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Transport demand models were initially designed for simulating car trips. Nowadays researchers and planners are considering pedestrian travel and its health and safety impacts in the regional transport models. However, the existing transport models lack the knowledge and experience in pedestrian modeling for health assessment. This paper contributes to the modeling practice by developing an integrated model called the MITO/MoPeD. The model builds upon previous model development and integrates the fine-grained pedestrian modeling tool into the agent-based transport model. The MITO/MoPeD model is applied to the Munich metropolitan area. Model performances are analyzed based on travel measures (e.g., walk share, trip length distribution, and pedestrian flow) and physical activity volumes. Results show that the MITO/MoPeD model can better represent pedestrian travel behavior than the existing Munich Model. It performed better in simulating the spatial distribution of walk shares and the distribution of walk trip lengths. Moreover, it overcomes the issue of overestimating physical activity volumes. These findings suggest that the MITO/MoPeD model can deliver more precise travel outcomes. More importantly, it is valuable for addressing pedestrian planning issues such as transportation infrastructure investments, land use planning, assessment of safety and health outcomes, and evaluation of environmental impacts. [ABSTRACT FROM AUTHOR]

Excess commute (EC) refers to the sub-optimal allocation of workers to jobs in an urban region in terms of minimal commute distances. This article investigated EC for the Munich metropolitan area using a microscopic agent-based modeling suite. We first considered the optimization strategy, comparing the traditional zone-based transportation problem to a microscopic routine. Zonebased optimization is computationally efficient, but it underestimates EC due to spatial biases, even when the zone system is highly disaggregate. We then applied the optimized job-worker assignment to a microscopic travel demand model, assigning workers to jobs of the same job sector at a shorter distance from their home, accounting for multi-worker households. With shorter commutes, there was a substantial shift toward active modes. However, we only observed moderate impacts on total travel demand, with the overall effect dampened due to compensatory behavior between mandatory and discretionary travel. Finally, the outputs from the demand model were used by a microscopic assignment model to calculate externalities attributable to EC. Because of the complexity of travel demand, we conclude that the EC indicator alone would overestimate the benefits of policies targeting jobs-housing balance. [ABSTRACT FROM AUTHOR]

This paper describes an improved noise modeling approach for the agent-based transport simulation MATSim. In contrast to previous versions, the new implementation takes into account the shielding of noise at building facades. The simplified approach is based on German noise modeling guidelines. As a proof of concept, a comparative calculation of noise immissions for a use case in the city of Munich with and without the consideration of buildings reveals more realistic immission values when shielding is taken into account. While uncovered areas are not affected by the updated calculation, backyards and areas behind larger building blocks show a major reduction in immissions. When looking at noise exposure costs in a dense area, ignoring the effect of shielding seems to significantly overestimate costs by up to 20%. The presented approach is a step forwards incorporating environmental aspects in an agent-based integrated land use/transport modeling suite. [ABSTRACT FROM AUTHOR]

Most travel demand models simplify the representation of trips from/to external zones. Despite the higher frequency of internal daily travel, long-distance travel cannot be neglected due to its high contribution to the travelled distance. In this paper we integrate two different models that represent those two travel segments. MITO is an agent-based model for travel demand implemented in the metropolitan area of Munich. DEMO is a macroscopic model that generates travel demand in Germany. DEMO is used to represent the external, long-distance travel from, to or through the MITO study area. DEMO demand is disaggregated and is jointly assigned with MITO trips using the transport model MATSim. The integration significantly improves the validation of the model against traffic counts and facilitates the simulation capabilities when the scenarios affect major roads. [ABSTRACT FROM AUTHOR]

This paper describes an improved noise modeling approach for the agent-based transport simulation MATSim. In contrast to previous versions, the new implementation takes into account the shielding of noise at building facades. The simplified approach is based on German noise modeling guidelines. As a proof of concept, a comparative calculation of noise immissions for a use case in the city of Munich with and without the consideration of buildings reveals more realistic immission values when shielding is taken into account. While uncovered areas are not affected by the updated calculation, backyards and areas behind larger building blocks show a major reduction in immissions. When looking at noise exposure costs in a dense area, ignoring the effect of shielding seems to significantly overestimate costs by up to 20%. The presented approach is a step forwards incorporating environmental aspects in an agent-based integrated land use/transport modeling suite. [ABSTRACT FROM AUTHOR]

Most travel demand models simplify the representation of trips from/to external zones. Despite the higher frequency of internal daily travel, long-distance travel cannot be neglected due to its high contribution to the travelled distance. In this paper we integrate two different models that represent those two travel segments. MITO is an agent-based model for travel demand implemented in the metropolitan area of Munich. DEMO is a macroscopic model that generates travel demand in Germany. DEMO is used to represent the external, long-distance travel from, to or through the MITO study area. DEMO demand is disaggregated and is jointly assigned with MITO trips using the transport model MATSim. The integration significantly improves the validation of the model against traffic counts and facilitates the simulation capabilities when the scenarios affect major roads. [ABSTRACT FROM AUTHOR]

• 2% of current car fleet is necessary to transport all car trips. • Vehicle kilometers travelled are reduced by up to 54% with ride-pooling. • Stop-based on-demand systems facilitate reductions of noise exposure. • Door-to-door systems may increase traffic and noise in residential areas. Pooled on-demand services promise to provide a convenient mobility experience and increase efficiency of road transport. We apply an established ride-pooling algorithm within the simulation framework MATSim to an autonomous fleet serving almost 2 million requests in Munich. Two mode choice scenarios are implemented, one substituting all car trips by ride-pooling, another one with free mode choice. For both scenarios we compare a stop-based and a door-to-door service in terms of system efficiency and noise imissions, applying an updated noise prediction model in MATSim. The results contribute to the systematic analysis of ride-pooling and show the effects of the proposed policies and service designs, which are essential for an efficient system with low noise exposure. Replacing all car trips by a stop-based ride-pooling system leads to a drastic noise reduction in residential areas whereas door-to-door systems may even increase noise exposure due to additional pick-up/drop-off rides and detours. [ABSTRACT FROM AUTHOR]