Model,process, technique,and the good thing

The paper unpacks the planning process into its component parts: model, process, technique, and goals—the “good thing”. The paper advances the concept that planning, policy-making, and organizational restructuring can be analyzed under the same framework. Each of the four components is described and reductionist examples are presented to clarify the intention and to illustrate the technique that the transport analyst teams employ in their work. The examples cover both successes and failures. They point toward the enormous scientific task ahead for planning to become meaningful and relevant to the problems of today. Finally, in the frame of the willingness to pay, the paper puts forward a case for an institutional framework for a financially autonomous road administration. Similarly organized, administered, and managed entities are relevant also for other transport modes.

Walking frequency, cars, dogs, and the built environment

To explain walking propensity or frequency, empirical studies have generally used two sets of explanatory variables, namely, socio-demographic variables and built environment variables. They have generally shown that both socio-demographic characteristics and built environment characteristics are associated with walking propensity. We examine the traditional walkability variables that encompass density, mix of uses, and network connectivity in New Jersey, using a statewide sample including an oversample of Jersey City. We estimate a two-stage least squares model using a conditional mixed process that combines an ordered probit model of walking frequency in the second stage based on a truncated regression of car ownership in the first stage. Our results show that built environment variables have some small effects, mainly from better network connectivity associated with increased walking frequency. One of our key findings is that built environment features also work indirectly via how they influence car ownership. In general, we find sufficient evidence that suggests fewer cars are owned in areas with more walkable built environment features. The other key variable that we control for is whether a household owns a dog. This also proved to be strongly associated with walking suggesting that dog ownership is a necessary control variable to understand the frequency of walking.     

Space,money, life-stage,and the allocation of time

Demographic, socioeconomic, seasonal, and scheduling factors affect the allocation of time to various activities. This paper examines those variables through exploration of the 1990 Nationwide Personal Transportation Survey, which has been inverted to track activity duration. Two key issues are considered. First, how much can activity duration and frequency explain travel duration? The analysis shows activity duration has positive and significant effects on travel duration, supporting recent arguments in favor of activity based models. Second, which recent trend is the main culprit in the rise in travel: suburbanization, rising personal incomes, or female labor force participation? This paper examines the share of time within a 24-hour budget allocated to several primary activities: home, work, shop, and other. The data suggest that income and location have modest effects on time allocation compared with the loss of discretionary time due to working.

     

Poverty,policy, and public transportation

By all appearances, the circumstances surrounding employment and income distribution in the United States have remained notably the same over the past 30–40 years. At the same time, policies for improving the conditions of low-income persons have remained relatively unchanged. Relevant published accounts continue to cite poorly integrated residential and employment location patterns and poor public transportation service as critical obstacles to improving the economic and social conditions of low-income persons. The relationship between poverty and public transportation was researched extensively during the late 1960s and the early 1970s; however, little recognition has been given to these efforts by more recent research efforts. To learn from the past we should review public transportation policies from 1960 to 2000 to highlight federal policies that affected urban areas during this time period, especially in relation to low-income transportation mobility.     

Governing autonomous vehicles: emerging responses for safety,liability, privacy,cybersecurity, and industry risks

ABSTRACT

The benefits of autonomous vehicles (AVs) are widely acknowledged, but there are concerns about the extent of these benefits and AV risks and unintended consequences. In this article, we first examine AVs and different categories of the technological risks associated with them. We then explore strategies that can be adopted to address these risks, and explore emerging responses by governments for addressing AV risks. Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications. The US has been active in introducing legislations to address issues related to privacy and cybersecurity. The UK and Germany, in particular, have enacted laws to address liability issues; other countries mostly acknowledge these issues, but have yet to implement specific strategies. To address privacy and cybersecurity risks strategies ranging from introduction or amendment of non-AV specific legislation to creating working groups have been adopted. Much less attention has been paid to issues such as environmental and employment risks, although a few governments have begun programmes to retrain workers who might be negatively affected.     

Activity sequencing,location, and formation of individual non-mandatory tours: application to the activity-based models for Columbus,Cincinnati, and Cleveland,OH

Most of the earlier activity based models (ABMs) largely relied on a tour-based modeling paradigm which explicitly predicts tour frequency and then adds details including stop frequency, order, and location of stops within each tour. The current study is part of new tour formation design framework for an ABM in which the underlying tour structure and the stop frequency within tours emerge from temporal, sequencing, and locational preferences of activities that the traveler intends to participate during the day. In order to do this, the study developed a modified rank-ordered logit (ROL) framework that is capable of modeling sequence, locations, as well as the underlying tour structure of all activity episodes simultaneously in an integrated manner. Model estimation with the household survey data, provided several important behavioral insights into underlying choices that drive tour formation. Specifically, the study uncovered pairwise ordering preferences among episodes of different activity purposes, clustering tendencies among episodes of same activity purpose, the impact of supply side activity opportunities on the location and sequence choice dimensions, and impedance effects (including distance and mode and time-of-day logsums) on location and tour break dimensions. The developed models are incorporated in the operational ABM structure adopted for three major cities (Columbus, Cleveland, and Cincinnati) in Ohio.     

Integrated scheduling of m-truck,m-drone,and m-depot constrained by time-window,drop-pickup,and m-visit using constraint programming

The idea of deploying unmanned aerial vehicles, also known as drones, for final-mile delivery in logistics operations has vitalized this new research stream. One conceivable scenario of using a drone in conjunction with a traditional delivery truck to distribute parcels is discussed in earlier literature and termed the parallel drone scheduling traveling salesman problem (PDSTSP). This study extends the problem by considering two different types of drone tasks: drop and pickup. After a drone completes a drop, the drone can either fly back to depot to deliver the next parcels or fly directly to another customer for pickup. Integrated scheduling of multiple depots hosting a fleet of trucks and a fleet of drones is further studied to achieve an operational excellence. A vehicle that travels near the boundary of the coverage area might be more effective to serve customers that belong to the neighboring depot. This problem is uniquely modeled as an unrelated parallel machine scheduling with sequence dependent setup, precedence-relationship, and reentrant, which gives us a framework to effectively consider those operational challenges. A constraint programming approach is proposed and tested with problem instances of m-truck, m-drone, m-depot, and hundred-customer distributed across an 8-mile square region.     

Adaptive traffic control system: Control strategy,prediction, resolution,and accuracy

Recent advances in traffic control methods have led to flexible control strategies for use in an adaptive traffic control system (ATCS). ATCS aims at controlling the imminent traffic, which is yet to arrive and hence not known perfectly. Therefore, volume prediction is an essential part. Associated with the prediction are two aspects: resolution and accuracy. Recent studies indicate a tradeoff between prediction resolution and accuracy: finer resolutions, larger errors. It is imperative to study the relationship and tradeoff between the control strategy, prediction resolution, and its associated error, which are crucial to the development of ATCS. This study investigates this relationship through an extensive simulation of scenarios in Hong Kong with a recently developed dynamic traffic control model, DISCO. Based on the Hong Kong scenarios conducted with DISCO, the major findings include: (i) the importance of resolution outweighs that of error; (ii) dynamic timing plans generally outperform time‐invariant timing plans; (iii) up to a certain extent, overestimated predictions lead to better results than underestimated predictions.     

Tradeoffs among free-flow speed, capacity, cost, and environmental footprint in highway design

This paper investigates differentiated design standards as a source of capacity additions that are more affordable and have smaller aesthetic and environmental impacts than modern expressways. We consider several tradeoffs, including narrow versus wide lanes and shoulders on an expressway of a given total width, and high-speed expressway versus lower-speed arterial. We quantify the situations in which off-peak traffic is sufficiently great to make it worthwhile to spend more on construction, or to give up some capacity, in order to provide very high off-peak speeds even if peak speeds are limited by congestion. We also consider the implications of differing accident rates. The results support expanding the range of highway designs that are considered when adding capacity to ameliorate urban road congestion.     

Modeling the structural relationships among short-distance travel amounts,perceptions, affections,and desires

Using structural equation modeling, the relationships among travel amounts, perceptions, affections, and desires across five short-distance (one-way trips of less than 100 miles) travel categories (overall, commute, work/school-related, entertainment/social/recreation, and personal vehicle) are examined. The models are estimated using data collected in 1998 from more than 1300 working commuters in the San Francisco Bay Area. A cross-model analysis reveals three robust relationships, namely: (1) myriad measures of travel amounts work together to affect perceptions; (2) perceptions are consistently important in shaping desires; and (3) affections have a positive relationship with desires. The second finding suggests that two individuals who travel the same objective amount may not have the same desire to reduce their travel: how much individuals perceive their travel to be is important. The third point argues that the degree to which travel is enjoyed is a key determinant of shaping desires to reduce travel: the more travel is enjoyed, the less the desire to reduce it.     

Estimation of missing traffic counts using factor,genetic, neural,and regression techniques

Analyses from some of the highway agencies show that up to 50% permanent traffic counts (PTCs) have missing values. It will be difficult to eliminate such a significant portion of data from traffic analysis. Literature review indicates that the limited research uses factor or autoregressive integrated moving average (ARIMA) models for predicting missing values. Factor-based models tend to be less accurate. ARIMA models only use the historical data. In this study, genetically designed neural network and regression models, factor models, and ARIMA models were developed. It was found that genetically designed regression models based on data from before and after the failure had the most accurate results. Average errors for refined models were lower than 1% and the 95th percentile errors were below 2% for counts with stable patterns. Even for counts with relatively unstable patterns, average errors were lower than 3% in most cases.