Influence of connected and autonomous vehicles on traffic flow stability and throughput

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.     

The problem of cold starts: A closer look at mobile source emissions levels

While the phenomenon of excess vehicle emissions from cold-start conditions is well known, the magnitude and duration of this phenomenon is often unclear due to the complex chemical processes involved and uncertainty in the literature on this subject. This paper synthesizes key findings regarding the influence of ambient and engine temperatures on light-duty vehicle (LDV) emissions. Existing literature, as well as analytical tools like the U.S. Environmental Protection Agency’s Motor Vehicle Emission Simulator (MOVES), indicate that while total vehicle emissions have dropped significantly in recent years, those associated with cold starts can still constitute up to 80% for some pollutant species. Starting emissions are consistently found to make up a high proportion of total transportation-related methane (CH₄), nitrous oxide (N₂O), and volatile organic compounds (VOCs). After 3–4 min of vehicle operation, both the engine coolant and the catalytic converter have generally warmed, and emissions are significantly lower. This effect lasts roughly 45 min after the engine is shut off, though the cooling rate depends greatly on the emission species and ambient temperature. Electrically (pre-)heated catalysts, using the bigger batteries available on hybrid drivetrains and plug-in vehicles, may be the most cost-effective technology to bring down a sizable share of mobile source emissions. Trip chaining (to keep engines warm) and shifting to non-motorized modes for shorter trips, where the cold start can dominate emissions, are also valuable tactics.     

Predicting market potential and environmental benefits of deploying electric taxis in Nanjing,China

This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG taxis.     

Network equilibrium models with battery electric vehicles

The limited driving ranges, the scarcity of recharging stations and potentially long battery recharging or swapping time inevitably affect route choices of drivers of battery electric vehicles (BEVs). When traveling between their origins and destinations, this paper assumes that BEV drivers select routes and decide battery recharging plans to minimize their trip times or costs while making sure to complete their trips without running out of charge. With different considerations of flow dependency of energy consumption of BEVs and recharging time, three mathematical models are formulated to describe the resulting network equilibrium flow distributions on regional or metropolitan road networks. Solution algorithms are proposed to solve these models efficiently. Numerical examples are presented to demonstrate the models and solution algorithms.     

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of energy efficient vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (±0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008, i.e., 519 privately owned, exempt EEVs.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

The influence of e-carsharing schemes on electric vehicle adoption and carbon emissions: An emerging economy study

Moving toward sustainable mobility, the sharing economy business model emerges as a prominent practice that can contribute to the transition to sustainability. Using a system dynamics modeling approach, this paper investigates the impacts of an e-carsharing scheme in carbon emissions and in electric vehicle adoption. We study the VAMO scheme located in Fortaleza, Brazil, as the first e-carsharing scheme in the country. We study two policies combined: a VAMO planned growth policy and a retirement policy for conventional vehicles. Our results show that the VAMO incentive policy is an important factor to reduce emissions and to increase awareness of electric vehicles, highlighting the role of the government as an institutional entrepreneur, stimulating and sustaining the VAMO scheme. The retirement policy in combination with the VAMO incentive policy obtained the best results in our simulations, reducing 29% of CO₂ emissions and increasing 36% electric vehicle adoption, when compared to the business-as-usual scenario. The main conclusions are that such e-carsharing schemes offer direct and indirect benefits to urban mobility (specially to electric vehicle adoption) and that they depend on how the government supports them.     

城市轻轨车辆最佳运行控制方案的研究

本文给出一种利用微型机实现城市轨道车辆最佳运行的控制方案,即在变化的外界条件下确定断电和制动时刻,以指导司机驾驶车辆,实现能耗最小和准时运行.该控制方案的特点是不断地利用实测值并结合估算确定断电和制动时刻,简单易行.     

地铁车体结构垂向总载荷和纵向力取值的探讨

针对我国地铁车辆车体强度载荷值不统一的现状 ,通过与国内外地铁强度规范的比较及计算分析 ,并考虑安全性和经济性 ,提出我国地铁车体的垂向载荷和纵向力的建议值