Framework for designing sample travel surveys for transport demand modelling in cities

Transportation - Travel surveys in cities remain the main source of information for obtaining people’s trip characteristics and developing transport models that serve to predict the...     

The marine electronic highway in the Straits of Malacca and Singapore—an assessment of costs and key benefits

The Straits of Malacca and Singapore are an important trade route linking the Indian Ocean to the South China Sea and Pacific Ocean. They are also rich in resources and support a range of activities that benefit the economies of the littoral states (Indonesia, Malaysia and Singapore). This important shipping route is a very congested waterway and the authorities are keen to improve navigation facilities to promote ship safety and reduce the risk of groundings, collisions and accidents. This will also help to protect the marine environment from the effects of pollution and hence reduce its damaging impact on activities related to the Straits, e.g. fisheries and tourism. The Marine Electronic Highway (MEH) is an attempt to bring together maritime safety technologies and environmental management systems. The paper examines the costs of providing such a highway and considers some of the benefits which could accrue from its implementation. The analysis, conducted in the form of a cost-benefit study, clearly shows the economic viability of the scheme.     

Effects of information in road transport networks with recurrent congestion

This paper aims to gain more insight into the implications of information provision to drivers on the performance of road transport networks with recurrent congestion. For this purpose, a simulation program consisting of three components has been written. The first component is the traffic simulation model, the second component is the information provision mechanism, and the third component monitors the behavioural decision-making process of the drivers, which is modelled using a utility-based satisficing principle. Three types of information provision mechanisms will be considered: information based upon own-experience, after-trip information and real-time en route information. The findings in this paper, obtained in a hypothetical context, underline the important relationship betweenoverreaction, thelevel of market penetration and thequality of the information. High quality information allows a high level of market penetration, while low quality information, even when provided at low levels of market penetration, induces overreaction. Furthermore, real-time en route information is in particular beneficial during the process leading to a steady state; it reduces the variance in travel time considerably. The paper concludes with a discussion on the market potential of motorist information systems when commercially marketed.     

通过传感器信号分析进气门是否积炭

进气门积炭影响行驶性能和排放,能否通过观察发动机传感器的数据来判断进气门是否有积炭呢?     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

Analyzing fluctuations in car-following

Many car-following models predict a stable car-following behavior with a very small fluctuation around an equilibrium value g¹ of the net headway g with zero speed-difference Δv between the following and the lead vehicle. However, it is well-known and additionally demonstrated by data in this paper, that the fluctuations are much larger than these models predict. Typically, the fluctuation in speed difference is around ±2 m/s, while the fluctuation in the net time headway T = g/v can be as big as one or even two seconds, which is as large as the mean time headway itself. By analyzing data from loop detectors as well as data from vehicle trajectories, evidence is provided that this randomness is not due to driver heterogeneity, but can be attributed to an internal stochasticity of the driver itself. A final model-based analysis supports the hypothesis, that the preferred headway of the driver is the parameter that is not kept constant but fluctuates strongly, thus causing the even macroscopically observable randomness in traffic flow.     

Is generalised cost justified in travel demand analysis?

Transportation - Generalised cost (GC) has long been widely used as a measure of the attractiveness of travel alternatives. We argue that its limitations have been forgotten, overlooked or not...     

Review and meta-analysis of U.K. time elasticities of travel demand

In contrast with reviews of values of time and price elasticities, the literature contains little by way of detailed reviews of travel time based choice and demand elasticities. This paper reports the most extensive meta-analysis of time-based demand elasticities yet undertaken, supplemented with a review of literature not previously in the public domain. The meta-analysis is based upon 427 direct elasticities covering travel time, generalised journey time (GJT) and service headway and drawn from 69 UK studies. The elasticities are found to vary, as expected, across attributes, and quite strong effects have been detected according to distance. We provide interesting insights into the relationship between long and short run elasticities and elasticities obtained from static models and choice models based on actual and hypothetical preferences. Significantly, the results seem to indicate that the duration for the long run demand impact to work through depends upon the periodicity of the model estimated. There is little variation apparent by journey purpose, source of the evidence, nor over time or by region/flow type, whilst travel time elasticities for high speed rail are not materially different from conventional contexts. The findings support some official elasticity recommendations and conventions but challenge others, and can be used to provide time-based elasticities where none exist or to assess new empirical evidence.     

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman in J Transp Econ Policy 48(3):367–384, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions.