Highway Capacity Manual改訂の動向--テイラ-教授の講演より

In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the energy consumption and carbon emissions of electric vehicles. Second, we propose a mixed integer programming model to minimize the total costs related to electric vehicle energy consumption and travel time. To solve this model efficiently, we develop an adaptive genetic algorithm based on hill climbing optimization and neighborhood search. The crossover and mutation probabilities are designed to adaptively adjust with the change of population fitness. The hill climbing search is used to enhance the local search ability of the algorithm. In order to satisfy the constraints of battery life and battery swapping stations, the neighborhood search strategy is applied to obtain the final optimal feasible solution. Finally, we conduct numerical experiments to test the performance of the algorithm. Computational results illustrate that a routing arrangement that accounts for power consumption and travel time can reduce carbon emissions and total logistics delivery costs. Moreover, we demonstrate the effect of adaptive crossover and mutation probabilities on the optimal solution.

https://www.mdpi.com/2071-1050/12/24/10537/pdf

Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions

Autonomous vehicles (AVs) may significantly change traveler behavior and network congestion. Empty repositioning trips allow travelers to avoid parking fees or share the vehicle with other household members. Computer precision and reaction times may also increase road and intersection capacities. AVs are currently being test driven on public roads and may be publicly available within the next two decades; they therefore may be within the span of 20- to 30-year planning analyses. Despite this time scale, AV behavior has yet to be incorporated into planning models. This paper presents a multiclass, four-step model that includes AV repositioning to avoid parking fees (although incurring additional fuel costs) and increases in link capacity as a function of the proportion of AVs on the link. Demand is divided into classes by value of time and AV ownership. Mode choice—parking, repositioning, or transit—is determined through a nested logit model. Traffic assignment is based on a generalized cost function of ti...

Effects of Autonomous Vehicle Ownership on Trip, Mode, and Route Choice

The bottleneck model introduced by Vickrey in 1969 has been recognized as a benchmark representation of the peak-period traffic congestion due to its ability to capture the essence of congestion dynamics in a simple and tractable way. This paper aims to provide a 50th anniversary review of the bottleneck model research since its inception. A bibliometric analysis approach is adopted for identifying the distribution of all journal publications, influential papers, top contributing authors, and leading topics in the past half century. The literature is classified according to recurring themes into travel behavior analysis, demand-side strategies, supply-side strategies, and joint strategies of demand and supply sides. For each theme, typical extended models developed to date are surveyed. Some potential directions for further studies are discussed.

Fifty years of the bottleneck model: A bibliometric review and future research directions

In California, High-Occupancy Vehicle (HOV) lanes have been implemented with two different configurations—continuous access HOV lanes, primarily used in Northern California, and limited access HOV lanes, primarily used in Southern California. Using a new emissions modeling methodology, this study estimates and compares vehicle emissions contributed from these two types of HOV lane configurations. A twelve mile freeway corridor was coded, calibrated, and simulated in a high-fidelity microscopic traffic simulation model. A state-of-the-art modal emissions model has been interfaced with the traffic simulation and emissions have been estimated for each vehicle’s driving trajectory. Under different scenarios with varying levels of travel demand and percentages of HOVs in the traffic mix, it was found that the network with continuous access HOV lanes consistently produced lower levels of pollutant emission compared to the network with limited access HOV lanes. Carbon monoxide was lower by 12-17%, hydrocarbons by 7-13%, and nitrogen oxides and carbon dioxide by 3-8%. These results were primarily due to the highly concentrated weaving maneuvers that take place on the dedicated ingress/egress sections in the limited access HOV network, causing a relatively higher frequency and magnitude of acceleration/deceleration events, resulting in higher emissions on these sections of the freeway. These findings from this study should be taken into consideration when implementing an HOV system, especially in the areas that have not met necessary air quality standards.

Impacts of Freeway High-Occupancy-Vehicle Lane Configurations onVehicle Emissions

This study is the first in the literature to analytically investigate the traffic dynamics of the integrated morning and evening commutes when daily trips are completed with autonomous vehicles (AVs). Given the parking locations of AVs resulting from the morning commute, firstly we analyse the evening commuting pattern, at which no traveller can reduce the individual travel cost given other AVs’ times of departures from the parking spaces. The equilibrium traffic pattern at the evening commute is then integrated with the morning commute, where equilibrium choices of departure time from home and parking location are derived and analysed. We then study the integrated morning-evening commuting pattern at the system optimum and develop the road tolling scheme to achieve the system optimum. Furthermore, this study analyses the optimal AV parking supply strategy to minimise the total system cost, which is comprised of the total social parking cost and the total daily travel cost under either user equilibrium or system optimum traffic pattern. We also illustrate the modelling insights through numerical studies regarding relationship among traffic efficiency, tolling schemes and AV parking supply plans. This study highlights the differences in daily commuting and parking patterns between the AV situation and the non-AV situation, and sheds light on how traffic and parking should be managed or planned in the future.

Modelling and managing the integrated morning-evening commuting and parking patterns under the fully autonomous vehicle environment

A network traffic assignment model for autonomous vehicles with parking choices

An ensemble machine learning‐based modeling framework for analysis of traffic crash frequency

The motivation of this study is to minimize the system‐level travel time costs and greenhouse emissions, which include tailpipe emissions by internal combustion engine vehicles (ICEVs) and...

Multitype Recharge Facility Location for Electric Vehicles

The objective of this study is to propose a novel definition of equity from the perspective of link performance with energy consumption and incorporate equity into the transportation network design problem (NDP). First, we introduce an aggregated equity measure and present the theoretical framework for the equity considering link travel time and energy consumption along with free flow traffic conditions. We demonstrate that a Braess paradox situation exists with regards to the proposed equity measure. Second, we formulate a bi-level modelling framework for the Link-based Equitable NDP (
 $$LE$$
 -NDP). The model is a multiobjective optimization program, where the upper level aims to minimize the total system travel time and optimize equity levels with respect to both travel time and energy consumption. The lower level then represents the flow response under user equilibrium conditions. To quantify the performance loss incurred relative to the equity criterion, we formulate the function of the price of fairness within the $$LE$$
 -NDP. Third, to solve the $$LE$$
 -NDP model, we develop a tailored heuristic solution method, which simulates the interaction between planners and travellers. The solution approach uses an $$\varepsilon$$
 -constraint method to identify Pareto-efficient solutions, and constraint optimization formulations are presented to solve the resulting single-objective program. Finally, the efficacy of the model and the solution algorithm is validated via case studies on three traffic networks. The results demonstrate that the proposed modelling device is capable of achieving more balanced solutions when the equity metrics are accounted for, and the developed solution method is efficient as a reference method in practice. The results also show the trade-offs between travel time and link-based equity, and indicate that equity metrics in terms of different travel costs, i.e. travel time and energy consumption, are shown to be conflicting design objectives for certain scenarios.

Xiang Zhang

Papers

Modelling and managing the integrated morning-evening commuting and parking patterns under the fully autonomous vehicle environment

A network traffic assignment model for autonomous vehicles with parking choices

An ensemble machine learning‐based modeling framework for analysis of traffic crash frequency

Multitype Recharge Facility Location for Electric Vehicles

Implications of link-based equity objectives on transportation network design problem