Incorporating human-factors in car-following models: A review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.     

Within day rescheduling microsimulation combined with macrosimulated traffic

The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.     

Strategies to achieve deep reductions in metropolitan transportation GHG emissions: the case of Philadelphia

ABSTRACT

This paper investigates strategies that could achieve an 80% reduction in transportation emissions from current levels by 2050 in the City of Philadelphia. The baseline daily lifecycle emissions generated by road transportation in the Greater Philadelphia Region in 2012 were quantified using trip information from the 2012 Household Travel Survey (HTS). Emissions were projected to the year 2050 accounting for population growth and trends in vehicle technology for both the Greater Philadelphia Region and the City of Philadelphia. The impacts of vehicle technology and shifts in travel modes on greenhouse gas (GHG) emissions in 2050 were quantified using a scenario approach. The analysis of 12 different scenarios suggests that 80% reduction in emissions is technically feasible through a combination of active transportation, cleaner fuels for public transit vehicles, and a significant market penetration of battery-electric vehicles. The additional electricity demand associated with greater use of electric vehicles could amount to 10.8 TWh/year. The use of plug-in hybrid electric vehicles (PHEV) shows promising results due to high reductions in GHG emissions at a potentially manageable cost.     

Women’s mode and trip structure choices in daily activity-travel: a developing country perspective

ABSTRACT

In this paper, we analyze the travel patterns of Iranian women, where typical patriarchal views and specific social and cultural norms may differ from the patterns of those in western societies. In addition to inherent psycho-physical gender differences, women in Iran can face special constraints forcing them not to be involved in all activity-travel patterns that people in developed countries usually undertake. We pay special attention to the role of marital and employment status on women’s activity-travel patterns. To this end, we develop a joint mode and daily activity pattern (DAP) discrete choice model, which is a two-level mixed nested Logit. The upper nest of the proposed model embodies women’s DAP choices, and the lower nest belongs to the mode choices. In this paper, we try to show how different factors in a patriarchal Muslim society like Iran affect or restrict women’s type and structure of activity-travel patterns.     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

Non‐compatible chemicals as cargoes in industry,on road,rail, and water

Toronto is to have an urban transit system with a passenger carrying capacity which fills the gap between the capacity of the subway and the capacity of the car and bus. Correspondingly, in the words of the Premier of Ontario, the system will “make possible an attractive alternative to high‐rise, high‐density living and urban sprawl. . . .” Furthermore, the new system is sufficiently economical to provide “. . . an encouragement to growth in appropriate areas, rather than merely responding to growth as it occurs . . .”

The decision to have such a system is the culmination of some years of major transportation activities in the Province, which included the Metropolitan Toronto and Region Transportation Study (MTARTS) of 1962. This study pursued both urban expressways and public transport solutions to the movement of people in Metropolitan Toronto.

The urban expressways programmes ran into difficulties, on environmental terms, when strong opposition from community groups was met on proposed routes. A climax came when the Ontario Government halted the construction of the controversial Spadina expressway in June 1971. However, the programmes of public transport solutions met with great success. The Toronto subway and its extensions, together with the change in land values along the route, has become a classic success story. So, too, has the introduction of the GO Train Service (Government of Ontario train service). This pioneered a combination of commuter rail service and integrated feeder buses and today replaces some 14,000 cars each day along the lakeshore highways.

The success of the subway and the GO train coupled with the difficulties experienced by the urban expressways programme, gave rise to the realisation that a better city through public transport rather than the car, was practicable. However, subways were too expensive and they needed a large patronage in a narrow corridor. Accordingly, an intermediate capacity transit system was sought.

The paper describes the programme of activities involved in the choice of the system and describes the technical specification which the system will enjoy. In particular, the demonstration installation which is to be set‐up in Toronto is described in detail, together with the plans to instal some 56 miles over five routes in Metropolitan Toronto.     

Eco-driver training within the City of Calgary’s municipal fleet: Monitoring the impact

This article highlights eco-driving as an available policy option to reduce climate altering GHG emissions. Recognizing the need to reduce the environmental impact of its fleet operations, the City of Calgary is a leader in developing programs and policies that aim to reduce GHG emissions and associated pollutants resulting from the use of fossil fuels. Among local action taken against climate change, the City sought to quantify CO₂ emissions reductions from their municipal fleet as a result of eco-driver training, with a specific focus on engine idling. Fifteen drivers from the Development & Building Approvals Business Unit had in-vehicle monitoring technology (CarChips®) installed into their vehicles as part of a three-phase research process. The results show that gasoline and hybrid vehicles decreased average idling between 4% and 10% per vehicle per day, leading to an average emissions decrease of 1.7 kg of CO₂ per vehicle per day.     

旅客购票模式与渠道关联选择行为的建模分析

为分析多元化售票渠道下旅客购票选择行为的影响因素及交互特征，解析了多渠道情境下旅客购票过程的 3个阶段，辨识了旅客购票的 3类典型模式；运用协同进化分析思想，建立了购票模式与渠道关联选择的协同进化 Logit模型；基于道路客运联网售票信息系统数据，进行了模型的实证应用，分析了特征变量对旅客购票选择行为的影响，揭示了渠道与模式间关联选择行为特征.研究表明：性别，年龄，提前购票时间，出行时间，出行里程，发车频率等因素对旅客购票行为有显著影响；旅客购票模式和渠道选择间存在相关性，某一决策选择受另一决策结果的影响；考虑两者的交互作用有助于提高分析预测精度，2类决策模型的精度分别提高了5.98%和5.72%.     

Evaluation of the effectiveness of accident information on freeway changeable message signs: A comparison of empirical methodologies

In this paper, we study the effectiveness of accident messages that are displayed on freeway changeable message signs (CMS). Motivated by the lack of empirical studies and the mixed results reported in the limited empirical studies, this paper focuses on the comparison of different aggregate analysis methodologies and their corresponding results, using the same empirical data set. We have two major findings. First, we find that the CMS accident messages do not seem to have any significant immediate effect on driver diversion based on our empirical data. Visible congestion, on the other hand, seems to be an important factor for driver diversion. Second, we show how the conclusion could have been if wrong methodologies were to be adopted. Methods that rely on correlation alone but not the timing of events (what we call correlation method) yield high correlation between CMS accident messages and driver diversion, which is typically and incorrectly interpreted as CMS accident messages being effective.     

Using the built environment to oversample walk,transit, and bicycle travel

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a ¼ mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle.