport. If sustainability arguments or climate policies are to target retaining the current low ecological footprint of the women as one of the strategies, it needs to cater to expansion of their mobility while improving infrastructure to support the same.     

Travel intensity in a city with a barrier

An analytical study is made of the determination of the travel intensity at an arbitrary point of a city with a straight line barrier. For a given origin and destination a trip is made by the shortest path not crossing the barrier or the city perimeter. The joint trip end distribution is arbitrary except for a continuity assumption.