Intermediate modes of transport, such as shared vehicles or ride sharing, are starting to increase their market share at the expense of traditional modes of car, public transport, and taxi. In the advent of autonomous vehicles, single occupancy shared vehicles are expected to substitute at least in part private conventional vehicle trips. The objective of this paper is to estimate the impact of shared autonomous vehicles on average trip duration and vehicle-km traveled in a large metropolitan area. A stated preference online survey was designed to gather data on the willingness to use shared autonomous vehicles. Then, commute trips and home-based other trips were generated microscopically for a synthetic population in the greater Munich metropolitan area. Individuals who traveled by auto were selected to switch from a conventional vehicle to a shared autonomous vehicle subject to their willingness to use them. The effect of shared autonomous vehicles on urban mobility was assessed through traffic simulations in MATSim with a varying autonomous taxi fleet size. The results indicated that the total traveled distance increased by up to 8% after autonomous fleets were introduced. Current travel demand can still be satisfied with an acceptable waiting time when 10 conventional vehicles are replaced with 4 shared autonomous vehicles.

Background: The paper presents a simulation model for freight. In the paper, this model is applied to understand the impacts of electric vans and cargo bikes for the last-mile delivery of parcels. Cargo bikes are electrically assisted vehicles that distribute parcels from micro depots located close to the final customers by means of short tours. The parcels are sent from the major distribution center to micro depots in vans (called feeders). Materials and methods: An agent-based model is used for the purpose of the paper. The model is based on the disaggregation of commodity flows to represent trucks (for all commodities) and individual shipments (for parcel deliveries). The model represents microscopically every freight vehicle in the study area. Results: The simulation of various scenarios with different shares of cargo bikes and electric vans assesses the impacts of electrification and cargo bikes. The use of cargo bikes to deliver parcels allows to reduce the number of motorized vehicles, although the presence of large parcels requires that at least half of deliveries by vans are still required. The shift to cargo bikes represents a slight increase in the total operating time to deliver the parcel demand. With low shares of cargo bikes, the total distance traveled increases, since the reduction of van tours cannot compensate the additional feeder trips from distribution centers to micro depots. The cargo bikes also do not reduce the number of vehicles for the served area, but modify the composition of vehicle types. Low noise, smaller, low emission vehicles increase, while delivery vans are reduced. Conclusion: Both cargo bikes and electric vans are able to reduce CO2 emissions, even after accounting for the emissions related to electricity production.

The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.

Drivers need sufficient passing sight distance (PSD) to pass slower vehicles with safety. This distance can help to improve traffic operation on two-way, two-lane highways. Existing models propose different values of PSD because of different assumptions. In only some cases were these models based on field data of passing maneuvers. This research proposed the design of a methodology to observe passing maneuvers on existing highways with the help of six video cameras installed at a fixed point next to passing sections. The use of more cameras allows complete registration of trajectories along the entire passing zone, with uniform image resolution. The methodology was applied to register a sample of 234 maneuvers on four passing zones. Trajectories of 58 maneuvers were completely described and analyzed with specific restitution software. Results were compared with those from existing PSD models. The distances traveled proposed by the AASHTO model on the left lane were (a) similar to average observed distances when the passed vehicle was one truck and (b) between 50 and 100 m higher when one passenger car was passed. Higher differences, greater than 100 m, were found between measured data and the PSD model (published previously), especially at high design speeds. The observed average speed difference between passing and impeding vehicles was significantly higher than that in any model. Variables with the strongest influence on the time and distance traveled on the opposing lane were the type and speed of the passed vehicle and the length of the passing zone. Left-lane time and distance increase with this length.

Integrated land-use/transport models have five decades of history of both widely recognized successful implementations and implementations that remained far behind their originally stated goals. This paper summarizes the state of the art of integrated land-use/transport modeling and reports on findings from the Symposium for the Integration of Land-Use and Transport Models in Raitenhaslach, which is near Munich, in 2016. From these sources, the paper identifies major challenges in integrated land-use/transport modeling and proposes paths that support successful implementations. Particular attention is given to the coordination of short- and long-term decisions, the technical integration of models, microscopic versus macroscopic frameworks and appropriate levels of model complexity. The paper concludes with five themes that require further research to ensure that integrated land-use/transport models will keep up with modeling needs in the future.