A dynamic stochastic assignment model for the analysis of general networks

The paper adopts the framework employed by the existing dynamic assignment models, which analyse specific network forms, and develops a methodology for analysing general networks. Traffic conditions within a link are assumed to be homogeneous, and the time varying O-D travel times and traffic flow patterns are calculated using elementary relationships from traffic flow theory and link volume conservation equations. Each individual is assumed to select a departure time and a route by trading off the travel time and schedule delay associated with each alternative. A route is considered as reasonable if it includes only links which do not take the traveller back to the origin. The set of reasonable routes is not consistant but depends on the time that an individual decides to depart from his origin. Equilibrium distributions are derived from a Markovian model which describes the evolution of travel patterns from day to day. Numerical simulation experiments are conducted to analyse the impact of different work start time flexibilities on the time dependent travel patterns. The similarity between link flows and travel times obtained from static and dynamic stochastic assignment is investigated. It is shown that in congested networks the application of static assignment results in travel times which are lower than the ones predicted by dynamic assignment.     

Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study

The connected environment provides driving aids to help drivers making efficient and safe driving decisions. The literature to date is devoid of conclusive evidences of the connected environment’s impact on drivers’ mandatory lane-changing (MLC) behaviour. As such, the objective of this study is to examine MLC behaviour through a driving simulator experiment using the CARRS-Q Advanced Driving Simulator. Participants with diverse background performed the experiment in randomised driving conditions: baseline (without the driving aids), connected environment with perfect communication, and connected environment with communication delay. Repeated measure ANOVA in the form of linear mixed model and Generalized Estimation Equation (GEE) are employed to analyse various driving performance indicators during MLC event. We find that drivers in the connected environment tend to wait longer, increase the initial speed, and maintain a larger spacing, compared to when they are driving in the baseline condition. In addition, drivers in the connected environment are likely to reject fewer number of gaps and select relatively bigger gap sizes. Furthermore, post-encroachment time (PET) in the connected environment is higher across different gap sizes, indicating that the connected environment makes MLC safer. The GEE model on gap acceptance suggests that the perfect communication and communication delay has positive and negative impact on the accepted gap size, respectively, and the GEE model on lane-change duration indicates that lane-change duration tends to increase in the connected environment.     

Assessing driving pattern factors for the specific energy use of electric vehicles: A factor analysis approach from case study data of the Mitsubishi i–MiEV minicar

Battery electric vehicles (BEVs) promise to contribute to the achievement of a more sustainable transport system. In order to estimate energetic efficiency potentials while taking into account operating conditions, insights on the factors of energy use are required. The driving pattern, i.e. the characteristics of the driving profile, is expected to affect the vehicles’ energy use to a great extent. This paper investigates whether the driving pattern parameters that have proved to be relevant for the fuel consumption of ICVs also apply to BEVs. In consequence, we analyse correlations between driving pattern factors and the specific energy use of BEVs. In order to record driving and energy data, four commercially used battery electric minicars were equipped with tracking devices. The resulting dataset contains 42 vehicle months. The driving pattern is described in 45 parameters that are calculated for segments of the logged driving profiles. Exploratory factor analysis is applied to reduce the large number of parameters into a smaller number of independent factors. Six independent driving pattern factors are identified. Suitable correlation coefficients are calculated to check for dependencies with energy use. The most significant correlations were found for the intensity of acceleration/deceleration, as well as for the oscillation factor. Our results could be used to inform further studies where driving pattern factors for ICVs and BEVs are directly compared. Also, results can be used to develop specific driving school training programs to learn to drive BEVs in an energy efficient manner.     

A commuting model for the analysis of the impacts of a tramway project: application to the Lens area

Road congestion is not only an issue for major European urban agglomerations, but also for smaller ones. It is also the case of the Lens urban area, where car use is much higher than the average for medium-sized urban agglomerations in France. Local authorities put forward tramway projects to deal with the strongly negative externalities of congestion: travel time losses and pollution. To analyse its medium-term impact, we have developed a commuting with congestion model, inspired by the four-step traditional model, but with data made available from an origin–destination matrix. The results are encouraging but insufficient, and it is necessary to adopt supplementary measures in order to retrieve and justify the sizeable investments needed. Some measures prove to be very efficient, such as parking fees and urban tolls. Other measures, such as the subsidization of public transport, are partially efficient since they have an impact mainly on intra-urban commutes.     

Variability in urban driving patterns

Although it is known that driving patterns strongly affect the emission of pollutants from vehicles, existing empirical knowledge about driving patterns is limited. The first-step in this project was to find relevant parameters for describing driving patterns. These served as a basis for investigating variations in such patterns. An experimental study was carried out to compare driving patterns between and within different street-types, drivers and traffic conditions. Data were analysed using general factorial analysis of variance. Driving patterns showed very significant differences between street type and driver, and these factors had significant impact on all the parameters employed. The effect of street type was generally higher than the driver effect. Average speed and deceleration levels were lower at peak hours compared to off-peak hours. Men had higher acceleration levels than women generally and specially on one street type. The study showed no major differences in average speed for gender except for one street type where men drove faster than women. The knowledge attained in this study may be a step towards a better knowledge of driving patterns and their variation, and may provide possibilities of changing driving patterns and thus exhaust emissions from vehicles. Knowledge about driving patterns is also an essential part in efforts to improve models to calculate emission from traffic in urban environment.     

Are multi-car households better suited for battery electric vehicles? – Driving patterns and economics in Sweden and Germany

Battery electric vehicles (BEVs) could reduce CO₂ emissions from the transport sector but their limited electric driving range diminishes their utility to users. The effect of the limited driving range can be reduced in multi-car households where users could choose between a BEV and a conventional car for long-distance travel. However, to what extent the driving patterns of different cars in a multi-car household’s suit the characteristics of a BEV needs further analysis. In this paper we analyse the probability of daily driving above a fixed threshold for conventional cars in current Swedish and German car driving data. We find second cars in multi-car households to require less adaptation and to be better suited for BEV adoption compared to first cars in multi-car households as well as to cars in single-car households. Specifically, the share of second cars that could fulfil all their driving is 20 percentage points higher compared to first cars and cars from single-car households. This result is stable against variation of driving range and of the tolerated number of days requiring adaptation. Furthermore, the range needed to cover all driving needs for about 70% of the vehicles is only 220 km for second cars compared to 390 km for the average car. We can further confirm that second cars have higher market viability from a total cost of ownership perspective. Here, the second cars achieve a 10 percentage points higher market share compared to first cars, and to cars in single-car households for Swedish economic conditions, while for Germany the corresponding figure is 2 percentage points. Our results are important for understanding the market viability of current and near-future BEVs.     

Is the provision of park-and-ride facilities at light rail stations an effective approach to reducing vehicle kilometers traveled in a US context?

Park-and-Ride (PNR) facilities are a commonly used means of making a transit system more widely available. However, given that a PNR passenger must drive for part of the trip, this approach to transit provision has an ambiguous influence on vehicle kilometers traveled (VKT). The impact of PNR on VKT is highly dependent of how PNR users would choose to travel if the PNR facilities were not available. Given that this issue has received little attention in a US context, we use the light rail system in Charlotte, North Carolina as a case study to examine the potential impact of PNR removal on VKT. Using a travel survey of PNR passengers, we estimate the VKT currently generated while driving to and from the rail stations and then estimate how VKT would change under various PNR removal scenarios that assume different behavioral responses. We find that, under the most realistic scenarios, PNR removal would lead the average PNR passenger to increase her driving by 8–15 VKT per round trip.     

The effects of an acceleration advisory tool in vehicles for reduced fuel consumption and emissions

This study evaluates whether the use of an acceleration advisor leads to fuel savings, to determine the change in traffic-related emissions and to analyse changes in driving patterns on various routes. The acceleration advisor provides advice to drivers through resistance in the accelerator pedal when they try to accelerate rapidly. In a test carried out in Southern Sweden, the acceleration advisor was installed in four postal delivery vehicles. The driving pattern parameters show that strong acceleration was significantly reduced, which indicated that the drivers had complied with the advisor. On two of the three routes, the acceleration advisor had a positive effect on emissions. In general, no significant reduction in fuel consumption was observed when driving with the acceleration advisor activated.     

Theory of jam-absorption driving

“Can a single car really absorb a traffic jam without making new jams?” In this paper, we focus on this frequently-discussed question, and have succeeded in making a theoretical framework of a driving technique how to absorb a traffic jam by using a minimal microscopic model. Jam-absorption driving comes from Beaty (Beaty, 1998, Beaty, 2013), and it is composed of a sequence of two actions termed the “slow-in” and “fast-out”. The “slow-in” is the action to avoid being captured by a jam and remove it by decelerating and taking a longer headway in advance. The “fast-out” is performed after the “slow-in”, and it is the action to follow the car in front without unnecessary time gaps by accelerating quickly. In our theoretical framework, we have represented the recipe of the actions such as the time–space points and the velocity. Moreover, we have clarified the condition of no secondary jams due to this driving, i.e., the condition that compression and expansion waves caused by this driving meet each other and disappear. Particularly, we have calculated how these waves propagates to the following cars and the point where and when they disappear. Besides, we have analyzed how this point moves in time–space diagrams by varying the timing to start the jam-absorption, and revealed that the pattern of this movement is not constant but changes greatly by the velocity-headway relationships. Furthermore, as a more realistic problem, we have formulated the driving for jam-absorption in two steps of deceleration, which brings rich patterns of collisions among compression and expansion waves.     

Traffic accident risk perception among drivers: a latent variable approach

ABSTRACT

Governments require decision tools to deal with road traffic accidents, a pandemic resulting in millions of deaths around the world. Evidence shows that human factors are one of the major causes of road accidents, and there is much interest in identifying variables that may have an impact on drivers’ perception of risk. To this aim, we design a stated choice experiment with eight hypothetical driving scenarios considering attributes that have been strongly associated with increased accident risks: (i) driving speed, (ii) driving the wrong way in a one-way street, (iii) overtaking on a bend, and (iv) driving under the influence of alcohol or drugs. Data from a sample of survey respondents are used to estimate a hybrid discrete choice model incorporating two latent variables, Driver Concentration and Safe Driving. Our results may contribute to the design of public policies geared to prevent accidents by encouraging safer driving behaviour.     

A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles

This paper describes the methodology we set up to gather appropriate data to study the impact of real life experience with electric vehicles (EVs) over a relatively long period of time on individual preferences and attitudes. We used stated choices (SC) to elicit individual preferences because EVs and their associated charging infrastructure are not yet fully integrated onto the market. Furthermore, to measure the extent to which the experience of using an EV may affect individual preferences and attitudes, we set up a “long panel” survey, where data was gathered before and after individuals experienced an EV in real life during a three-month period. We also measured attitudinal effects (AE) that might affect the choice of an EV by individuals. To our knowledge, this represents the first example of a “long panel” SC/AE and the first attempt to measure the formation of preferences and attitudes for this emerging product. Our results show that preferences and attitudes are indeed affected by real life experience. In the SC experiment, the respondents only chose the EV half as often as compared to the situation where they had not yet tried it. Furthermore, we measured a change in attitude for statements regarding the use of EVs. On the whole, respondents got a more positive view of the EV driving performance and this change is significantly greater for women than for men. However, respondents expressed more concern about being able to maintain current mobility with an EV. The data gathered in this survey should also serve to analyse the changes generated by direct experience with EVs, and eventually to formulate and estimate advanced discrete choice models that allow insights into factors relevant for improved understanding of market behaviour.     

Formal characterization of an efficient driving evaluation process for companies of the transport sector

Public institutions and private companies all around the world agree that road transport is one of the main sectors responsible for global warming. With this in mind, all of them have designed actions to increase efficiency and reduce fuel consumption and emissions. A favorite for the companies is eco-driving because it can improve the fleet performance without a great investment. However, although these programs have achieved promising results in the majority of the experiences, the figures are not so encouraging in the long term. In many cases this decrease is produced by fuzzy reward programs or the total lack of them. Nevertheless, any coherent reward program, in order to be effective, must be associated with a complete and fair evaluation process which takes into account all the different aspects and complexities related with driving. In this paper, we propose a formal characterization of an efficient driving evaluation process which starts with a review of many different driving recommendation systems. These recommendations are used as seeds to build a set of formal competences that any eco driver must have, as well as the learning outcomes associated with each competence. A set of patterns of driving behaviors are defined, that allow confirming any of the learning outcomes. The definition also comprises a set of Key Performance Indicators (KPIs) for each learning outcome. These KPIs allow measuring the progress associated with each competence. Finally, we also propose some relevant differences that must be taken into account for the goals associated with each KPI, depending on the domain of application: type and road geometry, vehicle type (automatic or manual, passengers, cargo or not, public or private), amount of traffic, weather. Some examples of this driver characterization have been included to demonstrate the process.     

Carbon dioxide emissions from diesel and compressed natural gas buses during acceleration

Motor vehicle emission factors are generally derived from driving tests mimicking steady state conditions or transient drive cycles. Neither of these test conditions, however, completely represents real world driving conditions. In particular, they fail to determine emissions generated during the accelerating phase – a condition in which urban buses spend much of their time. We analyse and compare the results of time-dependant emission measurements conducted on diesel and compressed natural gas buses during an urban driving cycle on a chassis dynamometer and we derive power-law expressions relating carbon dioxide emission factors to the instantaneous speed while accelerating from rest. Emissions during acceleration are compared with that during steady speed operation.     

Impact of license plate restriction policy on emission reduction in Hangzhou using a bottom-up approach

Many emission models have been developed for estimating the impact of transport policies on vehicle emissions. Macroscopic models, such as MOBILE and COPERT, are used for area analysis, while microscopic models, such as CMEM, are applied for corridor analysis. It is well known that driving dynamics are critical for estimating vehicle emissions. MOVES can be used for both macroscopic and microscopic emission analysis, and its advantage lies in the consideration of driving dynamics. Using a bottom-up approach, we study the impact of license plate restriction policy on vehicle emission reduction by localizing the emission rates in MOVES according to the vehicle emission standards in China. We implement the approach to evaluate the impact on the total vehicle emissions in Hangzhou, China before and after the implementation of license plate restriction policy. In the restricted region, the reductions of total Vehicle Kilometer Traveled (VKT) and total emissions are 9.6% and 6.9%, respectively. The result shows that the license plate restriction policy is effective in achieving the targeted emission reduction.     

Electric vehicles: How much range is required for a day’s driving?

One full year of high-resolution driving data from 484 instrumented gasoline vehicles in the US is used to analyze daily driving patterns, and from those infer the range requirements of electric vehicles (EVs). We conservatively assume that EV drivers would not change their current gasoline-fueled driving patterns and that they would charge only once daily, typically at home overnight. Next, the market is segmented into those drivers for whom a limited-range vehicle would meet every day’s range need, and those who could meet their daily range need only if they make adaptations on some days. Adaptations, for example, could mean they have to either recharge during the day, borrow a liquid-fueled vehicle, or save some errands for the subsequent day. From this analysis, with the stated assumptions, we infer the potential market share for limited-range vehicles. For example, we find that 9% of the vehicles in the sample never exceeded 100 miles in one day, and 21% never exceeded 150 miles in one day. These drivers presumably could substitute a limited-range vehicle, like electric vehicles now on the market, for their current gasoline vehicle without any adaptation in their driving at all. For drivers who are willing to make adaptations on 2 days a year, the same 100 mile range EV would meet the needs of 17% of drivers, and if they are willing to adapt every other month (six times a year), it would work for 32% of drivers. Thus, it appears that even modest electric vehicles with today’s limited battery range, if marketed correctly to segments with appropriate driving behavior, comprise a large enough market for substantial vehicle sales. An additional analysis examines driving versus parking by time of day. On the average weekday at 5 pm, only 15% of the vehicles in the sample are on the road; at no time during the year are fewer than 75% of vehicles parked. Also, because the return trip home is widely spread in time, even if all cars plug in and begin charging immediately when they arrive home and park, the increased demand on the electric system is less problematic than prior analyses have suggested.     

Analysis of vehicle emission measurements on the new WLTC,the NEDC and the CADC

Several studies have shown that the type-approval data is not representative for real-world usage. Consequently, the emissions and fuel consumption of the vehicles are underestimated. Aiming at a more dynamic and worldwide harmonised test cycle, the new Worldwide Light-duty Test Cycle is being developed. To analyse the new cycle, we have studied emission results of a test programme of six vehicles on the test cycles WLTC (Worldwide Light-duty Test Cycle), NEDC (New European Driving Cycle) and CADC (Common Artemis Driving Cycle). This paper presents the results of that analysis using two different approaches. The analysis shows that the new driving cycle needs to exhibit realistic warm-up procedures to demonstrate that aftertreatment systems will operate effectively in real service; the first trip of the test cycle could have an important contribution to the total emissions depending on the length of the trip; and that there are some areas in the acceleration vs. vehicle speed map of the new WLTC that are not completely filled, especially between 70 and 110 km/h. For certain vehicles, this has a significant effect on total emissions when comparing this to the CADC.     

Impacts of driving patterns on tank-to-wheel energy use of plug-in hybrid electric vehicles

We evaluate the implications of a range of driving patterns on the tank-to-wheel energy use of plug-in hybrid electric vehicles. The driving patterns, which reflect short distance, low speed, and congested city driving to long distance, high speed, and uncongested highway driving, are estimated using an approach that involves linked traffic assignment and vehicle motion models. We find substantial variation in tank-to-wheel energy use of plug-in hybrid electric vehicles across driving patterns. Tank-to-wheel petroleum energy use on a per kilometer basis is lowest for the city and highest for the highway driving, with the opposite holding for a conventional internal combustion engine vehicle.     

A hazard-based approach to modelling the effects of online shopping on intershopping duration

Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.     

The impact of transportation alternatives on the decision to cease driving by older adults in Japan

This study investigated whether the availability of transportation alternatives for older drivers is a determinant of the decision to cease driving. We recruited participants from a total of 7827 drivers aged 69 years or older living in Ibaraki Prefecture, Japan who were scheduled to renew their driving license between February and April 2011. In November 2010, we distributed questionnaires to collect data on predictors of driving cessation, and again in December 2012 to determine who had actually ceased driving. The relative impacts of factors related to driving cessation were then estimated. Of the 3089 respondents, 157 did not renew their license. The strongest determinants of this decision were having been advised to stop driving and if they had developed less confidence in their ability to drive safely. Even so, respondents were far more likely to have actually stopped driving if they were sure that someone else was available to provide a ride when they needed one. The final decision to stop driving is strongly influenced by personal convenience based on private transport, especially amongst drivers who have been advised to stop. The availability of public transport alternatives is not as important a factor in this decision.     

Getting around a license-plate ban: Behavioral responses to Mexico City’s driving restriction

License-plate-based driving restrictions are among the highest profile policies for local governments to address congestion and air pollution. Cities as varied as Sao Paulo, Paris, Tianjin, and New Delhi have enacted temporary or permanent restrictions to improve local air quality. Using household travel survey data and a research design based on the abrupt shift in how the policy applies to 10-year-old vs. 9-year-old vehicles, we evaluate the impact of Hoy No Circula, one of the earliest and most studied driving restrictions, in Mexico City. In line with previous studies, we find that Hoy No Circula has done little to reduce overall vehicle travel, but we reject the prevailing theory that its lack of success is due to perverse incentives for households to buy second cars. Instead, we highlight the range of other, less costly ways that people adjust behavior to avoid the restrictions. Although no single behavior dominates, most households — particularly those that own older, higher-polluting vehicles — do not use their car every weekday regardless of the restriction. As a result, it is relatively easy to shuffle travel from restricted days to unrestricted days and thus avoid the ban. Shuffling travel days is less costly, more immediately available, and far simpler for most households than buying a second car.