Several urban areas in the United States have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. As an example, the city of Charlotte has extended its current light rail transit (LRT) line (from South Charlotte to Uptown) to the University area in the northeast part of the region. Subsequently, there are plans to add more LRT routes and build pedestrian- and bicyclist-friendly infrastructure (e.g., on-street bicycle lanes, sidewalks, crosswalks, pedestrian signals, and so on). However, there is not enough evidence to justify whether such plans are instrumental in improving mobility and enhancing safety of the transportation system from a multimodal perspective. Further, there are no widely accepted methods to assess the effect of such facilities or transportation projects in terms of improved mobility and enhanced user safety. Therefore, the goal of this research is to model the operational performance of urban roads with heterogeneous traffic conditions to improve the safety, reliability, and mobility of people and goods. The objectives are 1. to collect data and comprehensively evaluate the effect of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time and travel time reliability (TTR) from a multimodal perspective, 2. to simulate and evaluate the influence of pedestrians, bicyclists, and public transportation system users (bus and LRT) on transportation system performance from a multimodal perspective, 3. to model and evaluate the effects on the operational performance at intersection level and corridor level by time of the day, 4. to research and examine the effects on the study corridor, parallel route, and cross-streets, and, 5. to conduct safety assessment by modeling and estimating traffic conflicts from a multimodal perspective. First, a TTR-based approach was used to assess the effect of the LRT system on the road network within its vicinity. A four-mile stretch of the Blue Line LRT extension, which connects Old Concord Road and the University of North Carolina at Charlotte’s main campus in Charlotte, North Carolina (NC), was considered as the study corridor. The raw travel time data were collected from a private data source at one-minute intervals. The average travel time (ATT), planning time (PT), buffer time (BT), buffer time index (BTI), and planning time index (PTI) were computed for each link, by day-of-the-week and time-of-day. Further, the TTR of the links on the LRT extension corridor and adjacent corridors (both the parallel route and the cross-streets) were computed for different scenarios: network without LRT, sixth month of LRT operation, twelfth month of LRT operation, and eighteenth month of LRT operation. The research revealed that the TTR of the parallel route and cross-streets was affected by the LRT system operation. Increased green signal times along N Tryon St as the LRT runs in parallel to this road, better signal coordination on this road, and the benefits associated with the alternative mode/route choice for commuters may be the reasons behind the steadiness in travel time performance measures seen due to the LRT. Simulation-based analysis was conducted using data for a 2.5-mile corridor along the new LRT route. The traffic and signal data were obtained from the City of Charlotte Department of Transportation (CDoT). There are no midblock or unsignalized crosswalks along the study corridor. The facilities and timings provided for pedestrians and bicycles at intersections seem to be adequate enough based on current or projected activity levels. Models were built in Vissim for the following scenarios: LRT is in operation with vehicles, LRT is in operation with vehicles and pedestrian activity, LRT is in operation with vehicles, pedestrians and bicyclist activity, change in vehicular traffic with LRT in operation with bicyclist activity and pedestrians, and increase in pedestrian and bicyclist activity with vehicles in the network. Bing maps data were used to import the network characteristics for each scenario. Vehicle delay, maximum queue length, and level of service (LOS) were used as the performance measures to evaluate the effect of the LRT on the transportation system’s performance. It was found that the increase in LRT frequency has increased the vehicle delay on cross-streets while the operational performance improved on the study corridor. It was observed that a 15% or higher increase in the number of vehicles deteriorated the operational performance of the corridor. There has been not much change in the operational performance at some of the intersections, but the vehicles seem to accumulate at the intersections with additional delay during the evening peak hour. An increase in pedestrian and bicycle activity affected the overall corridor performance marginally. The intersections close to the LRT stations have had deteriorated operational performance. Surrogate safety assessment was performed for all the hypothetical scenarios at a corridor level, and more than a 100% increase in traffic conflicts was seen with a 15% increase in vehicular traffic. A 15% increase in traffic conflicts was observed when pedestrian and bicycle count was increased by 100%. Many growing cities are transitioning toward multimodal mobility patterns by providing infrastructure for transit users, pedestrians, and bicyclists. Planning and building infrastructure for alternative modes results in a shift in transportation demand from motorized to non-motorized traffic and increases complexities which arise due to the interaction amongst multiple models of transportation. This research proposes the use of travel time analysis and simulation framework to evaluate and understand these complex interactions and mobility patterns. The methodological framework used in this research is cross-disciplinary, transferable, and can be applied to other regions.